As one of the first authors to publish a book on generative AI, she has emerged as a sought-after speaker helping global leaders, businesses, and institutions understand and adapt to this transformative moment.

We spoke to Nina to explore the future of AI-driven innovation, its ethical and political dimensions, and how organisations can lead in this rapidly evolving landscape.

In your view, how will generative AI redefine the foundational structures of business and economic productivity in the coming decade?

I believe generative AI is absolutely going to transform the entire economy as we know it. This moment feels quite similar to around 1993, when we were first being told to prepare for the Internet. Back then, some thirty years ago, we didn’t fully grasp, in our naivety, how profoundly the Internet would go on to reshape business and the broader global economy.

Now, we are witnessing something even more significant. You can think of generative AI as a kind of new combustion engine, but for all forms of human creative and intelligent activity. It’s a fundamental enabler. Every industry, every facet of productivity, will be impacted and ultimately transformed by generative AI. We’re already beginning to see those use cases emerge, and this is only the beginning.

As AI and data continue to evolve as forces shaping society, how do you see them redefining the political agenda and global power dynamics?

When you reflect on just how profound AI is in its capacity to reshape the entire framework of society, it becomes clear that this AI revolution is going to emerge as one of the most important political questions of our generation. Over the past 30 years, we’ve already seen how the information revolution — driven by the Internet, smartphones, and cloud computing — has become a defining geopolitical force.

Now, we’re layering the AI revolution on top of that, along with the data that fuels it, and the impact is nothing short of seismic. This will evolve into one of the most pressing and influential issues society must address over the coming decades. So, to answer the question directly — AI won’t just influence politics; it will, in many ways, become the very fabric of politics itself.

There’s been much discussion about the Metaverse and immersive tech — how do you see these experiences evolving, and what role do you believe AI will play in architecting this next frontier of digital interaction?

The Metaverse represents a vision for where the Internet may be heading — a future where digital experiences become far more immersive, intuitive, and experiential. It’s a concept that imagines how we might engage with digital content in a far more lifelike way.

But the really fascinating element here is that artificial intelligence is the key enabler — the actual vehicle — that will allow us to build and scale these kinds of immersive digital environments. So, even though the Metaverse remains largely an untested concept in terms of its final form, what is clear right now is that AI is going to be the engine that generates and populates the content that will live within these immersive spaces.

Considering the transformative power of AI and big data, what ethical imperatives must policymakers and society address to ensure equitable and responsible deployment?

The conversation around ethics, artificial intelligence, and big data is one that is set to become intensely political and highly consequential. It will likely remain a predominant issue for many years to come.

What we’re dealing with here is a technology so transformative that it has the potential to reshape the economy, redefine the labour market, and fundamentally alter the structure of society itself. That’s why the ethical questions — how to ensure this technology is applied in a fair, safe, and responsible manner — will be one of the defining political challenges of our time.

For business leaders navigating digital transformation, what mindset shifts are essential to meaningfully integrate AI into long-term strategy and operations?

For businesses aiming to digitally transform, especially in the era of artificial intelligence, it’s critical to first understand the conceptual paradigm shift we are currently undergoing. Once that foundational understanding is in place, it becomes much easier to explore and adopt AI technologies effectively.

If companies wish to remain competitive and gain a strategic edge, now is the time to start investigating how generative AI can be thoughtfully and effectively integrated into their business models. This includes identifying priority areas where AI can deliver long-term value — not just short-term.

If you put together a generative AI working group to look into this, your business will be transformed and able to compete with other businesses that are using AI to transform their processes.

As one of the earliest voices to articulate the societal implications of generative AI, what catalysed your foresight to explore this space before it entered the mainstream conversation?

My interest in AI didn’t come from a technical background. I’m not a techie. My experience has always been in analysing macro trends that shape society, geopolitics, and the wider world. That perspective is what led me to AI, as it quickly became clear that this technology would have far-reaching societal implications.

I began researching and writing about AI because I saw it as more than just a technological shift. Ultimately, this isn’t only a story about innovation. It’s a story about humanity. Generative AI, as an exponential technology built and directed by humans, is going to transform not just the way we work, but the way we live. It will even challenge our understanding of what it means to be human.

Photo by Heidi Fin on Unsplash

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

The post Nina Schick, author: Generative AI’s impact on business, politics and society appeared first on AI News.

However despite the benefits of the technology, many businesses are slow to adopt the technology, with recent statistics showing only one in ten of SME’s regularly use AI technology, indicating companies and employees are still not operating at their full potential, thus missing out on opportunities for growth and optimisation. 

Transforming the supply chain through AI

The potential that AI has in the supply chain is undeniable, with some estimating that AI helps businesses reduce logistics costs by 15%, reduce inventory levels by 35% and raise service levels by 65%. In contrast, failure to implement AI tools could set companies back, leave employees feeling unmotivated and unproductive and result in a weak supply chain and poor staff retention.

Now, more than ever, it’s time for businesses to not just pay lip service to AI – they must start using it within their supply chains to truly enhance operations. Due to the evolving market dynamics, AI is not just a competitive advantage; it’s essential for business agility and profitability. Here are two ways in which organisations can use AI to improve their supply chains.

Automating the supply chain & harnessing the power of AI for resilience

AI allows businesses to tackle supply chain challenges head-on by automating time-consuming manual processes, such as data-logging whilst reducing errors. By taking over repetitive and potentially hazardous tasks, AI frees up employees to focus on strategic initiatives that drive business value. For example, a recent report highlighted that nearly three quarters of warehouse staff surveyed are excited about the possibilities of generative AI and robotics improving their job roles.

Needless to say, a supply chain still can’t operate at its peak without resilience – which is the capacity of a supply chain to withstand and recover from disruptions – ensuring uninterrupted operations and minimal impact to businesses and customers.

As global markets continue to evolve & expand, businesses are challenged to adapt swiftly to unforeseen disruptions. AI enables businesses to provide real time data analysis, providing unprecedented insights into the web of supply chain dynamics and acting as the eyes and ears of a supply chain. This empowers each component with the ability to make informed decisions quickly to meet supply chain demands. Allowing insights into every aspect of their warehouse operations, real time data enables visibility which permits precise monitoring, enhanced customer service and reduced downtime – identifying potential issues before they become a major problem.

At the heart of the supply chain is communication between all stakeholders, with technology such as AI providing real time data, seamless collaboration is enabled by providing a shared platform where suppliers, manufacturers, and distributors can exchange information instantaneously. Enhanced communication leads to quicker issue resolution, enabling the supply chain to adapt rapidly to changing circumstances. Robotics, AI and real-time data introduce an all-encompassing visibility of the good’s journey, which leads to resilience.

Human expertise with robot precision

Building on the theme of resilience, in the next couple of years the industry will witness AI-integrated robots becoming collaborative partners to their human co-workers. Particularly in environments requiring vast coverage and extensive data capture, robots that are equipped with groundbreaking sensor technologies will navigate, adapt and work with greater levels of autonomy along with other machinery and people in busy environments. This will result in speed of data acquisition and most importantly, allowing companies to make decisions based on actionable insights a lot faster than ever before. 

These advancements will transform robots into true cobots and will take human-robot teamwork to an unprecedented level. We will also see that robots will become better with understanding nuanced human gestures and intentions. This evolution in collaboration with technology will redefine what humans and machines can accomplish together.

What’s next for the industry?

In theory implementing AI and advanced technology in the supply chain has the potential to bring significant benefits. However, we will only begin to see substantial results once these innovations are widely adopted in practice. By automating the supply chain and using data to fuel predictions, these technologies are the foundations for a new industrial revolution that will shape the future of the industries for years to come. Those that delay starting their journeys will risk being left behind.

Photo by Miltiadis Fragkidis on Unsplash

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post How can AI unlock human potential in the supply chain? appeared first on AI News.

We spoke to Kay to discuss the promise and pitfalls of generative AI, the future of the Metaverse, and how organisations can prepare for a decade of unprecedented digital transformation.

Generative AI has captured global attention, but there’s still a great deal of misunderstanding around what it actually is. Could you walk us through what defines generative AI, how it works, and why it’s considered such a transformative evolution of artificial intelligence?

It’s very exciting because it represents the next iteration of artificial intelligence. What generative AI allows you to do is ask questions of the world’s data simply by typing a prompt. If we think back to science fiction, that’s essentially what we’ve always dreamed of — just being able to ask a computer a question and have it draw on all its knowledge to provide an answer.

How does it do that? Well, it predicts which word is likely to come next in a sequence. It does this by accessing enormous volumes of data. We refer to these as large language models. Essentially, the machine ‘reads’ — or at least accesses — all the data available on the open web. In some cases, and this is an area of legal contention, it also accesses IP-protected and copyrighted material. We can expect a great deal of legal debate in this space.

Once the model has ingested all this data, it begins to predict what word naturally follows another, enabling it to construct highly complex and nuanced responses. Anyone who has experimented with it knows that it can return some surprisingly eloquent and insightful content simply through this predictive capability.

Of course, sometimes it gets things wrong. In the AI community, we call this ‘hallucination’ — essentially, the system fabricates information. That’s a serious issue because in order to rely on AI-generated outputs, we need to reach a point where we can trust the responses. The problem is, once a hallucination enters the data pool, it can be repeated and reinforced by the model.

While much has been said about generative AI’s technical potential, what do you see as the most meaningful societal and business benefits it offers? And what challenges must we address to ensure these advantages are equitably realised?

AI is now accessible to everyone, and that’s incredibly powerful. It’s a hugely democratising tool. It means that small and medium-sized enterprises, which previously couldn’t afford to leverage AI, now can.

However, we also need to be aware that most of the world’s data is created in the United States first, followed by Europe and China. There are clear challenges regarding the datasets these large language models are trained on. They’re not truly using ‘global’ data. They’re working with a limited subset. That has led to discussions around digital colonisation, where content generated from American and European data is projected onto the rest of the world, with an implicit expectation that others will adopt and use it.

Different cultures, of course, require different responses. So, while there are countless benefits to generative AI, there are also significant challenges that we must address if we want to ensure fair and inclusive outcomes.

The Metaverse has seen both hype and hesitation in recent years. From your perspective, what is the current trajectory of the Metaverse, and how do you see its role evolving within business environments over the next five years?

It’s interesting. We went through a phase of huge excitement around the Metaverse, where everyone wanted to be involved. But now we’ve entered more of a Metaverse winter, or perhaps autumn, as it’s become clear just how difficult it is to create compelling content for these immersive spaces.

We’re seeing strong use cases in industrial applications, but we’re still far from achieving that Ready Player One vision — where we live, shop, buy property, and fully interact in 3D virtual environments. That’s largely because the level of compute power and creative resources needed to build truly immersive experiences is enormous.

In five years’ time, I think we’ll start to see the Metaverse delivering on more of its promises for business. Customers may enjoy exceptional shopping experiences—entering virtual stores rather than simply browsing online, where they can ‘feel’ fabrics virtually and make informed decisions in real time.

We may also see remote working evolve, where employees collaborate inside the Metaverse as if they were in the same room. One study found that younger workers often lack adequate supervision when working remotely. In a Metaverse setting, you could offer genuine, interactive supervision and mentorship. It may also help with fostering colleague relationships that are often missed in remote work settings.

Ultimately, the Metaverse removes physical constraints and offers new ways of working and interacting—but we’ll need balance. Many people may not want to spend all their time in fully immersive environments.

Looking ahead, which emerging technologies and AI-driven trends do you anticipate will have the most profound global impact over the next decade. And how should we be preparing for their implications, both economically and ethically?

That’s a great question. It’s a bit like pulling out a crystal ball. But without doubt, generative AI is one of the most significant shifts we’re seeing today. As the technology becomes more refined, it will increasingly power new AI applications through natural language interactions.

Natural Language Processing (NLP) is the AI term for the machine’s ability to understand and interpret human language. In the near future, only elite developers will need to code manually. The rest of us will interact with machines by typing or speaking requests. These systems will not only provide answers, but also write code on our behalf. It’s incredibly powerful, transformative technology.

But there are downsides. One major concern is that AI sometimes fabricates information. And as generative AI becomes more prolific, it’s generating massive volumes of data 24/7. Over time, machine-generated data may outnumber human data, which could distort the digital landscape. We must ensure the AI doesn’t perpetuate falsehoods it has previously generated.

Looking further ahead, this shift raises deep questions about the future of human work. If AI systems can outperform humans in many tasks without fatigue, what becomes of our role? There may be cost savings, but also the very real risk of widespread unemployment.

AI also powers the Metaverse, so progress there is tied to improvements in AI capabilities. I’m also very excited about synthetic biology, which could see huge advancements driven by AI. There’s also likely to be significant interplay between quantum computing and AI, which could bring both benefits and serious challenges.

We’ll see more Internet of Things (IoT) devices as well—but that introduces new issues around security and data protection.

It’s a time of extraordinary opportunity, but also serious risks. Some worry about artificial general intelligence becoming sentient, but I don’t see that as likely just yet. Current models lack causal reasoning. They’re still predictive tools. We would need to add something fundamentally different to reach human-level intelligence. But make no mistake—we are entering an incredibly exciting era.

Adopting new technologies can be both an opportunity and a risk for businesses. In your view, how can organisations strike the right balance between embracing digital transformation and making strategic, informed decisions about AI adoption?

I think it’s vital to adopt the latest technologies, just as it would have been important for Kodak to see the shift coming in the photography industry. Businesses that fail to even explore digital transformation risk being left behind.

However, a word of caution: it’s easy to jump in too quickly and end up with the wrong AI solution — or the wrong systems entirely — for your business. So, I would advise approaching digital transformation with careful thought. Keep your eyes open, and treat each step as a deliberate, strategic business decision.

When you decide that you’re ready to adopt AI, it’s crucial to hold your suppliers to account. Ask the hard questions. Ask detailed questions. Make sure you have someone in-house, or bring in a consultant, who knows enough to help you interrogate the technology properly.

As we all know, one of the greatest wastes of money in digital transformation happens when the right questions aren’t asked up front. Getting it wrong can be incredibly costly, so take the time to get it right.

Photo by petr sidorov on Unsplash

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

The post Kay Firth-Butterfield, formerly WEF: The future of AI, the metaverse and digital transformation appeared first on AI News.

A key advocate for responsible AI governance and diversity in tech, Wendy has played a crucial role in global discussions on the future of AI.

In our Q&A, we spoke to her about the gender imbalance in the AI industry, the ethical implications of emerging technologies, and how businesses can harness AI while ensuring it remains an asset to humanity.

The AI sector remains heavily male-dominated. Can you share your experience of breaking into the industry and the challenges women face in achieving greater representation in AI and technology?

It’s incredibly frustrating because I wrote my first paper about the lack of women in computing back in 1987, when we were just beginning to teach computer science degree courses at Southampton. That October, we arrived at the university and realised we had no women registered on the course — none at all.

So, those of us working in computing started discussing why that was the case. There were several reasons. One significant factor was the rise of the personal computer, which was marketed as a toy for boys, fundamentally changing the culture. Since then, in the West — though not as much in countries like India or Malaysia — computing has been seen as something nerdy, something that only ‘geeks’ do. Many young girls simply do not want to be associated with that stereotype. By the time they reach their GCSE choices, they often don’t see computing as an option, and that’s where the problem begins.

Despite many efforts, we haven’t managed to change this culture. Nearly 40 years later, the industry is still overwhelmingly male-dominated, even though women make up more than

half of the global population. Women are largely absent from the design and development of computers and software. We apply them, we use them, but we are not part of the fundamental conversations shaping future technologies.

AI is even worse in this regard. If you want to work in machine learning, you need a degree in mathematics or computer science, which means we are funnelling an already male-dominated sector into an even more male-dominated pipeline.

But AI is about more than just machine learning and programming. It’s about application, ethics, values, opportunities, and mitigating potential risks. This requires a broad diversity of voices — not just in terms of gender, but also in age, ethnicity, culture, and accessibility. People with disabilities should be part of these discussions, ensuring technology is developed for everyone.

AI’s development needs input from many disciplines — law, philosophy, psychology, business, and history, to name just a few. We need all these different voices. That’s why I believe we must see AI as a socio-technical system to truly understand its impact. We need diversity in every sense of the word.

As businesses increasingly integrate AI into their operations, what steps should they take to ensure emerging technologies are developed and deployed ethically?

Take, for example, facial recognition. We still haven’t fully established the rules and regulations for when and how this technology should be applied. Did anyone ask you whether you wanted facial recognition on your phone? It was simply offered as a system update, and you could either enable it or not.

We know facial recognition is used extensively for surveillance in China, but it is creeping into use across Europe and the US as well. Security forces are adopting it, which raises concerns about privacy. At the same time, I appreciate the presence of CCTV cameras in car parks at night — they make me feel safer.

This duality applies to all emerging technologies, including AI tools we haven’t even developed yet. Every new technology has a good and a bad side — the yin and the yang, if you will. There are always benefits and risks.

The challenge is learning how to maximise the benefits for humanity, society and business while mitigating the risks. That’s what we must focus on — ensuring AI works in service of people rather than against them.

The rapid advancement of AI is transforming everyday life. How do you envision the future of AI, and what significant changes will it bring to society and the way we work?

I see a future where AI becomes part of the decision-making process, whether in legal cases, medical diagnoses, or education.

AI is already deeply embedded in our daily lives. If you use Google on your phone, you’re using AI. If you unlock your phone with facial recognition, that’s AI. Google Translate? AI. Speech processing, video analysis, image recognition, text generation, and natural language processing — these are all AI-driven technologies.

Right now, the buzz is around generative AI, particularly ChatGPT. It’s like how ‘Hoover’ became synonymous with vacuum cleaners — ChatGPT has become shorthand for AI. In reality, it’s just a clever interface created by OpenAI to allow public access to its generative AI model.

It feels like you’re having a conversation with the system, asking questions and receiving natural language responses. It works with images and videos too, making it seem incredibly advanced. But the truth is, it’s not actually intelligent. It’s not sentient. It’s simply predicting the next word in a sequence based on training data. That’s a crucial distinction.

With generative AI becoming a powerful tool for businesses, what strategies should companies adopt to leverage its capabilities while maintaining human authenticity in their processes and decision-making?

Generative AI is nothing to be afraid of, and I believe we will all start using it more and more. Essentially, it’s software that can assist with writing, summarising, and analysing information.

I compare it to when calculators first appeared. People were outraged: ‘How can we allow calculators in schools? Can we trust the answers they provide?’ But over time, we adapted. The finance industry, for example, is now entirely run by computers, yet it employs more people than ever before. I expect we’ll see something similar with generative AI.

People will be relieved not to have to write endless essays. AI will enhance creativity and efficiency, but it must be viewed as a tool to augment human intelligence, not replace it, because it’s simply not advanced enough to take over.

Look at the legal industry. AI can summarise vast amounts of data, assess the viability of legal cases, and provide predictive analysis. In the medical field, AI could support diagnoses. In education, it could help assess struggling students.

I envision AI being integrated into decision-making teams. We will consult AI, ask it questions, and use its responses as a guide — but it’s crucial to remember that AI is not infallible.

Right now, AI models are trained on biased data. If they rely on information from the internet, much of that data is inaccurate. AI systems also ‘hallucinate’ by generating false information when they don’t have a definitive answer. That’s why we can’t fully trust AI yet.

Instead, we must treat it as a collaborative partner — one that helps us be more productive and creative while ensuring that humans remain in control. Perhaps AI will even pave the way for shorter workweeks, giving us more time for other pursuits.

Photo by Igor Omilaev on Unsplash and AI Speakers Agency.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Dame Wendy Hall, AI Council: Shaping AI with ethics, diversity and innovation appeared first on AI News.

The problem:

In 2023, Neon Internet CEO and co-founder Misch Strotz was struck by a clever idea: give Luxembourg residents the power to easily generate local images using AI. Within a month, Luxembourg-focused LetzAI V1 went live.

Encouraged by strong local demand, Strotz and his team began working on a global version of the platform. The vision? An opt-in AI platform empowering brands, creators, artists, and individuals to unlock endless creative possibilities by adding their own images, art styles, and products. “Other AI platforms scrape the internet, incorporating people and their content without permission. We wanted to put the choice and power in each person’s hands,” Strotz explains.

Before long, the team began working on V2. In addition to generating higher quality and more personalised AI-generated images, V2 would drive consistency across objects, characters, and styles. After uploading their own photos and creating their own models, users can blend them with other models created by the community to create an endless number of unique images.

However, LetzAI faced a significant hurdle in training and launching V2 – a global GPU shortage. With limited resources to train its models, LetzAI needed a reliable partner to help evolve its AI-driven platform and keep it operating smoothly.

The solution:

In the search for a fitting partner, Strotz spoke to major vendors including hyperscalers and various Europe-based providers. Meeting Gcore’s product leadership team made the decision clear. “It was amazing to meet executives who were so knowledgeable about technology and took us seriously,” recalls Strotz.

Gcore’s approach to data security and sovereignty further solidified the decision. “We needed a trusted partner who shared our commitment to European data protection principles, which we incorporated into the development of our platform” he continues.

The result:

LetzAI opted for Gcore’s state-of-the-art NVIDIA H100 GPUs in Luxembourg. “This was the perfect option, allowing us to keep our model training and development local. With Gcore, we can rent GPUs rather than entire servers, making it a far more cost-effective solution by avoiding unnecessary costs like excess storage and idle server capacity,” Strotz explains. This approach provided flexibility, efficiency, and high performance, tailored specifically for AI workloads.

LetzAI was able to adapt its app to run in containers, configure model training tasks to run on GPU Cloud, and use Everywhere Inference for image generation and upscaling. “Everywhere inference reduces the latency of our output and enhances the performance of AI-enabled apps, allowing us to optimise our workflows for more accurate, real-time results,” Strotz says.

In just two months, LetzAI V2 launched to serve users around the world. And Strotz and team were already developing its successor.

Empowering creativity with scalable, high-performance AI infrastructure

With Gcore’s continued support, LetzAI quickly deployed V3. “The Gcore team was incredibly responsive to our needs, guiding us to the best solution for our evolving

requirements. This has given us a powerful and efficient infrastructure that can flex according to demand,” says Strotz.

Running V3 on Gcore means LetzAI users experience fast, reliable performance. Artists, individuals, and brands are already putting V3 to use in interesting ways. For example, in response to what LetzAI calls its ‘AI Challenges’, a Luxembourg restaurant chain prompted residents to create thousands of images using its model of a pizza.

In another example, LetzAI teamed with digital agency LOOP to dress PUMA’s virtual influencer and avatar, Laila, in a Moroccan soccer jersey. According to Strotz, “PUMA had struggled to make clothing look realistic on Laila. When they saw our images, they said the result was 1,000 times better than anything they had tried.”

That wasn’t the only brand intrigued by V3’s possibilities. After LetzAI posted V3-generated images of models wearing Sloggi underwear, Sloggi’s creative agency STAN Studios asked LetzAI to generate more images for market testing.

Always looking for new ways to support creators, LetzAI also launched its Image Upscaler feature, which enhances images and doubles their resolution. “Our creators can now resolve common AI image issues around quality and resolution. Everywhere Inference is pivotal in delivering the power and speed needed for these dynamic image enhancements,” noted Strotz.

Platform evolution and AI innovation without limits

As its models exceed user expectations worldwide, LetzAI can rely on Gcore to handle a high volume of requests. Confident about generating a limitless number of high-quality images on the fly, LetzAI can continue to scale rapidly to become a sustainable, innovation-driven business.

“As we further evolve—such as by adding video features to our platform – our partnership with Gcore will be central to LetzAI’s continued success,” Strotz concluded.

Photo by Tim Arterbury on Unsplash

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

The post How LetzAI empowered creativity with scalable, high-performance AI infrastructure appeared first on AI News.

Why is it important to have neurodiverse input into AI development?

Neurodiverse perspectives are absolutely critical for AI development, and it goes far beyond simply ticking a box for diversity. It’s about building AI that’s truly inclusive and reflects the diverse ways people think, learn, and interact with technology. Neurodiverse individuals bring fresh perspectives to UX and design, ensuring AI interfaces are intuitive and accessible for a wider range of cognitive styles. In my experience, there’s a direct correlation between neurodiversity and the creation of breakthrough solutions. Without those different perspectives, we risk building biased systems that only work for a narrow segment of the population, perpetuating existing inequalities and limiting the potential of AI.

AI models often struggle with biases. How can neurodivergent perspectives help create more inclusive and ethical AI systems?

Neurodivergent individuals often possess unique cognitive strengths, such as a heightened ability to identify patterns and inconsistencies, coupled with meticulous attention to detail and logical thinking. This makes them invaluable for spotting biases in AI algorithms and datasets. Their unique perspectives allow them to see potential pitfalls that others might overlook, leading to fairer, more reliable, and ultimately more ethical AI systems that benefit everyone.

How does Thrive incorporate neurodivergent talent in its AI development processes, and what benefits have you seen from this approach?

We’re passionate about making learning accessible and inclusive for everyone, and that starts with recognising the diverse ways people learn. That’s why incorporating diverse perspectives, including neurodivergent talent, is crucial for identifying and mitigating biases in our AI algorithms.

Our focus on accessibility is inherently linked to incorporating neurodivergent talent. We understand that a diverse workforce learns in diverse ways, and AI allows us to tailor the learning experience to individual needs and preferences. By actively working to incorporate features like people and product bots for automated answers without human interaction, we are creating a more inclusive learning experience for everyone, including those with diverse learning styles.

As a result, we’ve seen significant improvements in the quality and inclusivity of our AI learning platform, leading to more effective learning, a broader reach, and a stronger ethical foundation.

What are some of the biggest barriers preventing neurodivergent individuals from entering the AI and tech industries, and how can businesses address them?

The biggest barriers are often rigid workplace structures designed for neurotypical employees, coupled with a lack of understanding and acceptance of neurodiversity. Businesses need to prioritise flexibility in work arrangements and communication styles, create sensory-friendly spaces with quiet areas and adjustable lighting, and foster a culture where everyone feels safe, valued, and supported. It’s also important to offer alternatives to traditional social events and team-building activities, implement mentorship programmes pairing neurodivergent employees with supportive colleagues, and enable colleagues to choose their work environment to match their strengths and needs. Providing dedicated space for deeper, focused work with fewer distractions is critical for enabling neurodivergent colleagues to thrive.

With AI playing a growing role in workplace automation, how can it be used to support neurodivergent employees rather than exclude them?

AI should empower neurodivergent employees by providing tools and resources that support their individual needs and learning styles, rather than replacing human interaction or creating new barriers. This includes smart reminders and task management systems to help with organisation, AI-powered chat assistants that can provide quick answers, automated meeting summaries to ensure everyone has clear outputs, and tools to reduce distractions like AI-filtered emails. Personalised learning platforms that offer continuous learning and development with tailored recommendations are also essential. The goal is to leverage AI to create a more accessible, inclusive, and supportive work environment where everyone can reach their full potential.

What practical steps should AI companies take to ensure they are fostering a more neurodiverse and inclusive workforce?

AI companies need to move beyond simply raising awareness and take concrete, measurable action to create a truly neurodiverse and inclusive workforce. This includes moving beyond traditional interviews that often prioritise social skills over technical ability and allowing candidates to choose their preferred interview format. It also means creating an inclusive and accessible work environment with neurodivergent-friendly communication and sensory-friendly office spaces. Investing in comprehensive neurodiversity training for all employees is also crucial for better collaboration. Enabling open and honest conversations amongst smaller groups (one to four people) is also critical for creating a safe space for people to articulate themselves and share their perspectives.

Image by alexmogopro from Pixabay

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Frankie Woodhead, Thrive: Why neurodiverse input is crucial for AI development appeared first on AI News.

Breaking Down Barriers with AI

Looking ahead, Jethwa anticipates continued significant advancements in AI and machine learning, particularly with the push towards Gen AI. According to him, the integration of large language models (LLMs) with more sophisticated agents will not only perform complex tasks on behalf of users but also further reduce barriers to interaction. This shift, especially in the geospatial field, means that translating natural language into precise data queries will become more seamless, ultimately making geospatial datasets more accessible, mainstream, and user-friendly.

Training for Complex Tasks

Beyond LLMs, Jethwa is optimistic about progress in the broader category of machine learning, driven by greater access to graphics processing units for training.

He says: “At Ordnance Survey (OS), we’ll leverage this capability to train models for specific, complex tasks such as automatic feature extraction from imagery.

“With an increasing volume of data generated automatically, hopefully next year will also bring innovative tools and techniques to validate data, ensuring it can be confidently utilised for its intended use.”

He underscores the importance of not only pursuing new capabilities but also ensuring that these tools are integrated responsibly into workflows, focusing on quality and risk management.

The Ethical Frontier

The rapid evolution of AI brings with it an urgent need for ethical considerations. 

Jethwa explains: “I would like to see a greater emphasis on ethical AI and responsible technology development,” including creating AI systems that are “transparent, fair, and unbiased” while also considering their environmental and societal impact.

This focus on ethics is encapsulated in OS’s Responsible AI Charter, which guides their approach to integrating new techniques safely.

Moreover, Jethwa highlights the role of workforce development in successful transformations. He believes organisations must commit to “retraining and upskilling employees to prepare them for the impact of AI and digital transformation.” 

This is vital to ensure that in the pursuit of enhanced efficiency, companies do not “lose the personality, creativity, and emotion that we bring as humans into the workplace.” 

Embracing Change While Managing Risks

Despite the promise of technological advancements, obstacles remain in the journey toward digital transformation. Jethwa notes that challenges such as “cultural resistance and rapid successive changes leading to change fatigue will likely persist.”

He advocates for a careful balance between adopting new technologies and addressing the human elements of transformation processes.

As AI continues to influence various aspects of business, from decision-making to risk management, the issue of cybersecurity also looms large. Jethwa points out that “cybersecurity threats being powered by AI are becoming more sophisticated,” urging companies to develop comprehensive strategies that cover everything from data storage to analysis documentation.

The Imperative to Progress

In an evolving landscape, organisations that stagnate risk falling behind their competitors. Jethwa explains: “Companies that fail to keep up open themselves up to risks, such as changing customer expectations as well as attracting and retaining talent.” 

He also emphasises the need for a “clear vision of future goals, effective communication of progress, and celebrating milestones to sustain momentum” in digital transformation initiatives.

As we move into a new year filled with promise, the future of AI and geospatial technology holds transformative power – but it must be used responsibly. The path that lies ahead in 2025 requires vigilance, an unwavering commitment to ethical practices and a human touch in order to drive successful innovation.

(Photos by Annie Spratt and Ordnance Survey)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Ordnance Survey: Navigating the role of AI and ethical considerations in geospatial technology appeared first on AI News.

What have been the latest developments at BMC?

It’s exciting times at BMC and particularly our Control-M product line, as we are continuing to help some of the largest companies around the world in automating and orchestrating business outcomes that are dependent on complex workflows. A big focus of our strategy has been on DataOps specifically on orchestration within the DataOps practice. During the last twelve months we have delivered over seventy integrations to serverless and PaaS offerings across AWS, Azure and GCP enabling our customers to rapidly bring modern cloud services into their Control-M orchestration patterns. Plus, we are prototyping GenAI based use cases to accelerate workflow development and run-time optimisation.

What are the latest trends you’ve noticed developing in DataOps?

What we are seeing in the Data world in general is continued investment in data and analytics software. Analysts estimate that the spend on Data and Analytics software last year was in the $100 billion plus range. If we look at the Machine Learning, Artificial Intelligence & Data Landscape that Matt Turck at Firstmark publishes every year, its more crowded than ever before. It has 2,011 logos and over five hundred were added since 2023. Given this rapid growth of tools and investment, DataOps is now taking center stage as companies are realising that to successfully operationalise data initiatives, they can no longer just add more engineers. DataOps practices are now becoming the blueprint for scaling these initiatives in production. The recent boom of GenAI is going make this operational model even more important.

What should companies be mindful of when trying to create a data strategy?

As I mentioned earlier that the investment in data initiatives from business executives, CEOs, CMOs, CFOs etc. continues to be strong. This investment is not just for creating incremental efficiencies but for game changing, transformational business outcomes as well. This means that three things become very important. First is clear alignment of the data strategy with the business goals, making sure the technology teams are working on what matters the most to the business. Second, is data quality and accessibility, the quality of the data is critical. Poor data quality will lead to inaccurate insights. Equally important is ensuring data accessibility – making the right data available to the right people at the right time. Democratising data access, while maintaining appropriate controls, empowers teams across the organisation to make data-driven decisions. Third is achieving scale in production. The strategy must ensure that Ops readiness is baked into the data engineering practices so its not something that gets considered after piloting only.

How important is data orchestration as part of a company’s overall strategy?

Data Orchestration is arguably the most important pillar of DataOps. Most organisations have data spread across multiple systems – cloud, on-premises, legacy databases, and third-party applications. The ability to integrate and orchestrate these disparate data sources into a unified system is critical. Proper data orchestration ensures seamless data flow between systems, minimising duplication, latency, and bottlenecks, while supporting timely decision-making.

What do your customers tell you are their biggest difficulties when it comes to data orchestration?

Organisations continue to face the challenge of delivering data products fast and then scaling quickly in production. GenAI is a good example of this. CEOs and boards around the world are asking for quick results as they sense that this could majorly disrupt those who cannot harness its power. GenAI is mainstreaming practices such as prompt engineering, prompt chaining etc. The challenge is how do we take LLMs and vector databases, bots etc and fit them into the larger data pipeline which traverses a very hybrid architecture from multiple-clouds to on-prem including mainframes for many. This just reiterates the need for a strategic approach to orchestration which would allow folding new technologies and practices for scalable automation of data pipelines. One customer described Control-M as a power strip of orchestration where they can plug in new technologies and patterns as they emerge without having to rewire every time they swap older technologies for newer ones.

What are your top tips for ensuring optimum data orchestration?

There can be a number of top tips but I will focus on one, interoperability between application and data workflows which I believe is critical for achieving scale and speed in production.  Orchestrating data pipelines is important, but it is vital to keep in mind that these pipelines are part of a larger ecosystem in the enterprise. Let’s consider an ML pipeline is deployed to predict the customers that are likely to switch to a competitor. The data that comes into such a pipeline is a result of workflows that ran in the ERP/CRM and combination of other applications. Successful completion of the application workflows is often a pre-requisite to triggering the data workflows. Once the model identifies customers that are likely to switch, the next step perhaps is to send them a promotional offer which means that  we will need to go back to the application layer in the ERP and CRM. Control-M is uniquely positioned to solve this challenge as our customers use it to orchestrate and manage intricate dependencies between the application and the data layer.

What do you see as being the main opportunities and challenges when deploying AI?

AI and specifically GenAI is rapidly increasing the technologies involved in the data ecosystem. Lots of new models, vector databases and new automation patterns around prompt chaining etc. This challenge is not new to the data world, but the pace of change is picking up. From an orchestration perspective we see tremendous opportunities with our customers because we offer a highly adaptable platform for orchestration where they can fold these tools and patterns into their existing workflows versus going back to drawing board.

Do you have any case studies you could share with us of companies successfully utilising AI?

Domino’s Pizza leverages Control-M for orchestrating its vast and complex data pipelines. With over 20,000 stores globally, Domino’s manages more than 3,000 data pipelines that funnel data from diverse sources such as internal supply chain systems, sales data, and third-party integrations. This data from applications needs to go through complex transformation patterns and models before its available for driving decisions related to food quality, customer satisfaction, and operational efficiency across its franchise network.

Control-M plays a crucial role in orchestrating these data workflows, ensuring seamless integration across a wide range of technologies like MicroStrategy, AMQ, Apache Kafka, Confluent, GreenPlum, Couchbase, Talend, SQL Server, and Power BI, to name a few.

Beyond just connecting complex orchestration patterns together Control-M provides them with end-to-end visibility of pipelines, ensuring that they meet strict service-level agreements (SLAs) while handling increasing data volumes. Control-M is helping them generate critical reports faster, deliver insights to franchisees, and scale the roll out new business services.

What can we expect from BMC in the year ahead?

Our strategy for Control-M at BMC will stay focused on a couple of basic principles:

Continue to allow our customers to use Control-M as a single point of control for orchestration as they onboard modern technologies, particularly on the public cloud. This means we will continue to provide new integrations to all major public cloud providers to ensure they can use Control-M to orchestrate workflows across three major cloud infrastructure models of IaaS, Containers and PaaS (Serverless Cloud Services). We plan to continue our strong focus on serverless, and you will see more out-of-the-box integrations from Control-M to support the PaaS model. 

We recognise that enterprise orchestration is a team sport, which involves coordination across engineering, operations and business users. And, with this in mind, we plan to bring a user experience and interface that is persona based so that collaboration is frictionless. 

Specifically, within DataOps we are looking at the intersection of orchestration and data quality with a specific focus on making data quality a first-class citizen within application and data workflows. Stay tuned for more on this front!

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Basil Faruqui, BMC Software: How to nail your data and AI strategy appeared first on AI News.

Can you tell us a little bit about SS&C Blue Prism and what it does?

SS&C Blue Prism is a specialist in the field of Intelligent Automation, providing products and solutions that change the way in which our customers deliver the work they undertake.

We talk about automation augmenting the workforce, and we can do that by using a digital workforce that brings additional capacity to your human workforce. The rationale being we get a digital worker to do those repetitive, high volume, low value added tasks, and we then allow your employees to focus on the value add that they can bring. 

Intelligent Automation is really looking at the whole cycle of how to deliver the required work through the most efficient channel. That could include orchestration using business process management capabilities. It could also look at process identification through Blue Prism Process Intelligence technologies, where we’re trying to identify those tasks that lend themselves to be automated by technology. 

The dual effect of automation and orchestration of tasks that customers have to do day in, day out is where SS&C Blue Prism brings most value to its customers. A digital workforce could be aimed at improving an HR onboarding process, improving your finance period end close process or  transferring information from an outpatient system to an electronic patient record system and vice versa.The use cases are many and varied but the principle remains the same; use the right channel to deliver the work effort. The beauty of a digital workforce comes in the ability to flex work demands as and when necessary. 

What have been the latest developments at the company?

We’ve been putting a lot of our time, effort and resources into our Next Gen platform. That’s our cloud-native platform that provides access to intelligent automation capabilities, delivered in a way that suits our customers best. It helps customers enjoy the benefits of the cloud while keeping the work where it needs to be. With this hybrid deployment, Next Gen allows customers to take advantage of using the cloud, while having a self-hosted digital workforce that operates behind the customer’s firewall, on their own secure infrastructure – meaning no sensitive data leaves their network.

For many customers that operate in highly regulated industries, that really does drive the opportunity for us to enhance the way we can deliver that through the Next Gen platform. And Next Gen also brings together, in a single repository, all the capabilities that allow us to improve the business processes that we’re undertaking on behalf of our customers. 

Also, I think we’d have been living under a rock if we hadn’t appreciated the fact that Gen AI is really where the market is pivoting. We’re heavily looking into understanding how we can use that technology to really change the way that we work. We’ve introduced capabilities that allow us to integrate with a variety of large language models so our customers can adopt Gen AI. And the way in which we consider that is by using this concept that Gen AI is the capability, which is effectively the brain that allows you to have the emotional, considered response, and the digital workers are the arms and legs that deliver that work. 

So the brain, the Gen AI, does the thinking, and then the digital workforce does the actual doing. When Gen AI is wrapped into Intelligent Automation processes, it means it’s fully auditable and secure. With many customers hesitant to fully dive into using Gen AI due to security concerns, the combination is compelling. That’s something that our customers are really excited about in terms of driving use of Gen AI. And we’re seeing that in a number of places now where we’re looking at Gen AI to manage those customer facing interactions, manage those employee interactions, manage those supplier interactions. They have that ability to respond to any of those queries through a variety of channels, be that telephone,  email or chat capability, then Gen AI can pick up and author the response, executed by the automation platform. 

I speak to a lot of end users and the main thing they say about AI, because it’s so topical right now, is they think they should be utilising it. The problem for many though, is they don’t know how and why. They’re worried that they’re going to be left behind if they don’t get on board with it but maybe it’s not even suitable for them.

I couldn’t agree more. I think for a lot of our customers, and a lot of customer conversations you have, there is this view that we’ve got to do something. We’ve got to have a budget. And invariably there are budgets around for Gen AI. A lot of that is in pilot phase right now. And if you look at some of the evidence in support of it, they haven’t necessarily gone that well.

Part of the problem is that for many they are actually considering Gen AI without thinking of the business problem that they’re trying to solve. We know we’ve got this new shiny bit of kit and that we should be using it. How to use it and what to do with it is almost a secondary consideration. 

The conversation that we really try to move to with the customer is ‘what is the problem that you’re trying to solve? What is the customer issue that you’re trying to solve?’ And we’re certainly seeing that through three main lenses in terms of that use case for Gen AI.

The customer interaction, the employee interaction, or the citizen interaction, if it’s a member of the public. We’re seeing some really interesting things right now about how we are supporting our Gen AI partners, because most of what we are doing is facilitating the use of a third party large language model. We are effectively providing the framework by which our partners can interact with the customer and solve the customer problem.

What kind of trends have you seen developing in Intelligent Automation recently? 

There are a number of things that our customers talk to us about. One of the things we’ve already spoken about, and that is this notion of Gen AI. We’ve got to do it. What are we going to do? How are we going to do it? We need to use Gen AI, and we need to automate it. And there are a number of pilot initiatives that we see because of that. There’s been so much hype around the business value of Gen AI that I think it’s quite scary for some. 

There was a recent industry report by McKinsey that talked about a $4.4 trillion market opportunity with Gen AI. There are some absolutely unbelievable numbers that are thrown out about that. I think the reality of that is slightly more considered. And I think it’s not just about how we can change the way we work. It’s really about how can I get a better outcome for the stakeholder, whomever that may be, by deploying Gen AI with automation? So that’s one of the first trends. 

The second thing that’s really interesting is our customers that have adopted process automation. They’ve used digital workers to either reduce existing costs or improve productivity. So they’ve used it initially as an opportunity for maybe a bit of cost control around improving and automating some processes. But that now is taking them to the next level, which is looking at how to use process intelligence to really identify further process enhancements that they can make. We’re talking about targeting huge organisational objectives through the use of Intelligent Automation, such as growth, customer satisfaction, or employee satisfaction, to name just a few.

I think many companies have taken the low hanging fruit by automation, and now they are investing in those technologies around process identification so they can actually be sure that what they’re automating are the right things and delivering value. But are we? Are we leaving things uncovered by not using the process intelligence in support of the business operation? That is becoming more of a story that our customers are really getting into, and we’ve had a number of deployments where customers have done those initial automation activities, and are now looking to take it to the next level.

The third thing we see more of is this co-existence with Microsoft Power applications. We’re seeing customers adopting those capabilities alongside technologies such as ours, and actually coexisting together in support. We see that more and more, and I think that’s a trend that many customers recognise in terms of the way that they’re working. It’s not just a one size fits all approach. What is the most appropriate technology?

What are your customers biggest challenges? And how can Intelligent Automation help them deal with those? 

The number one challenge is cost control. How do we manage in a market of rising prices? How do we make sure that we’re getting value for money from the automation? We continue to advocate and demonstrate the value that automation is bringing. Be really structured in terms of how you are assessing the benefit that the automation is bringing, because you are accounting for that spend, you’ve got to prove that it’s worthwhile.

For example, what’s the impact on FTE savings? What’s the volume of automations that I’m delivering? What’s the average cost of an employee that’s doing that work? Multiply one by the other and that’s my FTE saving that goes into the business case. So actual cost control, but measured in the term of the business efficiency that I get as a consequence of it. But, where the magic happens is being able to demonstrate what those extra hours have enabled you to do. Have you been able to launch better, quicker products? Have you improved employee satisfaction? Cost factors are always important, but customers must look beyond this to make full use of automation. 

Many, if not most, of our customers have their own centres of excellence that need to be able to demonstrate a value to the business. So that’s the number one conversation we get with our customers. How do we continue to justify the investment in the technology? 

What advice would you give to any companies thinking about implementing Intelligent Automation?

For any customer considering introducing Intelligent Automation, what is the problem that you’re looking to solve? That’s the crux of the matter. And often you find that customers will look to technologies such as ours, where they know they have a challenge with existing technology estate. They’ve got a high degree of technology debt in their IT estate, and one of the ways that they can overcome some of those limitations is by adopting Intelligent Automation. 

So think about the problem that you’re trying to solve, and in order to do that, we need to get a really good understanding of what the actual business processes look like. Or, more importantly, what you think those business processes look like, because often what you think they look like and what they actually look like are very different. That’s where things like process intelligence come in to support that. So what is the problem that you’re looking to solve? 

The next thing that needs to be considered is how do you plan to support that moving forward? Because where our customers have continual investment in the technology and the development of the solution capability, they need to then start being advocates for automation technologies within the business. And once you are doing that, then you are the ones that are effectively going to other parts of the business and trying to identify those automation use cases. 

Our really successful customers are the ones that have got an internal champion who is going out to other parts of the business, because for many areas of the business, this is quite a well kept secret. So helping people understand what this technology can deliver by way of automation and streamlining process, and improvement of process because it’s not that widely understood. We often find that when employees realise what benefits it brings to their team, demand for those internal champions becomes huge. 

For some people, this notion of Intelligent Automation with digital workers has got this sort of Metal Mickey robot-type notion, and we’re not talking about that at all. You’re talking about using computers to emulate human interactions and, using Gen AI, they’re then emulating the human interaction that goes with it. 

So it becomes really quite powerful, but you’ve got to think about how you’re going to sustain that. What does a centre of excellence look like? What have I got by way of developers that can write the automations? What have I then got, by way of business analysts, that can then help us support and find the automations that we need? 

Think about what the initial use cases could look like. A business case on the whole is very easy to write. Where the challenge comes is how do I then sustain and grow the automation footprint? And the customers that are doing it really successfully are either partnering with someone who continues to deliver that function for them, or they’re bringing together their own centre of excellence in house, and they are then tasked with being the champions for further deployment. 

What plans does SS&C Blue Prism have for the year ahead?

It’s something we’ve already touched upon. We are absolutely focused on transitioning our customers to the Next Gen capability, and embracing the technology opportunity that comes with that is something that customers have really input into the the development roadmap for the technology, and how we are moving with that technology. 

Our customers are really looking at when is the optimum opportunity for them to deploy Next Gen. That’s going to be a focus in the short to medium term. And the benefit that offers to our customers is really exciting, particularly when you’re talking about a global customer, where they have operations in a variety of geographies. And actually by having that central automation capability you can deploy the actual workers within each of the regions. That gives you a real step change in terms of the efficiency of automation and the ease by which you monitor and manage those automations as well. 

And then, as others are also encountering, the whole value that Gen AI brings, again, we have got a lot of focus on that. We’ve got a number of customers that are doing some really interesting things. We’ve just been successful with a customer project – a public sector body that is looking at the way they transform the citizen experience – and Gen AI has a huge part to play in that. We see that as something that will continue to improve over time.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Mark Lockett, SS&C Blue Prism: Enhancing human capabilities with digital workforces appeared first on AI News.

The rapid evolution of AI is revolutionising digital marketing, offering unprecedented opportunities for personalisation, efficiency, and customer engagement.

By leveraging advanced algorithms and machine learning techniques, AI is transforming how marketers interact with their audiences, predict customer behaviour, and optimise their strategies for better results. This article delves into the multifaceted impact of AI on digital marketing, highlighting success stories and key strategies that are shaping the future of the industry.

AI’s influence on digital marketing careers and education

AI is reshaping digital marketing careers, requiring new skills and knowledge. As AI continues to integrate into marketing practices, professionals must adapt by acquiring expertise in data analysis, machine learning, and AI tools. Visit DigiPortal to learn about career opportunities and educational resources. Killian Smith, the mind behind DigiPortal, has over a decade of experience in software development and cybersecurity.

Personalisation and customer insights

AI helps in creating highly personalised marketing campaigns by analysing vast amounts of data to derive customer insights. Machine learning algorithms can identify patterns and preferences, allowing marketers to tailor their messages to individual customers. For instance, Netflix and Amazon use AI to recommend products and content based on user behaviour, resulting in higher engagement and satisfaction.

Predictive analytics and decision-making

AI-driven predictive analytics enable marketers to anticipate customer behaviour and make informed decisions. By analysing historical data, AI can forecast future trends, helping businesses to plan their strategies effectively. For example, retailers use predictive analytics to optimise inventory levels and marketing efforts, reducing costs and improving customer satisfaction.

AI-driven content creation and curation

AI tools are revolutionising content creation and curation, allowing marketers to produce high-quality content efficiently.

Tools like GPT-4 are capable of generating high-quality text content, from blog posts to social media updates. These tools can create content that is engaging and relevant, saving time and resources for marketers. For example, The Washington Post uses AI to write news articles, freeing up journalists to focus on in-depth reporting.

Content optimisation and SEO

AI helps optimise content for search engines by analysing keywords, recommending improvements, and tracking performance. AI-driven SEO tools can identify the most effective keywords, suggest content structure, and monitor rankings. A table comparing traditional vs. AI-driven SEO strategies highlights the efficiency and accuracy of AI in optimising content.

AI in customer engagement and support

AI significantly improves customer engagement and support through advanced technologies like chatbots and virtual assistants.

AI-powered chatbots

AI-powered chatbots provide 24/7 customer support, offering personalised responses and handling multiple queries simultaneously. Companies like H&M and Sephora use chatbots to assist customers with product recommendations, order tracking, and more, enhancing the overall customer experience.

Virtual assistants

Virtual assistants streamline customer interactions by providing seamless and personalised services. Technologies like Google Assistant and Amazon Alexa are examples of AI-driven virtual assistants that help businesses engage with customers through voice commands and smart interactions.

AI in advertising and campaign management

AI is transforming advertising by enabling precise targeting, real-time bidding, and campaign optimisation.

Programmatic advertising

Programmatic advertising uses AI to automate the buying and selling of ad space in real time. This method ensures that ads are shown to the right audience at the right time, maximising ROI. Case studies show that businesses using programmatic advertising see significant improvements in ad performance and cost-efficiency.

Audience targeting and segmentation

AI helps in segmenting audiences based on behaviour, demographics, and preferences. AI tools like Google Ads and Facebook Ads Manager allow marketers to target ads more effectively, resulting in higher engagement rates. A list of top AI tools for audience targeting includes platforms like AdRoll, Quantcast, and Smartly.io.

Ethical considerations and challenges in AI marketing

Despite its benefits, AI in marketing also raises ethical concerns and challenges that need to be addressed.

Data privacy concerns

AI’s reliance on data poses significant privacy concerns. Companies must ensure compliance with data protection regulations like GDPR to protect customer information. Best practices for data privacy include data anonymisation, secure data storage, and transparent data usage policies.

Addressing algorithmic bias

Algorithmic bias can lead to unfair and discriminatory outcomes in AI-driven marketing tools. Identifying and mitigating bias is crucial to ensure ethical AI usage. Examples of biased algorithms and corrective steps include regular audits, diverse data sets, and inclusive algorithm design.

Trends and future of AI in digital marketing

The future of AI in digital marketing is promising, with emerging trends set to further revolutionise the industry.

AI and augmented reality (AR)

AI is being integrated with AR to create immersive marketing experiences. Brands like IKEA and L’Oreal use AR to allow customers to visualise products in their own environment, enhancing engagement and purchase decisions.

Voice search and AI

The rise of voice search is changing how content is optimised for voice-based queries. AI tools optimise content for voice search by focusing on natural language processing and conversational keywords. Statistics show that voice search is becoming increasingly popular, with tips for voice search optimisation including the use of long-tail keywords and local SEO.

Conclusion

AI is undeniably transforming digital marketing, offering innovative solutions for personalisation, efficiency, and customer engagement. As AI continues to evolve, staying updated with the latest trends and technologies is essential for businesses to remain competitive. Embrace the power of AI to drive your marketing strategies and achieve unparalleled success in the digital landscape

The post How AI is transforming digital marketing: 2024 trends and insights appeared first on AI News.

At its core, the ChatGPT Prompt Generator is designed to simplify the process of crafting tailored prompts for ChatGPT. By leveraging the tool’s intuitive interface, users can effortlessly create prompts that align with their specific needs, whether they’re seeking assistance with customer support, content creation, or creative writing endeavors.

ChatGPT prompt generator tool features and benefits

The beauty of this tool lies in its user-friendly approach. With just a few clicks, users can select the desired action, such as ‘Create’, ‘Explain’, ‘Analyse’ or ‘Write’, and then specify the focus area. This level of customization ensures that the generated prompts are contextually relevant and tailored to the user’s requirements.

But the true power of the ChatGPT Prompt Generator extends beyond mere convenience. By automating the prompt creation process, the tool saves users valuable time and effort, enabling them to engage with ChatGPT in a more efficient and productive manner. Gone are the days of generic or irrelevant responses – every conversation is now tailored to the user’s specific needs.

One of the standout features of this tool is its ability to understand natural language and adapt to various contexts. Powered by cutting-edge AI technology, the ChatGPT Prompt Generator ensures that the generated prompts are thoughtful, contextually appropriate, and designed to elicit meaningful responses from ChatGPT.

Whether you’re a business professional seeking to streamline customer interactions, a content creator looking to generate engaging material, or a writer exploring new creative avenues, the ChatGPT Prompt Generator is your ultimate companion. By harnessing the power of AI, this tool empowers you to unlock the limitless potential of ChatGPT and elevate your conversations to new heights.

For those seeking to explore the vast realm of AI tools further, the AI Tools Directory at AI Parabellum is a treasure trove of resources. This comprehensive directory curates a wide range of AI-powered tools, spanning various domains and applications, ensuring that users can find the perfect solution for their specific needs.

Final words

In the rapidly evolving world of AI, the WebUtiliy’s ChatGPT Prompt Generator stand as beacon of innovation, empowering users to harness the power of cutting-edge technology and unlock new realms of possibility. Embrace the future of AI-driven conversations.

The post ChatGPT Prompt Generator: Unleashing the power of AI conversations appeared first on AI News.

Can you tell us a little bit about Atera and what it does?

We launched the Atera all-in-one platform for IT management in 2016, so quite a few years ago. And it’s very broad. It’s everything from technical things like patching and security to ongoing support, alerts, automations, ticket management, reports, and analytics, etc. 

Atera is a single platform that manages all your IT in a single pane of glass. The power of it – and we’re the only company that does this – is it’s a single codebase and single database for all of that. The alternative, for many years now, has been to buy four or five different products, and have them all somehow connected, which is usually very difficult. 

Here, the fact is it’s a single codebase and a single database. Everything is connected and streamlined and very intuitive. So, in essence, you sign up or start a trial and within five minutes, you’re already running with it and onboarding. It’s that intuitive.

We have 12,000+ customers in 120 countries around the world. The UK is our second-largest country in terms of business, currently. The US is the first, but the UK is right behind them.

What are the latest trends you’re seeing develop in AI this year?

From the start, we’ve been dedicated to integrating AI into our company’s DNA. Our goal has always been to use data to identify problems and alert humans so they can fix or avoid issues. Initially, we focused on leveraging data to provide solutions.

Over the past nine years, we’ve aimed to let AI handle mundane IT tasks, freeing up professionals for more engaging work. With early access to Chat GPT and Open AI tools a year and a half ago, we’ve been pioneering a new trend we call Action AI.

Unlike generic Generative AI, which creates content like songs or emails, Action AI operates in the real world, interacting with hardware and software to perform tasks autonomously. Our AI can understand IT problems and resolve them on its own, moving beyond mere dialogue to real-world action.

Atera offers Copilot and Autopilot. Could you explain what these are?

Autopilot is autonomous. It understands a problem you might have on your computer. It’s a widget on your computer, and it will communicate with you and fix the problem autonomously. However, it has boundaries on what it’s allowed to fix and what it’s not allowed to fix. And everything it’s allowed to deal with has to be bulletproof. 100% secure or private. No opportunity to do any damage or anything like that. 

So if a ticket is opened up, or a complaint is raised, if it’s outside of these boundaries, it will then activate the Copilot. The Copilot augments the IT professional.

They’re both companions. The Autopilot is a companion that takes away password resets, printer issues, installs software, etc. – mundane and repetitive issues – and the Copilot is a companion that will help the IT professional deal with the issues they deal with on a day-to-day basis. And it has all kinds of different tools. 

The Copilot is very elaborate. If you have a problem, you can ask it and it will not only give you an answer like ChatGPT, but it will research and run all kinds of tests on the network, the computer, and the printer, and it will come to a conclusion, and create the action that is required to solve it. But it won’t solve it. It will still leave that to the IT professional to think about the different information and decide what they want to do. 

Copilot can save IT professionals nearly half of their workday. While it’s been tested in the field for some time, we’re excited to officially launch it now. Meanwhile, Autopilot is still in the beta phase.

What advice would you give to any companies that are thinking about integrating AI technologies into their business operations?

I strongly recommend that companies begin integrating AI technologies immediately, but it is crucial to research and select the right and secure generative AI tools. Incorporating AI offers numerous advantages: it automates routine tasks, enhances efficiency and productivity, improves accuracy by reducing human error, and speeds up problem resolution. That being said, it’s important to pick the right generative AI tool to help you reap the benefits without compromising on security. For example, with our collaboration with Microsoft, our customers’ data is secure—it stays within the system, and the AI doesn’t use it for training or expanding its database. This ensures safety while delivering substantial benefits.

Our incorporation of AI into our product focuses on two key aspects. First, your IT team no longer has to deal with mundane, frustrating tasks. Second, for end users, issues like non-working printers, forgotten passwords, or slow internet are resolved in seconds or minutes instead of hours. This provides a measurable and significant improvement in efficiency.

There are all kinds of AIs out there. Some of them are more beneficial, some are less. Some are just Chat GPT in disguise, and it’s a very thin layer. What we do literally changes the whole interaction with IT. And we know, when IT has a problem things stop working, and you stop working. Our solution ensures everything keeps running smoothly.

What can we expect from AI over the next few years?

AI is set to become significantly more intelligent and aware. One remarkable development is its growing ability to reason, predict, and understand data. This capability enables AI to foresee issues and autonomously resolve them, showcasing an astonishing level of reasoning.

We anticipate a dual advancement: a rapid acceleration in AI’s intelligence and a substantial enhancement in its empathetic interactions, as demonstrated in the latest OpenAI release. This evolution will transform how humans engage with AI.

Our work exemplifies this shift. When non-technical users interact with our software to solve problems, AI responds with a highly empathetic, human-like approach. Users feel as though they are speaking to a real IT professional, ensuring a seamless and comforting experience.

As AI continues to evolve, it will become increasingly powerful and capable. Recent breakthroughs in understanding AI’s mechanisms will not only enhance its functionality but also ensure its security and ethical use, reinforcing its role as a force for good.

What plans does Atera have for the next year?

We are excited to announce the upcoming launch of Autopilot, scheduled for release in a few months. While Copilot, our comprehensive suite of advanced tools designed specifically for IT professionals, has already been instrumental in enhancing efficiency and effectiveness, Autopilot represents the next significant advancement.

Currently in beta so whoever wants to try it already can, Autopilot directly interacts with end users, automating and resolving common IT issues that typically burden IT staff, such as password resets and printer malfunctions. By addressing these routine tasks, Autopilot allows IT professionals to focus on more strategic and rewarding activities, ultimately improving overall productivity and job satisfaction.

For more information, visit atera.com

Atera is a sponsor of TechEx North America 2024 on June 5-6 in Santa Clara, US. Visit the Atera team at booth 237 for a personalised demo, or to test your IT skills with the company’s first-of-kind AIT game, APOLLO IT, for a chance to win a prize.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Gil Pekelman, Atera: How businesses can harness the power of AI appeared first on AI News.