Despite huge and ongoing advancements in generative AI, the massive wave it was supposed to create in the world of work looks more like a ripple so far.

Researchers Anders Humlum (University of Chicago) and Emilie Vestergaard (University of Copenhagen) didn’t just rely on anecdotes. They dug deep, connecting responses from two big surveys (late 2023 and 2024) with official, detailed records about jobs and pay in Denmark.

The pair zoomed in on around 25,000 people working in 7,000 different places, covering 11 jobs thought to be right in the path of AI disruption.   

Everyone’s using AI chatbots for work, but where are the benefits?

What they found confirms what many of us see: AI chatbots are everywhere in Danish workplaces now. Most bosses are actually encouraging staff to use them, a real turnaround from the early days when companies were understandably nervous about things like data privacy.

Almost four out of ten employers have even rolled out their own in-house chatbots, and nearly a third of employees have had some formal training on these tools.   

When bosses gave the nod, the number of staff using chatbots practically doubled, jumping from 47% to 83%. It also helped level the playing field a bit. That gap between men and women using chatbots? It shrank noticeably when companies actively encouraged their use, especially when they threw in some training.

So, the tools are popular, companies are investing, people are getting trained… but the big economic shift? It seems to be missing in action.

Using statistical methods to compare people who used AI chatbots for work with those who didn’t, both before and after ChatGPT burst onto the scene, the researchers found… well, basically nothing.

“Precise zeros,” the researchers call their findings. No significant bump in pay, no change in recorded work hours, across all 11 job types they looked at. And they’re pretty confident about this – the numbers rule out any average effect bigger than just 1%.

This wasn’t just a blip, either. The lack of impact held true even for the keen beans who jumped on board early, those using chatbots daily, or folks working where the boss was actively pushing the tech.

Looking at whole workplaces didn’t change the story; places with lots of chatbot users didn’t see different trends in hiring, overall wages, or keeping staff compared to places using them less.

Productivity gains: More of a gentle nudge than a shove

Why the big disconnect? Why all the hype and investment if it’s not showing up in paychecks or job stats? The study flags two main culprits: the productivity boosts aren’t as huge as hoped in the real world, and what little gains there are aren’t really making their way into wages.

Sure, people using AI chatbots for work felt they were helpful. They mentioned better work quality and feeling more creative. But the number one benefit? Saving time.

However, when the researchers crunched the numbers, the average time saved was only about 2.8% of a user’s total work hours. That’s miles away from the huge 15%, 30%, even 50% productivity jumps seen in controlled lab-style experiments (RCTs) involving similar jobs.

Why the difference? A few things seem to be going on. Those experiments often focus on jobs or specific tasks where chatbots really shine (like coding help or basic customer service responses). This study looked at a wider range, including jobs like teaching where the benefits might be smaller.

The researchers stress the importance of what they call “complementary investments”. People whose companies encouraged chatbot use and provided training actually did report bigger benefits – saving more time, improving quality, and feeling more creative. This suggests that just having the tool isn’t enough; you need the right support and company environment to really unlock its potential.

And even those modest time savings weren’t padding wallets. The study reckons only a tiny fraction – maybe 3% to 7% – of the time saved actually showed up as higher earnings. It might be down to standard workplace inertia, or maybe it’s just harder to ask for a raise based on using a tool your boss hasn’t officially blessed, especially when many people started using them off their own bat.

Making new work, not less work

One fascinating twist is that AI chatbots aren’t just about doing old work tasks faster. They seem to be creating new tasks too. Around 17% of people using them said they had new workloads, mostly brand new types of tasks.

This phenomenon happened more often in workplaces that encouraged chatbot use. It even spilled over to people not using the tools – about 5% of non-users reported new tasks popping up because of AI, especially teachers having to adapt assignments or spot AI-written homework.   

What kind of new tasks? Things like figuring out how to weave AI into daily workflows, drafting content with AI help, and importantly, dealing with the ethical side and making sure everything’s above board. It hints that companies are still very much in the ‘figuring it out’ phase, spending time and effort adapting rather than just reaping instant rewards.

What’s the verdict on the work impact of AI chatbots?

The researchers are careful not to write off generative AI completely. They see pathways for it to become more influential over time, especially as companies get better at integrating it and maybe as those “new tasks” evolve.

But for now, their message is clear: the current reality doesn’t match the hype about a massive, immediate job market overhaul.

“Despite rapid adoption and substantial investments… our key finding is that AI chatbots have had minimal impact on productivity and labor market outcomes to date,” the researchers conclude.   

It brings to mind that old quote about the early computer age: seen everywhere, except in the productivity stats. Two years on from ChatGPT’s launch kicking off the fastest tech adoption we’ve ever seen, its actual mark on jobs and pay looks surprisingly light.

The revolution might still be coming, but it seems to be taking its time.   

See also: Claude Integrations: Anthropic adds AI to your favourite work tools

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As vaccines continue to roll out, a hybrid work model has emerged, with staff now alternating and ‘taking turns’ being back in the office. In the US, research done by SHRM.org highlights that 55% of the workforce favours a hybrid workforce post-pandemic. 

In the UK, a survey by PWC found 77% of UK employees want a mix of face-to-face and remote working. As a result, 77% of UK organisations plan to reconfigure their existing office space and 50% think they will reduce the size of their office portfolio. 

However, there is one key concern from companies in the face of all this change; How does one maintain security in a hybrid workforce?

The answer involves putting the focus on maintaining company culture through education and communication, infusing data analytics to understand human error and how to mitigate it, and engaging in security planning and testing. 

The importance of educating staff

The emergency conditions that necessitated a widespread move to working from home in 2020 were far from typical. Many workers had trouble acclimating, stress levels were high, and distractions were plentiful.

Due to these obstacles, 55% of IT professionals said reducing human error and training employees on how to properly operate security systems from home was their biggest challenge in 2020. Educating employees on the importance of cybersecurity and giving them open access to continued training needs to start early.

For example, developing an internal trust centre for all things security gives employees a central location to find answers and resources easily. It also provides direct links to the company’s documentation on security protocols, settings, systems, and operations.

One organisation helping to scale education through data-driven insights in the workforce amidst the pandemic is Learning Pool, which has embedded Sisense BI tools to combine the power of its leading AI-driven analytics cloud platform with the world’s most-widely installed Learning Record Store (LRS), Learning Locker. 

With more than a billion data points under management, Learning Pool customers use Learning Locker to help manage their learning records.

Learning Pool is getting ready to launch a new addition to the Learning Pool suite, aptly named “Insights”. This new addition will incorporate Sisense’s AI capabilities for personalisation and automatic intelligence, helping transform data into real insights.

Insights will create expertly designed dashboards powered by AI, built specifically for learning data analysis. 

By presenting accessible, adaptable and actionable visualisations that are grouped together as meaningful dashboards, Insights provides Learning Pool clients with actionable insights about the past, present and potential future performance of their learning ecosystem and their users.

Communication in a hybrid environment

One downside to hybrid or remote environments is the lack of in-person interactions. Having to connect virtually may not come close to real-life engagements. However, considering many people prefer working remotely (65%, according to a PWC survey) and others are open to hybrid models (55%, according to Flexjobs.com), connecting virtually is key for maintaining company communication and fostering culture. 

As an example, when COVID caused Sisense to become a full-fledged work-from-home entity, setting up communication tools like Slack; creating virtual events, gatherings,  town hall meetings, and subscribing to video conferencing tools like Zoom, created simple pathways for teams and leadership to stay connected. Contrary to many business leaders’ concern, virtual communications will impact company culture but in many ways, the change improved culture. 

This connection and increased communication boosted the culture of Sisense, and that directly impacted security. People feel connected to the company, and as a result, they have something they care about protecting.

During COVID, one initiative Sisense had to maintain as part of their work culture was to offer employees self care days. 

“This is a day off each month dedicated for employees to take time to themselves, recharge, be with their families or sleep in– whatever they needed for that day was up to them,” Amir Orad, CEO at Sisense said.

“The key was (and still is) that the self care day is mandatory, we insist everyone take the day off together and make it legitimate to be away from zoom and email. The feedback we received from employees was that they felt supported and seen during a difficult time.”

Making workplace safety a priority with AI

When the pandemic hit and the world was forced to retreat into seclusion, some companies were more prepared to pivot effectively than others. Those who put safety and security by leveraging data and insights to do so, set themselves up to pull through stronger than ever before.

As an example, Air Canada used the Sisense Fusion Platform, was able to build powerful proofs of concept to improve safety across the airlines.

Air Canada was able to go ‘beyond the dashboard’ with new innovations to deliver insights to its frontline workers with the use of the Sisense Fusion Platform and pushing actionable data to their stakeholders (frontline employees and executives). In this way, Air Canada enabled these stakeholders to focus and immediately act upon important insights about their day-to-day activities, especially activities relating to safety. This helped add insights about safety across the organisation and improve safety measures for the end-user. 

The Canadian airline developed these innovative improvements as a result of their ability to deliver crucial and personalised data to their employees and frontline workers. 

Testing led to innovations in internal communications for Air Canada. The airline started sending real-time notifications to employees’ smartwatches and using the Amazon Echo speakers as a communication tool for staff to ask questions immediately in their own words. Additionally, Air Canada was able to transform traditional dashboards into immersive 3D environments which used mixed reality to display data in different ways. 

Results proved that there was not a one-size-fits-all approach in sharing data and insights with employees. It was clear that not all employees digested data the same way. However, as a result of the innovations, staff will now receive the same data differently to personalise what each employee wants and needs from the data. 

Future-proof your workforce with AI-infused analytics

As COVID rampaged, claiming lives, flipping the global economy and uprooting the habits of millions; Ty Sbano, Sisense Chief Security Officer’s team implemented their pandemic plan quickly, they learned as they went, and worked out kinks as they arose. 

“We adjusted our plan to fit exactly what was happening,” he said. “Having a contingency plan on paper for if and when an event hits puts our team ahead of the curve.” 

The planning phase for the security team included defining critical business workflows, creating a secure system for employees to use, and strengthening security protocols (like Zscaler) to enable the entire global company to continue working without interruption. The security and IT teams at Sisense worked diligently to test plans before they’re executed, uncover any gaps, software issues, or better routes for security success. 

While error will never be completely eradicated, it can be managed with the right AI-infused data-driven and innovative measures. Your data will be protected, your teams will be connected, your workforce feel more safe, and your business culture will have the opportunity to grow in a new, and potentially stronger, direction.

Editor’s note: This article is in association with Sisense.

(Photo by Marten Bjork on Unsplash)

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A report, commissioned by the TUC and carried out by leading employment rights lawyers Robin Allen QC and Dee Masters from the AI Law Consultancy, claims there are “huge gaps” in British law.

“The TUC is right to call for urgent legislative changes to ensure that workers and companies can both enjoy the benefits of AI,” the lawyers say. “[Employment law gaps] must be plugged quickly to stop workers from being discriminated against and mistreated.”

The report warns that employment law is failing to keep pace with the rapid adoption of AI in the workplace and workers will become powerless to challenge “inhuman” forms of AI performance management.

“Already important decisions are being made by machines,” the lawyers explain. “Accountability, transparency and accuracy need to be guaranteed by the legal system through the carefully crafted legal reforms we propose.”

Four legal reforms are proposed by the TUC:

• A legal duty on employers to consult trade unions on the use of “high risk” and intrusive forms of AI in the workplace.
• A legal right for all workers to have a human review of decisions made by AI systems so they can challenge decisions that are unfair and discriminatory.
• Amendments to the UK General Data Protection Regulation (UK GDPR) and Equality Act to guard against discriminatory algorithms.
• A legal right to ‘switch off’ from work so workers can create “communication free” time in their lives.

The pandemic has accelerated the adoption of automation to replace the productivity lost from having to furlough staff or make them redundant. The TUC notes how AI technologies are now making “high-risk, life-changing” decisions about workers’ lives—which is only likely to increase over the coming years.

Frances O’Grady, General Secretary of the TUC, commented:

“This is a fork in the road. AI at work could be used to improve productivity and working lives, but it is already being used to make life-changing decisions about people at work—like who gets hired and fired.

Without fair rules, the use of AI at work could lead to widespread discrimination and unfair treatment—especially for those in insecure work and the gig economy.

Every worker must have the right to have AI decisions reviewed by a human manager. And workplace AI must be harnessed for good, not to set punishing targets and rob workers of their dignity.”

The TUC is calling on tech companies, employers, and the government to support its proposed reforms.

A full copy of the report ‘Technology Managing People – the legal implications’ can be found here (PDF)

(Photo by engin akyurt on Unsplash)

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At its core, AI has a huge amount of potential to improve the way people work: think automating cumbersome processes, or helping employees be more efficient by balancing workloads and suggesting best-fit schedules. In effect, if it is leveraged in the right way, it can be instrumental in improving both an organisation’s bottom line and engagement of its workers.

Though there is some scepticism around AI in the workplace, I think it’s all in how you view it – can humans and machines coexist? Let’s take a look.

AI on the rise

AI has come a long way since its early days, when it was relegated largely to academic circles or the realm of science fiction. It’s now very much at the forefront, being used to make shift and holiday scheduling much less of a headache for employees, as a tool to transform marketing and customer service by analysing initial requests to match with the best human employee to carry out the task, and even as a pioneering technology in the world of data analytics to dive deep into data lakes much too cumbersome for a human, and bringing patterns and insights to the forefront.

These roles that AI is assuming alongside employees is being met with mixed reviews. According to a survey carried out by the Workforce Institute at Kronos, 92 percent of U.K. employees recognise that AI can make their lives easier by helping them improve the way they work. Alongside this, 68 percent said that they would be in favour of embracing AI if it helped them to better balance their workloads or increase fairness in subjective decisions.

So far, so good. But employees have concerns too.

Progress to be made

Digging a little deeper, 62 percent of respondents say that their employer has not yet shared details of plans to introduce AI with them. This lack of transparency can understandably lead to some workers fearing that their jobs are set to be replaced by so-called ‘better alternatives’.

However, there’s no need for this to be the case. There is a clear opportunity for leaders to be more transparent and communicative with their employees about the applications of AI and, specifically, how it can be hugely influential in making their lives easier and freeing up their time to focus on creativity and innovation. This point is again highlighted by the research: 63 percent of respondents said that they would be more comfortable with the introduction of AI if their employer were more open about how it will affect their roles.

A HR challenge, not just a technology one

Employees generally recognise that there’s potential in AI, but tackling any remaining suspicions is about focusing on the HR aspect of AI implementation, as well as the technological permutations. An organisation is only as strong as its people, so their well-being should be a close consideration whenever any change to the business is introduced.

This means that managers and leadership teams need to be as transparent as possible about how the technology will work, how they will work with the technology, and place special emphasis on its virtues and underlining how each person’s role will or will not change.

People innovate, technology facilitates

In any industry, it will always be people who contribute the innovative thought that will drive an organisation forward – with technology then being a tool through which this innovation will be facilitated. AI is no different in this respect: it will play a pivotal role in the workplace of the future, but its potential can only be maximised when it is used in tandem with the creative flair that human staff provide.

If managers and business leaders can communicate this message to their employees effectively, AI will be welcomed with open arms and its promise will be fulfilled.

Interested in hearing industry leaders discuss subjects like this and their use cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, Blockchain Expo, and Cyber Security & Cloud Expo.

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The company is using the data for a new feature called ‘Profile Recommendations’ whereby the app will recommend switching to a correct profile for your journey.

Many people will have two Uber profile – one for personal use, and the other for business.

Ronnie Gurion, GM and Global Head of Uber for Business, says:

“Using machine learning, Uber can predict which profile and corresponding payment method an employee should be using, and make the appropriate recommendation.”

When quickly booking a ride, it can be easy to forget to switch. Accidentally booking a ride home from a night out using a business account set up with a workplace’s payment details is an unwanted conversation with an employer.

Uber believes its success rate for determining the correct profile is around 80 percent.

To help reduce the 20 percent it gets wrong, businesses can assign ‘trip reviewers’ who know whether an employee’s use is supposed to be personal.

Any questionable rides can be flagged by the reviewer and the employee can decide in the app if it was supposed to be a personal ride or not. The whole process is designed to be much quicker than starting email threads about the issue and similar bureaucratic processes.

What are your thoughts on Uber’s use of AI for its latest feature? Let us know in the comments.

 Interested in hearing industry leaders discuss subjects like this and sharing their use-cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London and Amsterdam to learn more. Co-located with the  IoT Tech Expo, Blockchain Expo and Cyber Security & Cloud Expo so you can explore the future of enterprise technology in one place.

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