The summit was hosted by UAE-based Polynome Group under the patronage of H.H. Sheikh Hamdan bin Mohammed bin Rashid Al Maktoum. Strategic backers included Digital Dubai, Dubai Police, Emirates, Amazon Web Services, NVIDIA, IBM, SAP, MBZUAI among others.

“In just three years, MCS has evolved from a specialist meet‑up into a true crossroads for the world’s top minds in science, business and public policy. The week proved that when researchers, entrepreneurs and governments share one stage, we move a step closer to transparent, human‑centred AI that delivers real value for society,” said Alexander Khanin, founder & CEO of Polynome Group

Landmark agreements announced live on stage

During the two‑day programme, several high‑profile agreements were signed at the summit, including:

• A trilateral Memorandum of Understanding between Astana Hub (Kazakhstan), IT‑Park Uzbekistan and Al‑Farabi Innovation Hub (UAE), creating a Central‑Asia‑to‑MENA soft‑landing platform for high‑growth start‑ups.

• A Google Cloud initiative offering no‑cost “Gen‑AI Leader” learning paths and discounted certification vouchers to accelerate responsible AI adoption across the region.

Polynome Group officially launched AI Academy, an educational initiative developed in collaboration with the Abu Dhabi School of Management and supported by NVIDIA’s Deep Learning Institute. The Academy will offer short executive seminars and a specialised four‑month Mini‑MBA in AI, aimed at equipping leaders and innovators with practical AI knowledge to bridge the gap between technology research and commercial application.

Policy & talent

Day one opened with a ministerial round‑table – “Wanted: AI to Retain and Attract Talent to the Country.” Ministers Omar Sultan Al Olama (UAE), Amr Talaat (Egypt), Gobind Singh Deo (Malaysia), Zhaslan Madiyev (Kazakhstan) and Meutya Hafid (Indonesia) detailed visa‑fast‑track programmes, national GPU clouds and cross‑border sandboxes designed to reverse brain‑drain and accelerate R&D.

Breakthrough research

• Prof. Michael Bronstein (University of Oxford/Google DeepMind) demonstrated Geometric Deep Learning applications that shorten drug‑discovery timelines and model subatomic physics.

• Marco Tempest (NASA JPL/MagicLab.nyc) blended GPT‑4o dialogue with mixed‑reality holograms, turning the stage into an interactive mind‑map.

• Prof. Michal Irani (Weizmann Institute) showed perception‑to‑cognition systems capable of reconstructing scenes from a single gaze sequence.

• Andrea Vedaldi (Oxford) premiered a 3‑D generative‑AI pipeline for instant city‑scale digital twins, while Marc Pollefeys (ETH Zurich/Microsoft) demonstrated real‑time spatial mapping at sub‑10 ms latency.

Industry workshops & panels

AWS ran a hands‑on clinic – “Building Enterprise Gen‑AI Applications” – covering RAG, agentic orchestration and secure deployment. NVIDIA’s workshop unveiled its platform approach to production generative‑AI on Hopper‑class GPUs, complementing its newly announced Service Delivery Partnership with Polynome Group’s legal entity, Intelligent Machines Consultancies. Dubai Police hosted a closed‑door DFA session on predictive policing, while X and AI workshops explored social‑data pipelines on GPU clusters.

The parallel Machines Can Create forum examined AI’s role in luxury, digital art and media, with speakers from HEC Paris, The Sandbox, IBM Research and BBC, culminating in the panel “Pixels and Palettes: The Canvas of Tomorrow.”

Prof. Marc Pollefeys, Director of the Mixed Reality and AI Lab at ETH Zurich and Microsoft, highlighted the role of cutting-edge technology in daily life: “We are at a turning point where technologies like spatial AI and real-time 3D mapping are moving from laboratories into everyday life, transforming cities, workplaces, and how we interact with the digital world. The Machines Can See Summit underscores how collaboration between researchers, industry, and policymakers accelerates this transition, bringing innovative solutions closer to everyone,” he said.

Ethical & security focus

Panels “Good AI: Between Hype and Mediocrity” and “Defending Intelligence: Navigating Adversarial Machine Learning” stressed the need for continuous audits, red‑teaming and transparent supply chains. Dubai Police, TII UAE and IBM urged adoption of ISO‑aligned governance tool‑kits to safeguard public‑sector deployments.

High‑profile awards

On Day Two, H.H. Sheikh Hamdan bin Mohammed bin Rashid Al Maktoum presented trophies for the Global Prompt Engineering Championship, for breakthroughs in multilingual, safety-aligned LLM prompting.

Key takeaways

The summit underscored three strategic imperatives for the decade ahead. Talent aviation – backed by unified tech visas, national GPU clouds and government‑funded sandbox clusters – is emerging as the most effective antidote to AI brain‑drain. Spatial computing is moving from laboratory to street level as sub‑10‑millisecond mapping unlocks safe humanoid robotics and city‑scale augmented‑reality services. Finally, secure generative AI must couple adversarial robustness with transparent, explainable pipelines before the technology can achieve mass‑market adoption in regulated industries.

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Solana’s technical architecture can handle high-speed, low-cost transactions, thus making it an appealing foundation for AI developers who build real-time, decentralised applications. The convergence of blockchain and AI is influencing the network’s utility and market valuation, creating new narratives around the future of scalable, intelligent systems.

Why Solana appeals to the AI industry

One appeal of Solana is its extremely agile performance. The network can theoretically support over 65,000 transactions per second (TPS), with real-world numbers averaging 3,000 to 4,500 TPS. This is possible because of the unique proof-of-history (PoH) mechanism, which timestamps transactions to enhance the validation process.

Considering the consistently low transaction costs – an average of $0.036 per transaction – Solana offers an ecosystem for computation-dominated AI operations. Blockchain technology, at this level, allows large-scale interactions without latency or high costs.

Solana pricing momentum mirrors AI integration

While the price of Solana generally mirrors the prevailing mood of the market, analysts have noted correlation between price movements and AI developments on the network. For example, the launch of AI-focused projects and integrations has caused price increases.

Distributing AI models for Solana

Solana is emerging as a go-to hosting platform for AI-powered decentralised applications. Some of the more prominent projects using the network for AI include:

• Nosana (NOS) – A decentralised GPU marketplace where users can distribute AI model training.

• io.net – an AI-centric cost-effective cloud computing service.

• Grass – Project building an open, incentivised system where an AI agents get paid to write software for large-scale web crawling.

These projects rely on the throughput of Solana to maintain real-time inference, moving large data streams, and executing microtransactions. Unlike many chains, Solana’s architecture accommodates AI applications that need to access the blockchain directly and quickly – without losing on cost.

Economic feasibility and AI-powered microtransactions

Most required micropayments in Solana for data, model updates, or compute payments, need to be executed frequently, via decentralisation. Through its fee structure, where the cost per interaction (transaction) is roughly $0.036, Solana guarantees low interaction costs.

This capability fosters concepts like token-incentivised federated learning, autonomous model marketplace architectures, and on-the-go autonomous services – which each depend on micro-interactions unfeasible on slower, more-pricey blockchains.

AI-related activity on the blockchain verifies its growth

Blockchain analytics show a surge in transaction activity in Solana associated with AI tools and services implementations. The network is capable of thousands of transactions per second; an increasing proportion of those include AI-related functions.

The number of active daily addresses on Solana has increased in parallel, due to growing activity from developers working with AI, machine learning infrastructure, predictive analytics and real-time automation systems.

The numbers show the demand for blockchain-associated workloads and development related to artificial intelligence is rising, which may help bolster Solana’s longer-term prospects and shape market sentiment – as evidenced by fluctuations in the price of Solana.

Solana uses AI for network efficiency

Solana’s contributions to artificial intelligence do not stop at decentralised apps. The network also uses AI for its internal processes, with the Solana Foundation developing ML models for validator clustering and network optimisation. Using traffic patterns and predicting possible blockages, algorithms help maintain the lower latency Solana is known for, even at busy times. This increases the network’s resilience for applications like live dashboards powered by AI or data processing systems on the blockchain.

Ecosystem investment AI momentum

Throughout last year, there was a great deal of venture capital investment in Solana-based projects that used AI add-ons. Important, funded projects include:

• STARDEER formed the “STARDUST Fund” with $10 million earmarked for Solana ecosystem projects that focus on building intelligent backbone solutions.

• Seek Protocol announced the development of a Solana-based AR + AI platform, reportedly valued at $8.89 million.

• Pioneer AI Foundry: Began executing a disbursement strategy for investing in Solana-based AI-dedicated, decentralised educational tools.

The funding helps build infrastructure for functions that drive on-chain activity – like AI model training, decentralised inference, data lineage and provenance, and more.

Closing thoughts

Transitions in Solana’s infrastructural, AI-transformable blockchain capabilities are changing the ecosystem’s scope. The architecture provides for services that demand speed, scalability and cost-effectiveness. Its features will help create next-generation, AI-dedicated, decentralised systems; effectively becoming serverless AI.

With increasing adoption of AI models with blockchain implementation, Solana is set to become a foundation where information, logic, and algorithms co-exist. The ongoing development of advanced intelligent infrastructure on the Solana network provides an opportunity to redefine perceptions of changes to Solana’s price.

(Image source: Unsplash)

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The world’s third largest economy and host nation for GITEX EUROPE x Ai Everything, Germany’s role as the European economic and technology leader is confirmed as its ICT sector is projected to reach €232.8bn in 2025 (Statista).

GITEX EUROPE x Ai Everything is Europe’s largest tech, startup and digital investment event, and is organised by KAOUN International. It’s hosted in partnership with the Berlin Senate Department for Economics, Energy and Public Enterprises, Germany’s Federal Ministry for Economic Affairs and Climate Action, Berlin Partner for Business and Technology, and the European Innovation Council (EIC).

Global tech engages for cross-border and industry partnerships

The first GITEX EUROPE brings together over 1,400 tech enterprises, startups and SMEs, and platinum sponsors AWS and IBM. Also in sponsorship roles are Cisco, Cloudflare, Dell, Fortinet, Lenovo, NTT, Nutanix, Nvidia, Opswat, and SAP.

GITEX EUROPE x Ai Everything will comprise of tech companies from over 100 countries and 34 European states, including tech pavilions from India, Italy, Morocco, Netherlands, Poland, Serbia, South Korea, UK, and the UAE.

Trixie LohMirmand, CEO of KAOUN International, organiser of GITEX worldwide, said: “There is a sense of urgency and unity in Europe to assert its digital sovereignty and leadership as a global innovation force. The region is paving its way as a centre-stage where AI, quantum and deep tech will be debated, developed, and scaled.”

Global leaders address EU’s tech crossroads

Organisers state there will be over 500 speakers, debating a range of issues including AI and quantum, cloud, and data sovereignty.

Already confirmed are Geoffrey Hinton, Physics Nobel Laureate (2024); Kai Wegner, Mayor of Berlin; H.E. Jelena Begović, Serbian Minister of Science, Technological Development and Innovation; António Henriques, CEO, Bison Bank; Jager McConnell, CEO, Crunchbase; Mark Surman, President, Mozilla; and Sandro Gianella, Head of Europe & Middle East Policy & Partnerships, OpenAI.

Europe’s moves in AI, deep tech & quantum

Europe is focusing on cross-sector AI uses, new investments and international partnerships. Ai Everything Europe, the event’s AI showcase and conference, brings together AI architects, startups and investors to explore AI ecosystems.

Topics presented on stage range from EuroStack ambitions to implications of agentic AI, with speakers including Martin Kon, President and COO, Cohere; Daniel Verten, Strategy Partner, Synthesia; and Professor Dr. Antonio Krueger, CEO of German Research Centre for Artificial Intelligence.

On the show-floor, attendees will be able to experience Brazil’s Ubivis’s smart factory technology, powered by IoT and digital twins, and Hexis’s AI-driven nutrition plans that are trusted by 500+ Olympic and elite athletes.

With nearly €7 billion in quantum investment, Europe is pushing for quantum leadership by 2030. GITEX Quantum Expo (GQX) (in partnership with IBM and QuIC) covers quantum research and cross-industry impact with showcases and conferences.

Speakers include Mira Wolf-Bauwens, Responsible Quantum Computing Lead, IBM Research, Switzerland; Joachim Mnich, Director of Research & Computing, CERN, Switzerland; Neil Abroug, Head of the French National Quantum Strategy, INRIA; and Jan Goetz, CEO & Co-Founder, IQM Quantum Computers, Finland.

Cyber Valley: Building a resilient cyber frontline

With cloud breaches doubling in number and AI-driven attacks, threat response and cyber resilience are core focuses at the event. Fortinet, CrowdStrike, Kaspersky, Knowbe4, and Proofpoint will join other cybersecurity companies exhibiting at GITEX Cyber Valley.

They’ll be alongside law enforcement leaders, global CISOs, and policymakers on stage, including Brig. Gen. Dr. Volker Pötzsch, Chief of Division Cyber/IT & AI, Federal Ministry of Defence, Germany; H.E. Dr. Mohamed Al-Kuwaiti, Head of Cybersecurity, UAE Government; Miguel De Bruycker, Managing Director General, Centre for Cybersecurity Belgium; and Ugo Vignolo Lutati, Group CISO, Prada Group.

GITEX Green Impact: For a sustainable future

GITEX Green Impact connects innovators and investors with over 100 startups and investors exploring how green hydrogen, bio-energy, and next-gen energy storage are moving from R&D to deployment.

Key speakers so far confirmed are Gavin Towler, Chief Scientist for Sustainability Technologies & CTO, Honeywell; Julie Kitcher, Chief Sustainability Officer, Airbus; Lisa Reehten, Managing Director, Bosch Climate Solutions; Massimo Falcioni, Chief Competitiveness Officer, Abu Dhabi Investment Office; and Mounir Benaija, CTO – EV & Charging Infrastructure, TotalEnergies.

Convening the largest startup ecosystem among 60+ nations

GITEX EUROPE x Ai Everything hosts North Star Europe, the local version of the world’s largest startup event, Expand North Star.

North Star Europe gathers over 750 startups and 20 global unicorns, among them reMarkable, TransferMate, Solarisbank AG, Bolt, Flix, and Glovo.

The event features a curated collection of earlys and growth-stage startups from Belgium, France, Hungary, Italy, Morocco, Portugal, Netherlands, Switzerland, Serbia, UK, and UAE.

Among the startups, Neurocast.ai (Netherlands) is advancing AI-powered neurotech for Alzheimer’s research; CloudBees (Switzerland) is the delivery unicorn backed by Goldman Sachs, HSBC, and Lightspeed; and Semiqon (Finland), the world’s first CMOS transistor with the ability to perform in cryogenic conditions.

More than 600 investors with $1tn assets under management will be scouting for new opportunities, including Germany’s Earlybird VC, Austria’s SpeedInvest, Switzerland’s B2Venture, Estonia’s Startup Wise Guys, and the US’s SOSV.

GITEX ScaleX launches as a first-of-its-kind growth platform for scale-ups and late-stage companies, in partnership with AWS.

With SMEs making up 99% of European businesses, GITEX SMEDEX connects SMEs with international trade networks and investors, for funding, legal advice, and market access to scale globally.

Backed by EISMEA and ICC Digital Standards Initiative, the event features SME ecosystem leaders advising from the stage, including Milena Stoycheva, Chairperson of Board of Innovation, Ministry of Innovation and Growth, Bulgaria; and Oliver Grün, President, European Digital SME Alliance and BITMi.

GITEX EUROPE is part of the GITEX global network tech and startup events, taking place in Germany, Morocco, Nigeria, Singapore, Thailand, and the UAE.

For more information, please visit: www.gitex-europe.com.

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Machines Can See is staged by the Polynome Group, a machine vision, AI, robotic, and industrial design company based in the city.

This is the third year of the event, and will bring investors, business leaders, and policymakers together to explore AI-centric expansion opportunities. Machines Can See, as the name suggests, will have a particular focus on computer vision.

Each discussion and keynote is designed to be firmly rooted in practical applications of AI technology, but organisers hope that the show will be permeated with a sense of discovery and that attendees will be able to explore the possibilities of the tech on show. “We are not just shaping the future of AI, we are defining how AI shapes the world,” said Alexander Khanin, head of the Polynome Group.

UAE Government officials attending the event include H.E. Omar Sultan Al Olama, UAE Minister of State for Artificial Intelligence, Digital Economy, and Remote Work Applications, and H.E. Hamad Obaid Al Mansoori, the Director General of Digital Dubai.

Polynome Group has said that X will be the official streaming partner for Machines Can See 2025, and the US company will host workshops titled “X and AI” to show solutions that merge AI and streaming technologies, with GRok X central to those sessions. Via interactive demos, attendees will gain firsthand experience of GRok’s potential in AI delivery, analysis and optimisation.

Investment and business opportunities

UAE’s AI market is projected to grow by $8.4 billion in the next two years, and the summit is designed to serve as a venue for investors to engage with AI startups, existing enterprises, and government decision-makers. Attendees at Machines Can See will get to meet with investors and venture capital firms, be given the opportunity to meet executives from AI companies (including IBM and Amazon), and connect with startups seeking investment.

The summit is supported by Amazon Prime Video & Studios, Amazon Web Services, Dubai Police, MBZUAI, IBM, SAP, Adia Lab, QuantumBlack and Yango. The involvement of many organisations and large-scale enterprises should provide many opportunities for funding and collaborations that extend the commercial use of AI.

Local and international investors include Eddy Farhat, Executive Director at e& capital, Faris Al Mazrui, Head of Growth Investments at Mubadala, Major General Khalid Nasser Alrazooqi General Director of Artificial Intelligence, Dubai Police UEA, and Dr. Najwa Aaraj, the CEO of TII.

Speakers and insights

The summit will feature several US-based AI professionals, including Namik Hrle, IBM Fellow and Vice President of Development at the IBM Software Group, Michael Bronstein, DeepMind Professor of AI at Oxford University, Marc Pollefeys, Professor of Computer Science at ETH Zurich, Gerard Medioni, VP and Distinguished Scientist at Amazon Prime Video & Studio, and Deva Ramanan, Professor at the Robotics Institute of Carnegie Mellon University.

The event will feature a ministerial session composed of international government representatives to discuss the role of national IT development.

Among speakers already confirmed for the event are Gobind Singh Deo, Malaysia’s Minister of Digital, H.E. Zhaslan Madiyev, Minister of Digital Development, Innovation, and Aerospace Industry of Kazakhstan, and H.E. Omar Sultan Al Olama, UAE Minister of State for Artificial Intelligence, Digital Economy, and Remote Work Applications.

Event organisers expect to announce more representatives from overseas in the coming days. Read more here.

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What are digital twins?

Digital twins, originally developed to aid in the design of complex machinery have evolved significantly over the last two decades. They track and analyse live systems in real-time by processing device telemetry, detecting shifting conditions, and enhancing situational awareness for operational managers. Powered by in-memory computing, they enable fast, actionable alerts. Beyond real-time monitoring, digital twins also can simulate intricate systems like those for use in airlines and logistics, supporting strategic planning and operational decisions through predictive analytics.

Integrating digital twins with generative AI creates new opportunities for both technologies: The synergy can boost the prediction accuracy of generative AI, and can enhance the value of digital twins for system monitoring and development.

Proactively identifying anomalies with AI-powered digital twins

Continuous, real-time monitoring is a strategic necessity for organisations that manage complex live systems, like transportation networks, cybersecurity systems, and smart cities. Emerging problems must never be overlooked because delayed responses can cause small problems to become large ones.

Enhancing digital twins with generative AI reshapes how real-time monitoring interprets massive volumes of live data, enabling the reliable and immediate detection of anomalies that impact operations. Generative AI can continuously examine analytics results produced by digital twins to uncover emerging trends and mitigate disruptions before they escalate. While AI enhances situational awareness for managers, it can also pinpoint new opportunities for optimising operations and boosting efficiency.

At the same time, real-time data supplied by digital twins constrains the output of generative AI to avoid erratic results, like hallucinations. In a process called retrieval augmented generation, AI always uses the most up-to-date information about a live system to analyse behaviour and create recommendations.

Transforming data interaction with AI-driven visualisations

Unlocking insights from digital twin analytics should be intuitive, not technical. Generative AI is redefining how teams interact with massive datasets by enabling natural language-driven queries and visualisations. Instead of manually constructing intricate queries, users can simply describe their needs, and generative AI immediately visualises relevant charts and query results that provide new insights. This capability simplifies interactions and gives decision-makers the data they need. As organisations handle increasingly complex live systems, AI-powered intelligence allows them to efficiently sift through vast data pools, extract meaningful trends, and optimise operations with greater precision. It eliminates technical barriers, enabling faster, data-driven decisions that have a strategic impact.

Incorporating machine learning with automatic retraining

Digital twins can track numerous individual data streams and look for issues with the corresponding physical data sources. Working together, thousands or even millions of digital twins can monitor very large, complex systems. As messages flow in, each digital twin combines them with known information about a particular data source and analyses the data in a few milliseconds. It can incorporate a machine learning algorithm to assist in the analysis and find subtle issues that would be difficult to describe in hand-coded algorithms. After training with data from live operations, ML algorithms can identify anomalies and generate alerts for operational managers immediately.

Once deployed to analyse live telemetry, an ML algorithm will likely encounter new situations not covered by its initial training set. It may either fail to detect anomalies or generate false positives. Automatic retraining lets the algorithm learn as it gains experience so it can improve its performance and adapt to changing conditions. Digital twins can work together to detect invalid ML responses and build new training sets that feed automatic retraining. By incorporating automatic retraining, businesses gain a competitive edge with real-time monitoring that reliably delivers actionable insights as it learns over time.

Looking forward

Integrating digital twin technology with generative AI and ML can transform how industries monitor complex, live systems by empowering better real-time insights and enabling managers to make faster, more informed decisions. ScaleOut Software’s newly-released Digital Twins Version 4 adds generative AI using OpenAI’s large language model and automatic ML retraining to move real-time monitoring towards the goal of fully-autonomous operations. 

(Image source: Unsplash)

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While a lot of emerging technologies are playing a role in the evolution of the finance industry, the AI revolution is one of the most prominent. With that in mind, let us look at the ways AI is transforming financial platforms, starting with a brief overview of the role AI plays in financial services.

Understanding AI in financial services

AI is changing the landscape of the financial services sector, as in other industries. The integration of AI in the financial services industry extends to changes in how companies operate, customer interactions, agentic AI, and risk management.

The three core AI-related technologies that play an important role in the finance sector, are:

• Natural language processing (NLP): The NLP aspect of AI helps companies understand and interpret human language, and is used for sentiment analysis or customer service automation through chatbots.

• Machine learning (ML): AI can let financial systems learn from past data and improve performance with minimal human intervention. ML algorithms can analyse large data volumes and make important predictions about investment opportunities and market trends.

• Predictive analytics: Businesses can use machine learning techniques and AI algorithms to identify the likelihood of certain outcomes based on historical data. Companies can use predictive analytics for better accuracy in fraud detection or risk assessment.

It also helps that AI has already been adopted to a certain extent in the financial sector. Around 70% of financial institutions and companies currently invest in AI technologies, according to a 2024 report by Gartner. Moreover, around 58% of finance functions use AI in some capacity.

AI-integrated strategies in finance

For AI integration in the finance sector to be truly successful and unlock the untapped potential in a company, strategies using the technology must be well-defined. With robust strategies, finance companies, and service providers can ensure AI prepares them for a more profitable future.

Among other areas, three important areas of or strategies for financial services that currently use AI at a much bigger scale, are:

Risk management

While risk management is an essential business function in many companies and industries, it is especially important for financial institutions. With the help of advanced algorithms and data analytics, financial organisations can take a proactive approach to identifying, assessing, and mitigating risks. As a result, you can avoid issues like leakage of revenue or loss of important data.

AI models can help with credit risk assessment of businesses and individuals by analysing large datasets. Financial companies can also use AI-based systems to monitor transactions in real-time and identify unusual patterns pointing to fraudulent activity. Additionally, financial analysts use AI to conduct market risk analysis and predict market volatility by processing extensive market data.

Compliance and regulatory monitoring

As the financial industry faces increasing regulatory scrutiny, organisations have to invest and implement robust strategies for compliance management. AI systems can help organisations automate the checking of transactions for compliance with anti-money laundering laws, and flag down suspicious activity.

Many financial service providers are developing AI-driven risk assessment frameworks that help them identify and prevent compliance risks. Plus, they also use AI to streamline reporting processes to ensure timely submission of regulatory documents and the generation of compliance reports. Lastly, processes must align with the necessary AI regulations.

Personalisation of communication and products/services

AI can also help financial organisations provide highly-personalised services to customers by analysing their preferences and requirements. By using data analytics, banks and financial organisations can provide tailored financial products that meet their specific needs. AI-powered chatbots and virtual assistants help customers get instant support and answers to queries in real-time.

Financial companies should conduct continuous and consistent analysis of transactions and customer interactions to identify robust trends and deliver targeted and highly relevant marketing and promotional messages to customers.

AI-powered tools on financial platforms

The aforementioned strategies help financial companies provide unique and high-quality services to customers. Most financial platforms offer different kinds of AI-powered tools that add several value-adding features and abilities.

Here are some of the AI-powered financial tools to know about:

AI chatbots and virtual assistants

The quality of customer service is important to the success of any financial institution or organisation. Most financial companies use AI-powered chatbots and virtual assistants to provide excellent service to customers. Chatbots can ensure timely communication, helping companies humanise AI responses, and resolve queries for customers.

Enterprise AI agents

For larger financial organisations that offer multiple services, products or operate in many locations, an enterprise management strategy is a must. A lot of companies implement enterprise AI agent platforms that help automate repetitive actions and tasks when an event or feature is triggered.

Fraud detection system

Most financial platforms use a fraud detection system to monitor transactions in real-time and flag any suspicious instances to combat fraud. The systems also help companies monitor market conditions and user behaviour to detect any unusual patterns immediately.

Data mining tools

Most financial platforms handle large volumes of financial data that can be analysed and monitored to generate valuable insights. Data mining tools can help navigate this situation by extracting insights from large data volumes with the help of machine learning algorithms. It is possible to identify patterns and trends to inform strategic and financial decisions.

Automated trading systems

AI-powered automated trading systems help companies execute trades based on predetermined criteria. Automated trading systems aid financial organisations enhance efficiency in trades and react to market changes faster than humans.

The future of AI in financial systems and services

As the financial services industry evolves, so do the role and applications of AI in the industry. Companies should keep track of emerging trends to steer the success of financial service provision.

When integrating AI technologies into financial processes, it is important for companies to choose the right platforms to ensure smooth and efficient implementation. This brings us to a comparison of Sitecore vs. WordPress – two web platforms popular in the financial services space.

While Sitecore offers a highly personalised experience for customers, making it ideal for large financial institutions with complex needs, WordPress provides an affordable and scalable solution for smaller institutions or those just beginning their AI integration journey. Understanding the strengths and limitations of each platform can help financial organisations choose the best way to adopt AI solutions.

Some industry solutions include personalised financial services tailored to the preferences and risk appetite of customers, and decentralised finance solutions that could automate lending, borrowing and trading decisions effectively.

Many financial companies are looking to implement advanced risk management tools that use AI to assess risks and predict market disruptions proactively.

The integration of AI in financial processes may be slow but it is inexorable, making it important for companies to consider implementing the technology sooner rather than later. With effective AI integration, financial companies can enjoy better operational efficiency and enhanced customer experience in the long-term.

Conclusion

The role of AI in the financial industry has been discussed and debated for some time. While most financial applications and platforms use AI to strengthen or automate certain processes, others use it to add new functions and features to the existing platform.

(Image source: Unsplash)

The post How AI transforms financial platforms: Tools and strategies appeared first on AI News.

The built-in AI engine analyses emails based on factors like recency, most-clicked emails, and frequent contacts, to display conversations users are likely to be looking for. This isn’t just a convenience update but an improvement that professionals, including influencer marketers, who manage high volumes of correspondence, will appreciate. A fast-growing influencer marketing agency based in Europe, AWISEE.com, has taken a closer look at how the new Gmail update could help enhance influencer marketing.

How Gmail’s AI search update enhances influencer outreach

Source: Google blog

Gmail’s AI-powered update helps ensure effective communication and strengthens relationships for brands and agencies using influencer marketing.

Prioritising important responses

Influencer marketing relies heavily on engagement, and prompt responses are important to create and maintain partnerships. Gmail’s AI-driven search ensures that emails from influencers and other collaborators you’ve interacted with are displayed first.

Andrea Noureddine, AWISEE’s Influencer Marketing Coordinator, said, “New relationships are also given a priority as the AI can analyse content in emails and understand its relevance in future communications. If you are in a critical stage like negotiation with an influencer, you’ll see the communication at the top of the results.”

This makes it easier to find important emails and reduces the risk of delays in communication.

Streamlining follow-ups

Maintaining partnerships and ensuring that a brand’s marketing goals are met needs timely follow-ups. Before Google released Gmail’s latest update, marketers had to sift through pages of emails to find the latest correspondence with a specific influencer. Now, the email interface brings up the most relevant conversations.

Andrea said, “If a marketer needs to reach out to an influencer to enquire about various deliverables, they’ll have an easier time as Gmail will give priority to conversations that need a follow-up.”

Enhanced organisation for large-scale outreach

Part of influencer marketing is reaching out to many brands, agencies, and dozens – if not hundreds – of influencers. This can easily become challenging when an organisation isn’t efficient, and Gmail’s traditional chronological search order certainly didn’t help. An important conversation could be buried under tens of others that aren’t relevant.

Now that message sorting is based on AI, marketers have an easier time focusing on priority interactions. “What this means is that outreach emails that received a response, ongoing collaborations, and messages from the influencers you often work with are easier to locate,” Andrea said.

Using AI for data-driven influencer strategies

According to AWISEE, marketing relies on data, which makes AI an integral part of all strategies. Data focus goes beyond email management and requires that marketing agencies adopt advanced AI tools for analysing influencer profiles, assessing engagement authenticity, and refining campaign targeting.

Gmail’s AI search integration aligns perfectly with this data-driven approach to ensure a more streamlined and efficient workflow.

Andrea expanded how AWISEE.com is taking advantage of the update, and the AI tools that seem to come out every other day:

“At AWISEE.com, we are committed to enhancing our influencer outreach by integrating Google’s recent AI enhancements to Gmail’s search functionality. The technology allows us to prioritise emails based on relevance, considering factors like recency and user interaction frequency, thereby facilitating more efficient and effective collaborations.

“On top of that, we use advanced AI tools to improve our influencer outreach. By analysing influencer profiles and assessing engagement authenticity, we ensure our communications resonate with each influencer’s unique style. The approach strengthens our partnerships and aligns our strategies with the dynamic nature of digital marketing, delivering exceptional value to our clients.”

The future of influencer marketing in the age of AI

Gmail’s latest search update is just one example of the increasingly important role that AI plays in influencer marketing. As the technology evolves, it will become increasingly more influential in how brands and agencies identify, engage, and collaborate with influencers.

Hyper-personalised influencer outreach

AI can analyse huge amounts of data about a brand, influencer, and customers, so we can expect outreach strategies to become more tailored. Instead of sending generic pitch emails, brands and agencies can use AI to create personalised messages based on an influencer’s past collaboration, content style, demographics, and engagement trends.

Predictive analytics for campaign performance

Beyond improving outreach, AI plays an important role in marketing decision-making. It can analyse historical campaign data to help predict which influencers can drive the highest engagement and conversions for a particular brand. Agencies and brands can use this information to create more impactful campaigns by reducing guesswork.

Smarter campaign optimisation

AI can track the performance of different influencer campaigns in real-time, offering actionable insights into what’s working and what’s not. This gives brands and agencies metrics like engagement rates, audience sentiment, and conversation rates, which can be used to know whether a campaign needs tweaking.

Gmail’s recent update aligns with this goal, as all parties involved can look up past correspondence easily, quickly identifying strategies that aren’t working.

AWISEE.com‘s Andrea summarises:

“At AWISEE, we see AI as a game-changer in influencer marketing and a tool that we can take advantage of to maximise the chances of meeting our clients’ campaign goals. Gmail’s AI-driven search will go a long way in ensuring we prioritise conversations that matter and act on various insights in real time. And when you combine this with the advanced AI analytics we already have access to, we’ll be able to create data-driven influencer strategies that work well in today’s dynamic digital landscape.”

(Image source: Unsplash)

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GITEX ASIA 2025 will bring together 700+ tech companies, featuring 400+ startups and digital promotion agencies, and 250+ global investors & VCs from 60+ countries.

The event will serve as a bridge between the Eastern and Western technology ecosystems and feature 180+ hours of expert insights from 220 global thought leaders.

GITEX ASIA 2025 is set to foster cross-border collaboration, investment, and innovation, connecting global tech enterprises, unicorn founders, policymakers, SMEs, and academia to shape the future of digital transformation in Asia.

GITEX ASIA 2025 will comprise of five co-located events:

• AI EVERTYTHING SINGAPORE – the AI showcase.
• NORTHSTAR ASIA – for startups and investors
• GITEX CYBER VALLEY ASIA – helping create a defence ecosystem for governments and businesses
• GITEX QUANTUM QUANTUM EXPO ASIA – Asia’s quantum frontier
• GITEX DIGI HEALTH & BIOTECH SINGAPORE – the healthcare revolution

GITEX ASIA 2025 will host a lineup of conferences and summits, exploring a range of transformative trends in technology and investment. Key themes will include AI, cloud & connectivity, cybersecurity, quantum, health tech & biotech, green tech & smart cities, startups & investors, and SMEs.

Sessions will include Asia Digital AI Economy, AI Everything: AI Adoption & Commercialisation, Cybersecurity: AI-Enabled Cybersecurity & Critical Infrastructure, Digital Health, and the Supernova Pitch Competition.

The event will bring together leading voices and ideas from different industries, including public services, retail, finance, education, health, and manufacturing.

Be part of the action at GITEX ASIA 2025 and witness the future of technology unfold in Singapore. For more information and updates on GITEX ASIA, visit www.gitexasia.com

Social media links: LinkedIn | X | Facebook | Instagram | YouTube

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The event presents an opportunity for manufacturers to find industry partners and collaboration opportunities, and secure domestic and international orders.

The Greater Bay Area has a reputation as a place where industries can transform and grow. Its vibrant large economy, global outreach, and important manufacturing capabilities make it the natural centre of innovation and economic growth.

As a breeding ground for scientific and technological progress, it’s the place chosen to bring innovators, manufacturers, and heads of industry together under one roof.

Now in its sixth year, WAIE 2025 will focus on “Key Technologies for Intelligent Industry,” and be a showcase for a range of products and services that can be demonstrated in real-world, practical scenarios. 

The Digital Economy: Empowering Intelligent Industry Development

WAIE 2025 will showcase a range of solutions including sensor instruments and advanced lasers, industrial optoelectronics, robotics and intelligent factories, industrial internet, software & cloud, and photovoltaic energy storage. The aim is to connect core technologies and new products with industry and supply chains.

The Five Exhibition Areas

Industrial Chip and Sensor Instrument Expo

• Intelligent industrial sensors, MEMS sensors, 3D/machine vision, laser radar, sensing elements, light sources, lenses, visual sensing, millimetre wave radar, and instrumentation & measurement.
• Integrated circuit design: Wafer manufacturing and advanced packaging technology, power device/MEMS sealing and testing, silicon wafer and IC packaging
• Semiconductors: Materials, electronic core components and parts, associated equipment.
• Electronic terminal applications: including 5G, human-computer interaction, AIOT, and other related products.

Advanced Laser and Industrial Optoelectronics Expo

• Laser accessories, modules and components, fiber lasers, solid-state lasers, semiconductor lasers, new laser technologies, sheet metal cutting equipment, laser welding equipment, laser cleaning equipment, and material processing systems.
• Optics: Optical materials, components and elements, optical lenses, precision optical testing and measurement instruments, and optical processing equipment.

Robot and Intelligent Factory Expo

• Industrial Robots: Industrial robot systems, collaborative robots, mobile robots, humanoid robots, robot system integration, machine vision, manipulators, reducers, related machinery devices & components, and auxiliary equipment and tools.
• Intelligent Factory Production Line: Industrial automation equipment, intelligent factory total solutions, SMT, non-standard automation production lines, dispensers, automated production lines, inspection/instrumentation/testing and measurement technology, intelligent assembly and transfer equipment, reducers, motors, human-machine interface (HMI), motion servos, enclosures and cabinets, embedded systems, industrial power supplies, connectors, electrical equipment, process and energy automation systems, and intelligent factory management systems.

Industrial Internet, Software and Cloud Expo

• Industrial internet platforms including Cloud computing and big data, data centre infrastructure, data analysis and mining.
• Industrial Internet Network Interconnectivity including communication network services, IDC, CPS, IOT, AI, and Edge computing.
• Industrial internet security for network and data security
• Industrial Internet identification and data collection.
• Industrial software and integrated solutions, including industrial control software, MRO supply chain management, and embedded software.
• The digital factory, comprising of R&D and product development (CAX/MES/PLM), enterprise resource planning (ERP), mechanical automation, supply chain management, and intelligent factory management systems.

Photovoltaic Energy Storage Industrial Application Expo

• Solar photovoltaic power generation, including PV production equipment, batteries, modules, raw materials, photovoltaic engineering and systems, and photovoltaic application products.
• Energy storage power generation, including storage batteries, energy storage technology and materials, storage systems and EPC projects, energy storage equipment and components, and storage application solutions.
• Lithium battery related products and equipment, technical solutions and applications, and energy management.

Over 20 forum events

WAIE 2025 will host more than 20 forums and summits on the applications of intelligent industrial digitalisation. There will also be award ceremonies, project matchmaking, roadshow presentations, and product launches.

The event will feature more than 100 speakers and play host to over 100 experts, scholars, academicians, and entrepreneurs from diverse fields.

The event aims to cover all elements of the industry supply chain, promote the development of new technologies and applications, and inject new energy and innovation into the industry.

Highlight Focus

Summit + Exhibition, to boost brand exposure and customer acquisition.

Click to register for WAIE 2025.

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That’s where AI prompt generators come in, and AI Parabellum’s AI Prompt Generator is helping people get the results they want.

The challenge of effective prompting

Creating the perfect prompt is an art and a science. Too vague, and you get generic results, while too specific in the wrong ways, and the AI might misunderstand your intention.

Many of us waste time rewriting prompts several times before getting usable output. That’s why prompt generators have become important tools for anyone working with AI.

Introducing AI Parabellum’s AI Prompt Generator

AI Parabellum’s AI Prompt Generator is genuinely impressive. Unlike other generators that produce basic prompts, it creates structured, professional-grade prompts that get consistent results across different AI platforms.

What makes it unique is its approach to prompt architecture. The generator writes prompts with clear separation between system instructions and user requirements. Each prompt includes a <system></system> section that tells the AI how to behave, and a <requirement></requirement> section that specifies what you actually want. This structured approach can dramatically improve AI responses.

Versatile content creation support

AI Parabellum doesn’t just handle text prompts, but supports multiple content types too:

• Text generation
• Image generation
• Video generation

Its versatility means you can use one tool regardless of whether you’re writing an article, creating marketing visuals, or producing video content.

User-friendly features that make a difference

AI Parabellum has broken down the prompt creation process into intuitive components. When generating a text prompt, you can specify:

• Topic or subject – what your prompt is about
• Purpose – selected from common use cases
• Additional details – any specific requirements or constraints
• Tone – from formal to casual and everything between
• Output format – paragraphs, lists, essays, etc.
• Length – brief, medium, or detailed output

The interface also includes toggles for including examples, citations, and explanations in your generated prompts. These additions can make the difference between adequate and excellent AI output.

Why better prompts matter

Better prompts save time and money. When you’re paying per token or have limited credits on AI platforms, getting the right response the first time is valuable. AI Parabellum’s structured prompt format reduces the back-and-forth typically needed with AI tools.

The system/requirement separation also helps maintain consistency. By clearly defining how the AI should approach your request separately from what you’re requesting, you get more predictable results across different sessions and different AI models.

Getting started

Using AI Parabellum is straightforward. Visit the website, select your content type, fill in the relevant fields, and click “Generate Prompt.” In seconds, you’ll have a crafted prompt to copy and paste into your favorite AI tool.

The generated prompts work well with ChatGPT, Claude, and other AI platforms, making this a universal solution regardless of which tools you prefer.

Final thoughts

If you’re serious about getting better results from AI tools, investing time in better prompts pays dividends. AI Parabellum’s AI Prompt Generator removes the guesswork and flattens the learning curve, allowing anyone to create expert-level prompts that deliver consistent, high-quality outputs.

Check out the best AI prompt generator to see how much better your AI interactions can be with properly-structured prompts. Whether you’re a casual user or an AI power user, having this tool in your arsenal will dramatically improve your results.

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Scheduled for 5 – 6 May 2025 at the JW Marriott Hotel in Riyadh, this event will bring together 300+ data and AI professionals, including CDOs, CIOs, data scientists, AI directors, C-suite executives and many others, to explore the latest advances, tackle challenges, and unlock opportunities in data and artificial intelligence.

With the Kingdom’s data analytics market projected to reach $8.8 billion by 2030, the summit comes at an important time, offering a platform for public and private sector leaders to collaborate, innovate, and approach the nation’s Vision 2030 goals.

A platform for innovation and collaboration

Building on the success of its debut last year, which was inaugurated by a leading official from the Saudi Data & AI Authority (SDAIA), the 2025 edition promises to be bigger and more impactful.

The summit will feature:

• 25+ cutting-edge solution providers showcasing the latest technologies in data and AI.

• 50+ industry experts sharing insights on emerging trends, challenges, and opportunities.

• 300+ attendees, including data engineers, architects, AI pioneers, and decision-makers from Saudi Arabia’s largest organisations.

• 1:1 meetings to foster collaboration and evaluate tailored solutions.

• CPD-accredited sessions to help professionals enhance their skills and advance their careers.

Unveiling the future of data and AI

The summit’s agenda will look at important topics shaping the future of data and AI, including:

• Navigating open data in Saudi Arabia

• AI fusion and machine learning innovations

• Data virtualisation and the power of data mesh

• Ethical data governance and cybersecurity analytics

• Unified data cloud architectures

Discussions will be led by thought leaders from the Kingdom’s top organisations, including Ministry of Hajj & Umrah, Insurance Authority, Council of Health Insurance, NEOM, AlNASSR Club Company | PIF, and Abdul Latif Jameel United Finance.

DAMA Saudi Arabia joins as supporting partner

The Data Management Association (DAMA Saudi Arabia), the Kingdom’s largest data management community, has joined the summit as a supporting partner. The partnership underscores DAMA’s commitment to fostering a robust data management ecosystem and aligns with the summit’s mission to elevate Saudi Arabia’s position as a global leader in data and AI.

Abdulaziz Almanea, Founder & Chairman of the Board, DAMA Saudi, spoke of the importance of the summit: “Artificial intelligence is only as good as the data behind it. Quality, governance, and ethics must come first to ensure trust, accuracy, and impact. As Saudi Arabia accelerates its data-driven transformation, industry events like the Smart Data & AI Summit serve as vital platforms for bringing experts together to shape the future of AI with responsible and innovative data practices.”

A legacy of excellence

The inaugural edition of the summit set a high benchmark, with attendees praising the quality of speakers, depth of discussions, and opportunities for networking and collaboration. Nayef Al-Otaibi, VP & Chief Digital Officer at Saudi Aramco, said, “The event was well-managed, the coordination was excellent, and the quality of the speakers was above expectations. It was a beautiful experience connecting with industry experts during the panel discussions and sharing our experiences. This could basically help us establish the platform and collaborate and work together in future.”

Driving Vision 2030 forward

The Smart Data & AI Summit is a strategic initiative to support Saudi Arabia’s Vision 2030 goals. By bringing together global expertise, cutting-edge technologies, and local insights, the summit aims to:

• Accelerate the Kingdom’s digital transformation.

• Foster innovation and collaboration across industries.

• Address regulatory challenges and ethical considerations in data and AI.

• Unlock new opportunities for investment and growth in the Kingdom’s data and AI sectors.

Sudhir Ranjan Jena, CEO & Co-founder of Tradepass, the organising body, spoke of the summit’s mission: “The data & AI sector is entering a transformative chapter, fuelled by technology disruptions, heightened expectations, and the unprecedented expansion of digital tools and platforms. In the upcoming edition, we will delve into Vision 2030 goals, unlock limitless opportunities, and explore emerging trends and solutions that will play an integral role in shaping the Kingdom’s post-oil economy.”

A high-impact speaker lineup

The summit will feature an impressive roster of speakers, including:

• Dr Ahmed Alzahrani – Director of Business Intelligence and Data Analytics Centre, Ministry of Hajj & Umrah

• Hajar Alolah – Data Governance and Management Office Director, Saudi Development Bank

• Abdullah AlBar – Chief Data Officer, Abdul Latif Jameel United Finance

• Usamah Algemili – Chief Data Executive, Insurance Authority

• Jawad Saleemi – Director – AI & Cloud, Telenor

• Abbasi Poonawala – Executive Director – Enterprise Architecture, Alinma Bank

• Nawaf Alghamdi – Director – Data Analytics & AI, Council of Health Insurance

These experts will share their insights on the latest trends, challenges, and opportunities in data and AI, offering attendees strategies to drive innovation and growth in their organisations.

For more information, visit: https://saudi.smartdataseries.com/

Media contact:

Shrinkhal Sharad
PR & Communication Lead
Tradepass
Email: shrinkhals@tradepassglobal.com
Phone: + (91) 80 6166 4401

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Regulatory challenges and the new AI standard ISO 42001

Tony Porter, former Surveillance Camera Commissioner for the UK Home Office, provided insights into regulatory challenges surrounding AI transparency. He highlighted the significance of ISO 42001, the international standard for AI management systems which offers a framework for responsible AI governance. “Regulations are evolving rapidly, but standards like ISO 42001 provide organisations with a structured approach to balancing innovation with accountability,” Porter said. The panel dissociation led by Prof. Yaniski Ravid featured representatives from leading AI companies, who shared how their organisations implement transparency in AI systems, particularly in retail and legal applications.

Chamelio: Transforming legal decision-making with explainable AI

Alex Zilberman from Chamelio, a legal intelligence platform exclusively built for in-house legal teams, addressed the role of AI in corporate legal operations. Chamelio changes how in-house legal teams operate through an AI agent that learns and uses the legal knowledge stored in its repository of contracts, policies, compliance documents, corporate records, regulatory filings, and other business-important legal documents.

Chamelio’s AI agent performs core legal tasks like extracting important obligations, streamlines contract reviews, monitors compliance, and delivers actionable insights that would otherwise remain buried in thousands of pages of documents. The platform integrates with existing tools and adapts to a team’s legal knowledge.

“Trust is the number one requirement to build a system that professionals can use,” Zilberman said. “This trust is achieved by providing as much transparency as possible. Our solution allows users to understand where each recommendation comes from, ensuring they can confirm and verify every insight.”

Chamelio avoids the ‘black box’ model by letting legal professionals trace the reasoning behind AI-generated recommendations. For example, when the system encounters areas of a contract that it doesn’t recognise, instead of guessing, it flags the uncertainty and requests human input. This approach helps legal professionals control important decisions, particularly in unprecedented scenarios like clauses with no precedent or conflicting legal terms.

Buffers.ai: Changing inventory optimisation

Pini Usha from Buffers.ai shared insights on AI-driven inventory optimisation, an important application in retail. Buffers.ai serves medium to large retail and manufacturing brands, including H&M, P&G, and Toshiba, helping retailers – particularly in the fashion industry – tackle inventory optimisation challenges like forecasting, replenishment, and assortment planning. The company helps ensure the right product quantities are delivered to the correct locations, reducing instances of stockouts and excess inventory.

Buffers.ai offers a full-SaaS ERP plugin that integrates with systems like SAP and Priority, providing ROI in months. “Transparency is key. If businesses cannot understand how AI predicts demand fluctuations or supply chain risks, they will be hesitant to rely on it,” Usha said.

Buffers.ai integrates explainability tools that allow clients to visualise and adjust AI-driven forecasts, helping ensure alignment with real-time business operations and market trends. For example, when placing a new product with no historical data, the system analyses similar product trends, store characteristics, and local demand signals. If a branch has historically shown strong demand for comparable items, the system might recommend a higher quantity without any existing data for the new product. Similarly, when allocating inventory between branches and online stores, the system details factors like regional sales performance, customer traffic patterns, and online conversion rates to explain its recommendations.

Corsight AI: Facial recognition in retail and law enforcement

Matan Noga from Corsight AI discussed the role of explainability in facial recognition technology, which is used increasingly for security and customer experience enhancement in retail. Corsight AI specialises in real-world facial recognition, and provides its solutions to law enforcement, airports, malls, and retailers.

The company’s technology is used for applications like watchlist alerting, locating missing persons, and forensic investigations. Corsight AI differentiates itself by focusing on high-speed, and real-time recognition in ways compliant with evolving privacy laws and ethical AI guidelines. The company works with government and its commercial clients to promote responsible AI adoption, emphasising the importance of explainability in building trust and ensuring ethical use.

ImiSight: AI-powered image intelligence

Daphne Tapia from ImiSight highlighted the importance of explainability in AI-powered image intelligence, particularly in high-stakes applications like border security and environmental monitoring. ImiSight specialises in multi-sensor integration and analysis, utilising AI/ML algorithms to detect changes, anomalies, and objects in sectors like land encroachment, environmental monitoring, and infrastructure maintenance. “AI explainability means understanding why a specific object or change was detected. We prioritise traceability and transparency to ensure users can trust our system’s outputs,” Tapia said. ImiSight continuously refines its models based on real-world data and user feedback. The company collaborates with regulatory agencies to ensure its AI meets international compliance standards.

The panel underscored the important role of AI explainability in fostering trust, accountability, and ethical use of AI technologies, particularly in retail and other high-stakes industries. By prioritising transparency and human oversight, organisations can ensure AI systems are both effective and trustworthy, aligning with evolving regulatory standards and public expectations.

Watch the full session here

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