Employers

Meaning, there’s a missed opportunity for trusts to streamline operations and transform care. Only one in five NHS organisations are considered “digitally mature”. And despite lots of progress in the last decade, there are still areas of the NHS relying on paper and non-digital processes.

It makes embracing new technologies, such as AI, feel like an unattainable goal – one that goes beyond moving the health service from analogue to digital.

As we enter this new era for the NHS, data and digital skills across the workforce will be fundamental to improving patient care, streamlining processes, and making cost savings.

The case for upskilling in the NHS

Why should a consultant anaesthetist care about data skills? You might not immediately think it’s important.

But when we show how understanding patient data supports positive patient outcomes, the story changes.

Data and AI skills can support better decision-making, automate routine tasks and even enable innovation from within teams – outcomes that are relevant for roles across each trust.

Being data-driven moves the health service away from a reliance on “gut feeling” when making decisions. So, the information NHS staff work with becomes more meaningful – with the opportunity to save millions in costs.

With more than 1,500 learners across 95 NHS trusts and arm’s-length bodies, Multiverse’s digital, data and AI training programmes have so far unlocked £10m in savings over six months. And that’s just the tip of the iceberg.

Building on a skills foundation to boost productivity

Data and AI skills have to be embedded into every layer of trusts in order to deliver the lasting impact the health service needs.

Looking at skills holistically will improve data maturity and, in turn, AI readiness.

Assessing the levels of data maturity in the workforce will help NHS trust leaders understand their current skill gaps and opportunities for growth. Tailored learning programmes can then align with the goals and objectives of the transformation strategy.

Aligning skills requirements with strategic workforce planning processes creates a solid foundation – making skill gaps easier to spot and solve.

Importantly, providing upskilling through the levy, combined with applied learning, means people can learn on the job – making a stronger link between the training and how it impacts their day-to-day. After all, what’s the point of learning new skills if they can’t be applied directly into your role?

North London Foundation Trust (NLFT), for example, needed to reset its company culture around technology. To make this happen, the trust provided an upskilling programme, delivered by Multiverse, to improve data literacy across its workforce and improve productivity.

One learner used the analytical skills gained in the Digital Academy to pinpoint bottlenecks in one department’s discharge process. By employing data visualisation techniques using Power BI, he could effectively illustrate the issues, reducing the number of active patients awaiting assessments from 25 to one within nine months.

Engaging staff for a future-fit NHS

Improving the data and AI skills of NHS staff can create opportunities across the service. From improving patient outcomes to automating routine tasks, freeing up time and even enabling innovation from the inside.

The results from our digital, data and AI programmes show what’s possible. We see NHS workers saving on average seven hours a week – just from improving their data skills.

Today, the NHS can take advantage of the levy – a strategic funding pot for trusts to deliver applied learning that upskills the workforce at scale and at no extra commercial cost.

Levy-funded training is an ideal way to harness the talents of NHS workers to effect positive change – helping every employee gain the skills and confidence to support the digital evolution of the NHS.

Multiverse is empowering every NHS employee to unlock innovation and improve patient care through our applied learning programmes. Discover more

Article originally featured in HSJ Online

The AI Opportunities Action Plan highlights the potential the technology has to enhance efficiency, improve service delivery and support better decision-making.

The big question is: what does it mean for public services?

Howard Lewis, the managing director of Modern Workplace at Microsoft, shares some thoughts on how to take advantage of AI in local government and strengthen public sector services. Here’s a snapshot of what he has to say.

Applying AI in the public sector

In practice, implementing AI in the public sector could look like:

1. Predictive insights to notify when potholes could need maintenance, social care services that might require urgent intervention, and where emergency services could need to be deployed based on data trends.
2. Automating back-office processes to free up staff time for higher value or community-facing work.
3. Improving citizen engagement with AI-powered chatbots that handle common questions, reducing response times and improving accessibility.

But the challenge is implementation. AI is only as effective as the strategy and the people behind it. And that's why we're seeing a shift from exploring AI to developing real-life use cases which benefit the public.

An AI-ready culture comes from the top

Successful AI adoption starts with strong leadership. Whether it’s breaking down silos or driving data strategies, public sector leaders need to be champions of change – creating a culture of collaboration and innovation.

"Encouraging the right culture comes from the top-down – no matter what you’re looking to achieve. When implementing AI, business leaders need to be active, visible and demonstrate consistent participation."

Howard Lewis, Managing director of Modern Workplace at Microsoft

To make this possible, building a coalition with executive peers and the wider management community will help to engage the rest of the organisation – enabling a culture that’s ready for change.

Establish ethical frameworks for AI usage

There are several pillars of an AI ethics framework, including fairness, accountability, transparency, reliability and safety, inclusivity, and privacy and security.

Yet, a framework alone won’t do the job – you also need strong internal communications.

“Communication is key. You have to demonstrate the importance of the framework, why shortcuts shouldn't be taken, and the impact on fair, secure and accurate AI usage,” Howard explains. “Never has this been more necessary than in the public sector, where employees work with sometimes confidential and sensitive data.”

Having an ethical framework for how you will use AI can also help reduce data constraints. That means no waiting to sort your data quality to get started. Instead, your data strategy works alongside the implementation of AI – all shaped by your ethical framework.

“Starting with small-scale pilots helps to get the ball rolling and see those early wins, but it also means cleaning up your data in manageable chunks so it’s ready to use for specific applications,” Howard shares.

Empower your people

Today, the topic of AI adoption coincides with concerns about how the technology could be used to replace workers.

“Establishing clearly how AI will be applied can help to assuage worries. But, you can empower your workforce too if you’re able to show how their involvement is critical,” Howard explains. “We call this: keeping humans in the loop. And it’s a vital part of ensuring compliance is maintained too.”

The key to getting this right, Howard says, is upskilling and reskilling employees on AI. By ensuring staff can understand and apply the technology, you can create an environment where people feel empowered.

“Having the right skills in your workforce means employees can start to think of creative, responsible ways to leverage AI to improve legacy processes and deliver real, long-term impact.”

Howard Lewis, Managing director of Modern Workplace at Microsoft

When people feel empowered to use AI – with the appropriate guardrails in place – public services will benefit from more available time for human contact and support.

Collaborate with partners to develop best practice

“Whether it’s demonstrating real-world use cases or how to address your specific AI applications, technology partners can help you identify and prioritise high-impact areas for implementation,” Howard mentions.

By partnering with trusted AI advisors, the public sector can focus on driving the most meaningful change. “There’s a feedback loop to partnerships that means you can benefit from the technology now and as it evolves to better meet their needs,” Howard concludes

At Multiverse, we’re partnering with Microsoft to equip 1 million people with the skills needed to thrive in an AI-enabled economy by 2025. By collaborating, we can work together to share expertise and create opportunities to prioritise best practice.

Get started today

It’s important to remember the public sector is only two years into working with AI on a large scale.

While there could be a tendency to feel left behind or out of the loop, public services adoption is just getting started. As long as those in the sector take initial steps to begin AI implementation today, no one will be left behind.

See how Essex County Council and the NHS are embarking on their digital transformation journey with incremental changes.

Nearly three in four (72%) businesses are using AI, which is up from 50% in previous years, according to McKinsey.

Here are 10 key benefits of AI in the workplace – and four ways you can unlock them within your business:

10 benefits of AI in the workplace

1. New career opportunities: The World Economic Forum (WEF) predicts that by 2027 we’ll see 2.6 million jobs added by AI.
2. Revenue increases: Four in five leaders say implementing AI has led to an increase in revenue generation (Multiverse ROI of AI report). About 75% of the value that generative AI (GenAI) could deliver falls across four areas: customer operations, marketing and sales, software engineering and R&D (McKinsey).
3. A productivity boost: Businesses using AI to sort vast amounts of customer and market data are seeing as much as an 80% reduction in data processing time – supporting a 40% improvement in speed to market for new products and services (Accenture).
4. Increased GDP: PwC and McKinsey report that global GDP will be 14% higher in 2030 as a direct result of AI – the equivalent of a staggering $15.7 trillion of new value.
5. Creating efficiencies: More than 80% of workers surveyed – who use generative AI (GenAI) daily – expect it to make their time at work more efficient in the next 12 months (PwC).
6. Business value: 83% of workers think AI skills will help them to drive more value for their employer in the next 12 months (ROI of AI report).
7. Greater employee satisfaction: Deloitte reports that, on average, more than half of Millennials (55%) and Gen Z (58%) employees believe GenAI will free up time and improve work/life balance. And half (49%) of all daily GenAI users expect the technology to lead to higher salaries (PwC).
8. Increased demand for AI specialists: The WEF expects to see a 40% jump in the number of AI and machine learning specialists. And a 30%-35% rise in demand for roles such as data analysts and scientists or big data specialists.
9. Heightened competitive advantage: 68% of senior leaders in financial services and telcos believe that competitive advantage in their industry will depend on who can make the best use of AI (Experian).
10. Transforming industries: According to cross-industry research from Accenture, 90% of C-level executives expect GenAI to revolutionise their industry and customer interactions. However, separate insight from the company found that the banking (54%) and insurance (48%) industries hold the highest potential for AI impact through automation.

4 ways to unlock the benefits of AI in your workforce

1. Create a future-ready AI skills strategy

Tech investments need to be combined with an AI-enabled workforce to get the most from the technology. But there are several barriers holding businesses back from reaching AI maturity – and technical skills are a big one.

In fact, our ROI of AI: Unlocking AI maturity through workforce skills report found that leaders currently name AI as their most significant skill gap (45%).

That’s because AI and data literacy is an ongoing challenge in the workplace. Half of workers have received less than five hours of AI training. And employees struggle with the basic data sksills needed to achieve the full benefits of AI, such as making data more efficient (53%) or analysing data to make informed data-driven decisions (46%).

Fixing these skills gaps starts with a targeted upskilling strategy. One which equips your teams the most needed AI skills for your business.

These skills may be different across sectors, job titles, roles and functions, and your crafting an effective AI skills strategy needs to first begin with identifying your business opportunities to generate Return On Investment (ROI) from AI.

2. Define measurable goals

Measurement should sit at the heart of your strategy.

Setting a benchmark for measuring success with AI also helps to ensure all training ladders up to your business’s wider picture. Do your customer service executives need training in how to automate manual processes? If one of your goals is to improve the speed of customer responses, then the answer could be yes.

However, measurement is only as successful as the strength of the strategy and goals set in the first place. Only then can results truly be measured to anticipate hurdles and uncover opportunities.

3. Give teams the tools and training they need to succeed

Once you’ve got a solid skills strategy in place, implementing tools and training is the next step.

When we think of tools, it’s easy to go straight to technology. But, when it comes to unlocking the benefits of AI in your workforce, providing safe guardrails to innovate is vital. That means creating clear policies, guidelines or even Centres of Excellence with best practice examples.

Today, just 45% of employees have received formal AI training provided by their employer. So, it’s likely workers will struggle to assess whether their actions are aligned with the company without policies or broader best practice – creating potential risks for the business.

It’s about ensuring policies are being adhered to, with people not only accountable for how they’re using AI, but also proud of it. That means fostering a positive culture around AI in the workplace, with the integration of technologies into operations, processes, and employee interactions.

4. Enable new career opportunities for employees through AI skills

Businesses need to build expertise in AI, fast, but formal AI training opportunities remain in short supply.

Our data shows that most workers learn AI skills informally by experimenting with ChatGPT (61%) or learning on the job (59%). And half (51%) have received fewer than five hours of training on AI.

This presents challenges for both the worker and the business, from struggling to assess knowledge gaps to unlocking efficient processes.

According to our ROI of AI report, businesses are aware of the gaps and leaders are looking to invest in data upskilling in 2025. Half of the organisations that have identified skills gaps as a key barrier to full implementation of AI plan on upskilling employees through long-term external AI training programmes (56%) and ad-hoc/short-term external AI training programmes (50%).

There’s a clear opportunity for businesses to upskill employees in AI – unleashing productivity benefits, opening up new career pathways, and delivering measurable impact.

But while financial institutions are making significant investments in AI technology, many are still developing the workforce capabilities needed to maximise its potential. This presents a timely opportunity for organisations to gain competitive advantage through strategic upskilling.

Our recent research reveals an industry at an inflection point: enthusiastically adopting new technology while simultaneously working to develop the human skills that drive AI success.

"The future of financial services isn't written by algorithms, but by the people who understand how to make those algorithms work for humanity." Anna Wang, Head of AI, AI Advisory Board Member - Multiverse

Based on our comprehensive survey of senior leaders in UK financial institutions,* here are the critical insights defining the state of AI in financial services today:

AI adoption surges, while results lag behind

67% of financial organisations are using AI for process automation, yet only 37% report transformative business results.

Financial institutions are enthusiastically embracing AI across multiple functions:

• 67% for process automation and operational efficiency
• 64% for customer service enhancement
• 57% for strengthening cybersecurity
• 52% for risk management and fraud detection

But despite widespread implementation, the majority (47%) experience only moderate benefits, while 9% admit they aren't measuring AI's impact at all.

The workforce readiness gap

Only 46% of financial institutions are heavily investing in AI upskilling, while 11% have no formal AI training initiatives whatsoever.

Organisations face critical skills gaps in:

• Building AI features (40%)
• Identifying AI use cases (37%)
• Implementing AI projects (33%)
• Risk management (32%)
• Ethical AI practices (30%)

The competitive landscape: An industry of explorers

Only 37% of financial institutions rate their AI maturity ahead of competitors.

The research reveals most organisations remain in early maturity stages:

• 52% classify themselves as "AI Explorers"
• 55% view their AI maturity as comparable to peers

This relatively level playing field creates a significant opportunity for ambitious organisations to gain competitive advantage through strategic skills development.

The future of AI in financial services

Our research shows financial leaders expect AI to transform:

• Cybersecurity (64%)
• Customer service & engagement (55%)
• Regulatory compliance & reporting (48%)
• Process automation & operational efficiency (57%)

Yet this transformation depends entirely on workforce readiness. While 36% of leaders believe AI will transform their roles and create new opportunities, 12% fear their roles may become redundant without proper adaptation.

"The biggest risk is being left behind and seen as uncompetitive because the organisation cannot deliver the service levels that others will have developed." Senior Financial Services Leader

The path forward

Organisations that successfully bridge the AI skills gap will lead the industry through:

• Enhanced cybersecurity capabilities
• Hyper-personalised customer experiences
• Automated compliance through regulatory technology
• Operational efficiencies with AI co-pilots
• Strategic decision-making powered by predictive insights

But this future is only possible with strategic investment in people alongside technology.

Methodology

*The survey, conducted by Radish on behalf of Multiverse between February and March 2025, targeted 157 leaders within financial services organisations. An online survey was used, with all respondents based in the UK. Phone interviews with leaders within the financial services sector were also conducted.

The reality is that AI is here to stay. But with mounting questions around risk, governance and making a return on investment (ROI), how can leaders move from chaos to competence with AI? And how can they overcome AI adoption challenges?

We spoke to Rudy Lai, CEO at Tactic, and Jason Smith, AI Strategy Lead at Publicis Media, to tackle these questions and to share guidance on how best to get started.

Lesson 1: Prioritise people and processes

What’s their best advice for starting AI transformation?

“The technology is the least of your worries,” says Jason. “People and process are two of the most difficult things to get right.”

Jason recommends assessing the ‘day in the life’ of your workers to understand how generative AI (GenAI) can help, while also encouraging people to be hands-on with the technology. He adds:

<block-starlight>“Because GenAI has democratised access to AI and machine learning, people need to roll their sleeves up, try things, and get grace to make mistakes.”</block-starlight>

“Everybody understands that AI is the next big thing, the next business opportunity, the next tool to create impact,” says Rudy, agreeing on the need to focus on people and processes.

He argues many businesses struggle to find the right place to start, and suggests a three-tiered approach when thinking about AI adoption:

• Tier one: empowering employees with GenAI tools such as Microsoft Copilot, helping people be more productive.
• Tier two: transforming your product or services with AI features.
• Tier three: using AI to create entirely new business models.

As you move through each tier, you’ll shift from internally focused AI use cases to external ones. How far you’ve progressed depends on a range of factors, including your level of data skills maturity.

However, Rudy argues: “No matter how you slice and dice the use cases of AI in your organisation, you always need to go back to the business impact.”

Upskilling should be treated as a priority – giving your people the foundational data skills to unleash the potential of AI.

Lesson 2: Identify champions to support AI implementation

When asked which teams are most receptive to AI, Rudy notes that it depends on task suitability, digital maturity, and staff readiness:

“One of the first signs of a department being AI-ready is you can imagine putting the work they do into a large language model (LLM) and automating it.”

He adds that “well-defined problems” such as repeating tasks and processes are good candidates for automation. And not to forget: teams with an existing strong data culture will be better targets for initial AI adoption.

AI champions – people who are curious, proactive, and willing to experiment with new tools – is one way to encourage adoption.

So what else makes a great AI champion?

“[They have] the right mindset, a willingness to give it a go,” says Jason. AI optimism goes a long way – and these people may already be building rough and ready prototypes to show what can be achieved – even if these prototypes aren’t perfect.

After getting AI champions on a consistent skill level, they can act as mentors to others around them – as well as being focal points for spotting new use cases.

“Those use cases are when you can start to get some traction with the help of these champions, who can then hopefully bring other team members along,” he adds.

One initial step you can take to identify your AI champions is reviewing your skills inventory – helping you spot AI capability and strengths that may already exist in your workforce.

Lesson 3: Watch out for ‘shadow AI’ to manage risk and AI governance

Significant risks are emerging from unmanaged AI use – also known as ‘shadow AI’.

Without proper AI tool oversight, risks can include data leakage, compliance issues, and misinformation. It’s a challenge that adds to the barriers to AI adoption.

Given the availability of free-to-access tools, as well as new players entering the market such as DeepSeek, businesses can run into difficulty when they have no rules or protections in place around tool use.

“There's not a huge amount of visibility on how and what people are using, and it’s fairly challenging to detect,” says Rudy.

“People can be almost too excited about what AI can do, and being too reliant on what AI is producing without verification.”

As well as the need to have solid AI governance frameworks in place, Jason argues responsible AI usage should also be considered, with people asking the questions:

“Should I do this? Is it ethically correct? That's much more difficult to get right, but you have to factor in both [governance and responsible use]. It's important to recognise what might be the unintended consequences of deployment and adoption,” he says.

So how can these risks be contained?

Creating a ‘sandbox’ environment where your people can experiment with AI tools safely is one way to protect leaders from risk, data security and compliance challenges.

For it to work, Jason suggests: “It’s a combination of leadership setting the tone and the policies. Make sure agreements are in place so you can use the tools in the sandbox. And then training so that people are aware of the risks.”

Lesson 4: ‘Find the baseline’ to measure the ROI of AI

As AI projects shift from proof-of-concepts to full adoption, showing the ROI of AI is a recurring theme for leaders making a business case for AI.

And while there is no one-size-fits-all approach or a ‘magic measurement tool’ to share all the answers, the panel recommends going back to basics on measurement.

Rudy advises against using vanity metrics, and instead for people to look at the 'business as usual' KPIs they're already tracking.

“Vanity metrics don't deliver real business impacts because you have shifted the focus from what you need – such as time efficiency, cost efficiency, or more revenue.”

It’s a sentiment echoed by Jason, who says how you measure can vary between use cases. He recommends establishing ‘baselines’ that you measure in the business:

“If you've got that in place it's going to make it much easier for you to measure your return on investment.”

What next with your AI adoption challenges?

With agentic AI influencing trends in 2025, you are likely looking closely at how to overcome your AI adoption challenges.

Rudy and Jason share three principles to help get you started:

1. Start with clear business goals, not just AI hype
2. Empower internal AI champions to drive change
3. Balance innovation with governance to scale AI safely

The reality is that AI is here to stay. But with mounting questions around risk, governance and making a return on investment (ROI), how can leaders move from chaos to competence with AI? And how can they overcome AI adoption challenges?

We spoke to Rudy Lai, CEO at Tactic, and Jason Smith, AI Strategy Lead at Publicis Media, to tackle these questions and to share guidance on how best to get started.

Lesson 1: Prioritize people and processes

What’s their best advice for starting AI transformation?

“The technology is the least of your worries,” says Jason. “People and process are two of the most difficult things to get right.”

Jason recommends assessing the ‘day in the life’ of your workers to understand how generative AI (GenAI) can help, while also encouraging people to be hands-on with the technology.

“Because GenAI has democratized access to AI and machine learning, people need to roll their sleeves up, try things, and get grace to make mistakes,” he adds.

“Everybody understands that AI is the next big thing, the next business opportunity, the next tool to create impact,” says Rudy, agreeing on the need to focus on people and processes.

He argues many businesses struggle to find the right place to start, and suggests a three-tiered approach when thinking about AI adoption:

• Tier one: empowering employees with GenAI tools such as Microsoft Copilot, helping people be more productive.
• Tier two: transforming your product or services with AI features.
• Tier three: using AI to create entirely new business models.

As you move through each tier, you’ll shift from internally focused AI use cases to external ones. How far you’ve progressed depends on a range of factors, including your level of data skills maturity.

However, Rudy argues: “No matter how you slice and dice the use cases of AI in your organization, you always need to go back to the business impact.”

Upskilling should be treated as a priority – giving your people the foundational data skills to unleash the potential of AI.

Lesson 2: Identify champions to support AI implementation

When asked which teams are most receptive to AI, Rudy notes that it depends on task suitability, digital maturity, and staff readiness:

“One of the first signs of a department being AI-ready is you can imagine putting the work they do into a large language model (LLM) and automating it.”

He adds that “well-defined problems” such as repeating tasks and processes are good candidates for automation. And not to forget: teams with an existing strong data culture will be better targets for initial AI adoption.

AI champions – people who are curious, proactive, and willing to experiment with new tools – is one way to encourage adoption.

So what else makes a great AI champion?

“[They have] the right mindset, a willingness to give it a go,” says Jason. AI optimism goes a long way – and these people may already be building rough and ready prototypes to show what can be achieved – even if these prototypes aren’t perfect.

After getting AI champions on a consistent skill level, they can act as mentors to others around them – as well as being focal points for spotting new use cases.

“Those use cases are when you can start to get some traction with the help of these champions, who can then hopefully bring other team members along,” he adds.

One initial step you can take to identify your AI champions is reviewing your skills inventory – helping you spot AI capability and strengths that may already exist in your workforce.

Lesson 3: Watch out for ‘shadow AI’ to manage risk and AI governance

Significant risks are emerging from unmanaged AI use – also known as ‘shadow AI’.

Without proper AI tool oversight, risks can include data leakage, compliance issues, and misinformation. It’s a challenge that adds to the barriers to AI adoption.

Given the availability of free-to-access tools, as well as new players entering the market such as DeepSeek, businesses can run into difficulty when they have no rules or protections in place around tool use.

“There's not a huge amount of visibility on how and what people are using, and it’s fairly challenging to detect,” says Rudy.

“People can be almost too excited about what AI can do, and being too reliant on what AI is producing without verification.”

As well as the need to have solid AI governance frameworks in place, Jason argues responsible AI usage should also be considered, with people asking the questions:

“Should I do this? Is it ethically correct? That's much more difficult to get right, but you have to factor in both [governance and responsible use]. It's important to recognize what might be the unintended consequences of deployment and adoption,” he says.

So how can these risks be contained?

Creating a ‘sandbox’ environment where your people can experiment with AI tools safely is one way to protect leaders from risk, data security and compliance challenges.

For it to work, Jason suggests: “It’s a combination of leadership setting the tone and the policies. Make sure agreements are in place so you can use the tools in the sandbox. And then training so that people are aware of the risks.”

Lesson 4: ‘Find the baseline’ to measure the ROI of AI

As AI projects shift from proof-of-concepts to full adoption, showing the ROI of AI is a recurring theme for leaders making a business case for AI.

And while there is no one-size-fits-all approach or a ‘magic measurement tool’ to share all the answers, the panel recommends going back to basics on measurement.

Rudy advises against using vanity metrics, and instead for people to look at the 'business as usual' KPIs they're already tracking.

“Vanity metrics don't deliver real business impacts because you have shifted the focus from what you need – such as time efficiency, cost efficiency, or more revenue.”

It’s a sentiment echoed by Jason, who says how you measure can vary between use cases. He recommends establishing ‘baselines’ that you measure in the business:

“If you've got that in place it's going to make it much easier for you to measure your return on investment.”

What next with your AI adoption challenges?

With agentic AI influencing trends in 2025, you are likely looking closely at how to overcome your AI adoption challenges.

Rudy and Jason share three principles to help get you started:

1. Start with clear business goals, not just AI hype
2. Empower internal AI champions to drive change
3. Balance innovation with governance to scale AI safely

The power is now in the hands of employers and learners to decide if achieving a level 2 English and Maths qualification should form part of their apprenticeship course – after the UK Government announced a change in the rules.

Employers have consistently told us that functional skills apprenticeship requirements act as a blocker to apprenticeship take-up – so removing this bureaucratic barrier is great news for both employers and apprentices.

Let’s explore what’s been announced and what it means for apprenticeship programmes.

What functional skills apprenticeship rules has the Government changed?

The government is relaxing the functional skills rules for adult apprentices (people aged 19 and over) with immediate effect.

Previously, learners who didn’t pass Maths and English at GCSE had to achieve a functional skills qualification to complete their course.

Now, businesses and apprentices have the power to choose whether functional skills qualifications should be an exit requirement on their courses or not. Apprentices will still have the opportunity to develop English and Maths skills relevant to their chosen apprenticeship standard as part of their programme.

Announced during National Apprenticeship Week, the Government says the changes will mean up to 10,000 more apprentices will qualify from training every year. It’s hoped this will boost the number of skilled people entering high-demand sectors.

The changes will apply to apprentices who are currently on programme (provided they were over 19 at the time of starting their course) as well as apprentices who have not yet started. Many of those that have previously withdrawn due to functional skills requirements, will also be able to re-enroll.

Apprentices aged 16-18 will still have to complete a functional skills qualification as a part of their course.

The Multiverse take on functional skills in apprenticeships

At Multiverse, we’ve consistently campaigned for the reform of functional skills and welcome the changes made by the Government. We believe they will make for a fairer and more inclusive apprenticeship system, improving access to skills at every age and every career stage.

For example, employers may already be satisfied with the Maths and English abilities of their employees, based on performance in their role – even if they don’t have formal qualifications, achieved through a written test. For some apprentices, the previous rules meant digging out evidence of old qualifications in order to finish their course – which might not always have been possible.

The changes will also improve access to apprenticeships for those from disadvantaged backgrounds.

Department for Education data suggests 38% of non-disadvantaged pupils without a Level 2 in English and maths by age 16 will achieve it by age 19, the proportion is only 24% for people from a disadvantaged background.

The change means employers can shift attention to tackling the skills gaps they want to address, and learners can focus on developing and deploying their skills.

Speaking in response to the Government’s announcement, Multiverse CEO and founder Euan Blair said the reforms will widen and expand access to apprenticeships:

“For years this requirement has created an artificial barrier between apprenticeships and those who could benefit from them, including young people from disadvantaged backgrounds and older workers whose roles are at risk of job displacement, while often diluting the quality and purpose of an apprenticeship.

“Apprenticeships are about giving as many people as possible the ability to improve their career prospects and contribute meaningfully to their employers: this move helps to underline that focus.”

What business leaders are saying about functional skills changes

Multiverse helps more than 1,500 leading companies upskill their workforces with our apprenticeship programmes – and we’ve trained more than 20,000 professional apprentices.

For a long time, employers have said the old rules acted as a hurdle to apprenticeship uptake. We know many of the organisations we work with are welcoming the news, including the John Lewis Partnership (JLP):

“We welcome the relaxation in functional skills requirements. It’s an important step towards the reform needed to help more people access apprenticeships. Gaining GCSE Maths and English qualifications can be a significant barrier to starting or completing one and we believe it will help more disadvantaged people, including those who leave the care system or those with learning disabilities, make a career for themselves.”

Jo Rackham
Executive Director of People, JLP

What other changes have the Government announced?

The Government also confirmed plans to cut the legal minimum length of apprenticeships from 12 to eight months, as part of the Growth and Skills levy reform. The change in the minimum length of an apprenticeship is expected to be introduced in August 2025.

Three Trailblazer areas will pioneer the approach first:

• Green energy
• Healthcare
• Film and TV production sectors

Multiverse is in conversation with policymakers on what this approach could look like for critical data and AI programmes.

What steps should employers take next?

If you need support navigating the changes to functional skills requirements, our expert team is on hand to help.

Capita launched its Data and AI Academy last year, designed to equip employees with new skills to use AI responsibly and drive business outcomes.

Lisa told us about her vision for AI skills at scale, the value of internal storytelling, and her lessons for leaders embarking on multi-year transformation journeys.

First things first. Can you tell us a little about your experience, your role at Capita, and your career journey to your current role?

I’ve been with Capita for 19 years and have a broad remit, looking after all things performance and development, culture, responsible business, and our early careers and apprenticeship offer.

I fell into learning from recruitment, and developed a fond love of lifelong learning as a result. When I left school, I went straight into an apprenticeship with a car manufacturer, and then joined Capita in a recruitment role, where I was lucky enough to study my CIPD part-time to get my HR qualifications.

Recently I’ve done my Master's in Leadership as well, funded through the Apprenticeship Levy, which was a fantastic opportunity to go back and study. So I’m a huge advocate for all things apprenticeships!

How is Capita approaching the opportunity of AI?

AI is fundamental to Capita’s ‘Unlocking Value Together’ strategy. We’re helping to reduce operational costs for our customers and enable them to provide higher-quality work to their employees, by removing repetitive and mundane tasks.

We’ve been partnering with several local authorities on proof of concepts to test out new AI tools. For example, we're helping advisors in our contact centres with a more human-centred and empathetic approach to how we deal with customer enquiries. AI allows us to listen to live conversations and seamlessly stitch together the council services in the background. It equips advisors to answer many enquiries much faster. It’s reduced our average call handling times for clients by 20%, which has a brilliant impact on our customer service and CNPS.

A separate trial for the British Army uses AI to streamline and process medical records, reducing processing times for applicants by 30%.

We're also drawing on the expertise of the highest calibre AI engineers and partnering with technology hyperscalers, including the likes of Microsoft ServiceNow, Salesforce and AWS, to develop efficient, ethical, impactful solutions, which now underpin our operations.

How is AI transforming the skills teams need at Capita?

We’re having to think about skills in a completely different way. As part of our workforce planning strategy and the work of my team, we’re looking at how we augment humans with the AI capability we’re bringing in – it’s a huge shift in mindset.

I’m really thinking about the skills the organisation needs in the future. The reality is that AI is transforming how teams operate, automating more repetitive tasks, and simplifying workflows.

It’s allowing us to focus on different skills, and for us, we’re prioritising data literacy. The AI we’re using is only as good as the data that we’ve got. We’re therefore trying to enable teams to interpret that data as fluently as possible. It doesn’t mean we’re training everybody to be data scientists, by any means, but it’s giving anyone the fundamental skills to ask the right questions, and critically analyse AI-generated insights to make better informed decisions.

We’re also looking at the behavioural skills that go alongside that, creating curiosity and an adaptive learning mindset. For instance, we need higher levels of emotional intelligence than before to help with critical thinking and problem-solving.

One way Capita is taking action has been launching the Data and AI Academy. Can you tell us how that idea came about and the goals of the programme?

The Data and AI Academy has been fundamental to us shifting the dial. The need came from a multitude of different skills we were looking to develop, particularly around technical proficiency.

For our employees, it’s about understanding the benefits of AI, the basics around data science and machine learning, as well as AI literacy. Ethical considerations and the responsible use of AI are also massively important.

We can’t underestimate AI's impact on frontline colleagues, so we’re focussing on adaptability: giving individuals the skills to be curious and continue to learn. We want our employees to make that human judgement and be creative for the parts that AI can’t replicate.

Data management and analysis is another area. We want to ensure everyone understands data governance, security practices, and the data lifecycle.

We’re proud of the programme we’ve built in partnership with Multiverse. We’ve got 86 learners on the AI for Business Value apprenticeship, and that's had a significant impact on our business.

I’m also incredibly proud of the materials we’ve built together for colleagues who sit out of the Levy-funded options. It’s important we’re developing AI literacy right across the business.

What made you decide to work with Multiverse?

The reason we chose Multiverse was their ability to demonstrate thought leadership in the AI space. We felt that out of all of the providers that we have worked with, or we went through a procurement exercise with, Multiverse was able to demonstrate the link to the actual business benefit.

Multiverse took the time to understand the transformation and change journey that Capita is on, and build something that was appropriate and meaningful to our employees.

The flexibility that Multiverse has given us on content and delivery styles for different audiences, from lower levels to leadership, has been fantastic, and we've seen a huge impact from that.

The biggest thing is true partnership. It's listening, it's understanding each other and building something that's successful together.

What’s the biggest success you’ve seen from the AI Academy? And what are you proudest of so far?

I’m proud we’ve got people talking about AI and the impact it can have while dispelling some of the myths.

It’s been lovely to do some internal storytelling around people's success on the programme. We often do things like fireside chats where individuals share their proof of concepts. One apprentice recently shared the impact of manual processing changes they’d made within back-office operations. Hearing somebody bring it to life and talk with such fluency around their AI solutions was fantastic.

I’m also hugely proud of our Microsoft 365 Copilot rollout, which is happening across the business. Using the AI for Business Value programme, we’re integrating our internal learning alongside how we’re developing Copilot's impact on our business.

How are employees responding to AI-driven changes in workforce development and skills programmes?

The business has undergone a huge transformation, and naturally, there has been a lot of scepticism about AI replacing human interaction. What this programme has done is demonstrate the advantages that you can have with AI. Our employees are now much more curious – the programme has made them keen to be involved and learn more.

Where there was maybe a fear of job displacement or reluctance to change previously, we’re finding that people are embracing AI.

Learners on the apprenticeship sharing their stories and successes has been fantastic – it’s bringing more people to the table and making them want to be part of the journey. We’re now seeing the knock-on effects where we’ve got people breaking down the door to be part of the next cohorts – it's exactly the success we wanted to get.

Let’s talk strategy. How does workforce transformation in AI support Capita’s broader strategic goals?

A big part of my role at the moment is leading our cultural transformation globally, and emphasising AI's ethical and responsible use across the business. It’s part of our Better Company pillar, which ladders up to our Unlocking Value Together strategy.

We have to align our cultural transformation with AI, so we can drive operational efficiencies, improve governance, and create better skills development to support our tech-enabled culture and future.

We're also refreshing our values at the moment, which I’m leading. It’s been fantastic hearing people so energised in focus groups about the opportunity that AI and data presents, and the opportunity to think about their roles in a different way – less transactional, and more creative and problem solving work.

What’s the biggest hurdle you’ve had so far on that journey, and how have you overcome it?

Navigating budget constraints. We've had to be as creative as ever to help individuals through that change journey, but also to give them the skills they need for the future.

So we've been repurposing a lot of our content – and challenging the art of the possible, utilising AI ourselves internally to create better materials and content.

Without our partners investing time to understand some of those challenges and be on that journey with us, it wouldn't have been such a success. So we’re grateful for the support Multiverse has given us.

Do you have a piece of advice that you’d share with other leaders looking to embark on a similar journey?

Don’t underestimate the change journey. For us, it’s a multi-year strategy – and not something that will happen overnight. We’re introducing AI and continuous improvement initiatives to change employees’ perceptions and drive teams to work together differently over time. But, it’s required strong leadership in that process.

We’re investing lots of time with our senior leadership team to help develop their skills. We want our leaders to become real advocates for changing workforce planning and viewing career pathways differently.

To build a truly augmented workforce, you must make sure all members of the organisation – at all career levels – are equipped with the right skills and tech. It's simple things. Make sure they've got the right equipment, they've got the right tools, but then to allow them to trial things and have a safer space to fail.

And finally, collaborate in strong partnerships. That’s the biggest element for me that’s been successful.

When you look at the year ahead, what are the trends shaping your role, and what are you doing to prepare?

I’m super excited about 2025. It will be keeping up with the rapid pace of change now – things are moving and accelerating faster than ever before. We’re using our budget as creatively as possible to upskill people to get ahead of that change.

Our business is hugely ambitious for its transformation with AI, and what we’re doing for our clients and customers. I can’t let our people down in giving them the skills to deliver what we’re expecting.

I’m also thinking about AI-driven learning experiences. We should practise what we preach and focus on social and collaborative learning to help individuals accelerate their growth. So we will be focused on upskilling and reskilling.

We all talk about the future of work, but do we understand what the future of work looks like in enough detail? We’re putting a lot of focus into that.

A practical challenge for me is ensuring that our remote workforce are still feeling part of that change journey, and adapting to our generational workforce and the differences that brings, as well.

One principle we have at Multiverse is that learning should be available for everyone at every age, and every stage. How is Capita considering this across the generational workforce?

Having five generations in the workplace is hugely exciting, but it brings lots of differences and lots of change. Multiverse has challenged our thinking around making sure that we have learning available to all different generations. Some Capita employees have been with us for a long time, and their roles are changing.

I’m sure that in some organisations those skills would be written off. Instead, it’s about looking early enough to ensure we are reskilling and upskilling. Individuals have got so much capability to do different things. We just need to make sure that we're challenging them in the right way, and giving them accessible, digestible content that’s relevant to their role.

I don’t think any inward learning team can do this on their own. Having truly great partnerships where you understand each other, you trust each other, and you can bring in the experts to fill gaps for you works wonders.

National Apprenticeship Week is coming up. How do you perceive the importance of apprenticeships at Capita?

On a personal level, apprenticeships have really supported me. They helped me at the start of my career, and I've now got a Master's funded through the Levy too.

Apprenticeships give fantastic opportunities to school leavers, but they are also an incredible mechanism for upskilling and reskilling. That's where we’ve tried to dispel myths at Capita – we’ve had over 700 learners go through apprenticeship programmes in the last couple of years. It's fantastic to see skills development in management, leadership, data and AI, where we're seeing huge impact and change.

The Levy allows us to partner and think about things in a slightly different way, using it as a mechanism to upskill our workforce. I’d encourage other organisations to think a little bit more outside the box about how you can use some of the apprenticeship standards that are out there to add business value.

So I will always continue to advocate for apprenticeships. It's hugely exciting to see how they develop and change individuals.

And finally, let’s end on a fun one… in an ideal world, what’s the one dream task you’d like AI to do for you?

I’d love it to manage my teenagers’ emotions for me! But joking aside, for me it would be to create a continuous learning culture of growth and curiosity. I’d love it if AI had a magic way to consistently embed that spirit of constant learning and growth into individuals and across the business.

It’s maturing and it's learning at such a rapid rate. Who knows what AI will do in the future?

Capita launched its Data and AI Academy last year, designed to equip employees with new skills to use AI responsibly and drive business outcomes.

Lisa told us about her vision for AI skills at scale, the value of internal storytelling, and her lessons for leaders embarking on multi-year transformation journeys.

First things first. Can you tell us a little about your experience, your role at Capita, and your career journey to your current role?

I’ve been with Capita for 19 years and have a broad remit, looking after all things performance and development, culture, responsible business, and our early careers and apprenticeship offer.

I fell into learning from recruitment, and developed a fond love of lifelong learning as a result. When I left school, I went straight into an apprenticeship with a car manufacturer, and then joined Capita in a recruitment role, where I was lucky enough to study my CIPD part-time to get my HR qualifications.

Recently I’ve done my Master's in Leadership as well, funded through the Apprenticeship Levy, which was a fantastic opportunity to go back and study. So I’m a huge advocate for all things apprenticeships!

How is Capita approaching the opportunity of AI?

AI is fundamental to Capita’s ‘Unlocking Value Together’ strategy. We’re helping to reduce operational costs for our customers and enable them to provide higher-quality work to their employees, by removing repetitive and mundane tasks.

We’ve been partnering with several local authorities on proof of concepts to test out new AI tools. For example, we're helping advisors in our contact centres with a more human-centred and empathetic approach to how we deal with customer enquiries. AI allows us to listen to live conversations and seamlessly stitch together the council services in the background. It equips advisors to answer many enquiries much faster. It’s reduced our average call handling times for clients by 20%, which has a brilliant impact on our customer service and CNPS.

A separate trial for the British Army uses AI to streamline and process medical records, reducing processing times for applicants by 30%.

We're also drawing on the expertise of the highest calibre AI engineers and partnering with technology hyperscalers, including the likes of Microsoft ServiceNow, Salesforce and AWS, to develop efficient, ethical, impactful solutions, which now underpin our operations.

How is AI transforming the skills teams need at Capita?

We’re having to think about skills in a completely different way. As part of our workforce planning strategy and the work of my team, we’re looking at how we augment humans with the AI capability we’re bringing in – it’s a huge shift in mindset.

I’m really thinking about the skills the organisation needs in the future. The reality is that AI is transforming how teams operate, automating more repetitive tasks, and simplifying workflows.

It’s allowing us to focus on different skills, and for us, we’re prioritising data literacy. The AI we’re using is only as good as the data that we’ve got. We’re therefore trying to enable teams to interpret that data as fluently as possible. It doesn’t mean we’re training everybody to be data scientists, by any means, but it’s giving anyone the fundamental skills to ask the right questions, and critically analyse AI-generated insights to make better informed decisions.

We’re also looking at the behavioural skills that go alongside that, creating curiosity and an adaptive learning mindset. For instance, we need higher levels of emotional intelligence than before to help with critical thinking and problem-solving.

One way Capita is taking action has been launching the Data and AI Academy. Can you tell us how that idea came about and the goals of the programme?

The Data and AI Academy has been fundamental to us shifting the dial. The need came from a multitude of different skills we were looking to develop, particularly around technical proficiency.

For our employees, it’s about understanding the benefits of AI, the basics around data science and machine learning, as well as AI literacy. Ethical considerations and the responsible use of AI are also massively important.

We can’t underestimate AI's impact on frontline colleagues, so we’re focussing on adaptability: giving individuals the skills to be curious and continue to learn. We want our employees to make that human judgement and be creative for the parts that AI can’t replicate.

Data management and analysis is another area. We want to ensure everyone understands data governance, security practices, and the data lifecycle.

We’re proud of the programme we’ve built in partnership with Multiverse. We’ve got 86 learners on the AI for Business Value apprenticeship, and that's had a significant impact on our business.

I’m also incredibly proud of the materials we’ve built together for colleagues who sit out of the Levy-funded options. It’s important we’re developing AI literacy right across the business.

What made you decide to work with Multiverse?

The reason we chose Multiverse was their ability to demonstrate thought leadership in the AI space. We felt that out of all of the providers that we have worked with, or we went through a procurement exercise with, Multiverse was able to demonstrate the link to the actual business benefit.

Multiverse took the time to understand the transformation and change journey that Capita is on, and build something that was appropriate and meaningful to our employees.

The flexibility that Multiverse has given us on content and delivery styles for different audiences, from lower levels to leadership, has been fantastic, and we've seen a huge impact from that.

The biggest thing is true partnership. It's listening, it's understanding each other and building something that's successful together.

What’s the biggest success you’ve seen from the AI Academy? And what are you proudest of so far?

I’m proud we’ve got people talking about AI and the impact it can have while dispelling some of the myths.

It’s been lovely to do some internal storytelling around people's success on the programme. We often do things like fireside chats where individuals share their proof of concepts. One apprentice recently shared the impact of manual processing changes they’d made within back-office operations. Hearing somebody bring it to life and talk with such fluency around their AI solutions was fantastic.

I’m also hugely proud of our Microsoft 365 Copilot rollout, which is happening across the business. Using the AI for Business Value programme, we’re integrating our internal learning alongside how we’re developing Copilot's impact on our business.

How are employees responding to AI-driven changes in workforce development and skills programmes?

The business has undergone a huge transformation, and naturally, there has been a lot of scepticism about AI replacing human interaction. What this programme has done is demonstrate the advantages that you can have with AI. Our employees are now much more curious – the programme has made them keen to be involved and learn more.

Where there was maybe a fear of job displacement or reluctance to change previously, we’re finding that people are embracing AI.

Learners on the apprenticeship sharing their stories and successes has been fantastic – it’s bringing more people to the table and making them want to be part of the journey. We’re now seeing the knock-on effects where we’ve got people breaking down the door to be part of the next cohorts – it's exactly the success we wanted to get.

Let’s talk strategy. How does workforce transformation in AI support Capita’s broader strategic goals?

A big part of my role at the moment is leading our cultural transformation globally, and emphasising AI's ethical and responsible use across the business. It’s part of our Better Company pillar, which ladders up to our Unlocking Value Together strategy.

We have to align our cultural transformation with AI, so we can drive operational efficiencies, improve governance, and create better skills development to support our tech-enabled culture and future.

We're also refreshing our values at the moment, which I’m leading. It’s been fantastic hearing people so energised in focus groups about the opportunity that AI and data presents, and the opportunity to think about their roles in a different way – less transactional, and more creative and problem solving work.

What’s the biggest hurdle you’ve had so far on that journey, and how have you overcome it?

Navigating budget constraints. We've had to be as creative as ever to help individuals through that change journey, but also to give them the skills they need for the future.

So we've been repurposing a lot of our content – and challenging the art of the possible, utilising AI ourselves internally to create better materials and content.

Without our partners investing time to understand some of those challenges and be on that journey with us, it wouldn't have been such a success. So we’re grateful for the support Multiverse has given us.

Do you have a piece of advice that you’d share with other leaders looking to embark on a similar journey?

Don’t underestimate the change journey. For us, it’s a multi-year strategy – and not something that will happen overnight. We’re introducing AI and continuous improvement initiatives to change employees’ perceptions and drive teams to work together differently over time. But, it’s required strong leadership in that process.

We’re investing lots of time with our senior leadership team to help develop their skills. We want our leaders to become real advocates for changing workforce planning and viewing career pathways differently.

To build a truly augmented workforce, you must make sure all members of the organisation – at all career levels – are equipped with the right skills and tech. It's simple things. Make sure they've got the right equipment, they've got the right tools, but then to allow them to trial things and have a safer space to fail.

And finally, collaborate in strong partnerships. That’s the biggest element for me that’s been successful.

When you look at the year ahead, what are the trends shaping your role, and what are you doing to prepare?

I’m super excited about 2025. It will be keeping up with the rapid pace of change now – things are moving and accelerating faster than ever before. We’re using our budget as creatively as possible to upskill people to get ahead of that change.

Our business is hugely ambitious for its transformation with AI, and what we’re doing for our clients and customers. I can’t let our people down in giving them the skills to deliver what we’re expecting.

I’m also thinking about AI-driven learning experiences. We should practise what we preach and focus on social and collaborative learning to help individuals accelerate their growth. So we will be focused on upskilling and reskilling.

We all talk about the future of work, but do we understand what the future of work looks like in enough detail? We’re putting a lot of focus into that.

A practical challenge for me is ensuring that our remote workforce are still feeling part of that change journey, and adapting to our generational workforce and the differences that brings, as well.

One principle we have at Multiverse is that learning should be available for everyone at every age, and every stage. How is Capita considering this across the generational workforce?

Having five generations in the workplace is hugely exciting, but it brings lots of differences and lots of change. Multiverse has challenged our thinking around making sure that we have learning available to all different generations. Some Capita employees have been with us for a long time, and their roles are changing.

I’m sure that in some organisations those skills would be written off. Instead, it’s about looking early enough to ensure we are reskilling and upskilling. Individuals have got so much capability to do different things. We just need to make sure that we're challenging them in the right way, and giving them accessible, digestible content that’s relevant to their role.

I don’t think any inward learning team can do this on their own. Having truly great partnerships where you understand each other, you trust each other, and you can bring in the experts to fill gaps for you works wonders.

National Apprenticeship Week is coming up. How do you perceive the importance of apprenticeships at Capita?

On a personal level, apprenticeships have really supported me. They helped me at the start of my career, and I've now got a Master's funded through the Levy too.

Apprenticeships give fantastic opportunities to school leavers, but they are also an incredible mechanism for upskilling and reskilling. That's where we’ve tried to dispel myths at Capita – we’ve had over 700 learners go through apprenticeship programmes in the last couple of years. It's fantastic to see skills development in management, leadership, data and AI, where we're seeing huge impact and change.

The Levy allows us to partner and think about things in a slightly different way, using it as a mechanism to upskill our workforce. I’d encourage other organisations to think a little bit more outside the box about how you can use some of the apprenticeship standards that are out there to add business value.

So I will always continue to advocate for apprenticeships. It's hugely exciting to see how they develop and change individuals.

And finally, let’s end on a fun one… in an ideal world, what’s the one dream task you’d like AI to do for you?

I’d love it to manage my teenagers’ emotions for me! But joking aside, for me it would be to create a continuous learning culture of growth and curiosity. I’d love it if AI had a magic way to consistently embed that spirit of constant learning and growth into individuals and across the business.

It’s maturing and it's learning at such a rapid rate. Who knows what AI will do in the future?

And if 2024 was about experimentation with generative AI (Gen AI), 2025 is about proving value for the bottom line as leaders seek to understand the ROI of AI.

You’ll be hard-pressed to find any 2025 trends or predictions without a mention of AI – so we've dedicated this whole article to three AI trends shaped by the skills agenda.

Trend 1: Upskilling to address an AI talent shortage

The roles of AI engineer, data governance manager and AI researcher all feature in the top 10 fastest-growing jobs in the UK, according to LinkedIn’s 2025 ‘Jobs on the Rise’ research.

A tightening labour market for in-demand AI and data skills will force leaders to consider their options.

The same study found that 45% of UK HR professionals feel their company doesn’t have a clear view of the skills it will need in the coming years. Responding quickly to new skills gaps will be a crucial challenge for people teams.

Yet, the answer may already sit within their four walls, with an opportunity to upskill and create new career paths for existing employees.

The appetite from staff is there: our ROI of AI research found that 83% of workers think AI skills will help them to drive more value for their employer in the next 12 months.

With AI on the agenda, leaders can capitalise on this appetite to learn new skills, while making cost efficiencies through employee upskilling.

AI upskilling is the best place to start – explore how to unleash productivity and make AI your competitive advantage.

Trend 2: Agentic AI experimentation on the rise

Agentic AI has been dubbed as the ‘new frontier in generative AI’ by PwC and called out by Gartner as one of its Strategic Technology Trends for 2025.

In essence, this is where GenAI is used to create ‘intelligent agents’ which can make automated (or semi-automated) decisions on their own. Uses are emerging in trend analysis, resource allocation and real-time problem-solving.

With workers spending an average of 14.3 hours a week on data tasks – according to our Skills Intelligence report – there’s a clear case for AI agents to help boost productivity by tackling data-intensive jobs when guided by a human.

While this is the new frontier, it will be early adopters who have the right skills, data governance, and policies in place to push forward with experimental use cases in 2025.

We will see ‘customer service AI agents’ becoming more commonplace, but full-scale adoption of agentic AI is still a while away.

In 2025, expect proof of concepts to be a priority – and for those early adopters to move quickly.

Trend 3: Policy and regulation aims to keep pace with AI

In the UK, the Government launched its AI Opportunities Action Plan to push forward AI adoption and deploy AI across the public sector.

In January, it backed a report of 50 recommendations on how the country can best use AI, written by tech entrepreneur Matt Clifford.

Closing the national skills gap is highlighted as crucial for the UK to become an "AI superpower."

Meanwhile, the incoming EU AI Act will apply to any AI system used inside the EU. The legislation seeks to protect individuals and encourage investment, as well as put a welcome emphasis on AI literacy and skills development.

Businesses globally have found it a challenge to keep pace with the rate of technological advancement, due to a lack of workforce skills. In the UK and Europe at least — both these initiatives will provide additional structure for leaders with their long-term approach to AI.