Employers

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.

Prime Minster Keir Starmer wants to “unleash AI” - promising to drive adoption and deploy AI widely across the public sector, from reducing admin for teachers to assessment and diagnosis in the NHS.

What will this mean in practice for employers? In this article we’ll explore the AI Opportunities Action Plan and what this means for the skills agenda in the UK.

What’s included in the AI Opportunities Action plan?

The plan was commissioned by the Government and developed by tech entrepreneur Matt Clifford. It includes 50 recommendations, with the goal of boosting economic growth and improving people's everyday lives by supercharging AI adoption.

Improving living standards and transforming public services are called out as key ambitions of the plan – which is made up of three pillars:

1. Lay the foundations to enable AI: including the development of ‘AI Growth Zones’, the creation of a National Data Library (unlocking data sets to enable training of new models), as well as training, retaining and attracting talent.
2. Change lives by embracing AI: pushing public sector adoption by piloting and scaling AI products and services, while encouraging the same in the private sector.
3. Secure our future with homegrown AI: ensuring the UK has national champions through a new unit, UK Sovereign AI.

“In the coming years, there is barely an aspect of our society that will remain untouched by this force of change,” said Prime Minster Keir Starmer, in part of the government’s response to the recommendations, which sets out how the government will take forward the 50 recommendations included in the plan.

In practice, it’s hoped AI will enable public sector workers to spend less time on admin and more on delivering services. The opportunity for public benefit is huge: ranging from automated pothole inspection to faster cancer diagnosis.

The Prime Minister has now tasked his cabinet to make AI adoption a top priority for their Departments.

The Multiverse take: AI tools are only as powerful as the humans that wield them

The focus on skills and talent in the action plan is welcome – AI adoption must start with skills.

Here’s what Euan Blair, Founder and CEO of Multiverse, said following the announcement:

“Being first to mass adoption is just as important as being first to innovation. We may have missed the first-mover advantage on LLMs and data centres, but it’s encouraging to see the UK Government recognises its other unique opportunity: to be first to implement AI at scale.

“None of the AI action plan can happen without a substantial investment in skills, since AI tools are only as powerful as the humans who wield them.”

Multiverse engages regularly with policymakers and will offer advice as the recommendations are taken forward.

What will happen next?

The plan sets out how the country can train, attract and retain the next generation of AI scientists and founders in a set of recommendations. These include:

• Accurately assessing the size of the national skills gap, including AI and digital skills, by Spring 2025
• Setting out how the UK will attract highly skilled AI workers from abroad in the Industrial Strategy, by Summer 2025
• Ensuring the lifelong skills programme is ready for AI by assessing the importance of digital and AI skills in the curriculum, by Autumn 2025
• Establishing headhunting capability to bring top AI talent to the UK, by Autumn 2025
• Increasing the diversity of the talent pool with a focus on improving gender balance, starting at school level, by Autumn 2026
• Expanding education pathways into AI, by Autumn 2026
• Launching an undergraduate and master’s AI scholarship programme, by Autumn 2026
• Expanding the Turing AI Fellowships offer, by Autumn 2026
• Increasing the number of AI graduates and teach industry-relevant skills, such as AI-related degrees in Higher Education, by Autumn 2027

What should employers do on AI skills?

Considering 51% of workers have received less than five hours of AI training – according to our ROI of AI report, there is a clear opportunity for employers to upskill their workforce on AI.

Equipping people with the skills and confidence to use AI will spur further growth - as workers start to see how the technology can reshape their day-to-day.

For leaders wanting to bring AI into their company, understanding skills gaps is the first port of call.

Prime Minster Keir Starmer wants to “unleash AI” - promising to drive adoption and deploy AI widely across the public sector, from reducing admin for teachers to assessment and diagnosis in the NHS.

What will this mean in practice for employers? In this article we’ll explore the AI Opportunities Action Plan and what this means for the skills agenda in the UK.

What’s included in the AI Opportunities Action plan?

The plan was commissioned by the Government and developed by tech entrepreneur Matt Clifford. It includes 50 recommendations, with the goal of boosting economic growth and improving people's everyday lives by supercharging AI adoption.

Improving living standards and transforming public services are called out as key ambitions of the plan – which is made up of three pillars:

1. Lay the foundations to enable AI: including the development of ‘AI Growth Zones’, the creation of a National Data Library (unlocking data sets to enable training of new models), as well as training, retaining and attracting talent.
2. Change lives by embracing AI: pushing public sector adoption by piloting and scaling AI products and services, while encouraging the same in the private sector.
3. Secure our future with homegrown AI: ensuring the UK has national champions through a new unit, UK Sovereign AI.

“In the coming years, there is barely an aspect of our society that will remain untouched by this force of change,” said Prime Minster Keir Starmer, in part of the government’s response to the recommendations, which sets out how the government will take forward the 50 recommendations included in the plan.

In practice, it’s hoped AI will enable public sector workers to spend less time on admin and more on delivering services. The opportunity for public benefit is huge: ranging from automated pothole inspection to faster cancer diagnosis.

The Prime Minister has now tasked his cabinet to make AI adoption a top priority for their Departments.

The Multiverse take: AI tools are only as powerful as the humans that wield them

The focus on skills and talent in the action plan is welcome – AI adoption must start with skills.

Here’s what Euan Blair, Founder and CEO of Multiverse, said following the announcement:

“Being first to mass adoption is just as important as being first to innovation. We may have missed the first-mover advantage on LLMs and data centres, but it’s encouraging to see the UK Government recognises its other unique opportunity: to be first to implement AI at scale.

“None of the AI action plan can happen without a substantial investment in skills, since AI tools are only as powerful as the humans who wield them.”

Multiverse engages regularly with policymakers and will offer advice as the recommendations are taken forward.

What will happen next?

The plan sets out how the country can train, attract and retain the next generation of AI scientists and founders in a set of recommendations. These include:

• Accurately assessing the size of the national skills gap, including AI and digital skills, by Spring 2025
• Setting out how the UK will attract highly skilled AI workers from abroad in the Industrial Strategy, by Summer 2025
• Ensuring the lifelong skills programme is ready for AI by assessing the importance of digital and AI skills in the curriculum, by Autumn 2025
• Establishing headhunting capability to bring top AI talent to the UK, by Autumn 2025
• Increasing the diversity of the talent pool with a focus on improving gender balance, starting at school level, by Autumn 2026
• Expanding education pathways into AI, by Autumn 2026
• Launching an undergraduate and master’s AI scholarship programme, by Autumn 2026
• Expanding the Turing AI Fellowships offer, by Autumn 2026
• Increasing the number of AI graduates and teach industry-relevant skills, such as AI-related degrees in Higher Education, by Autumn 2027

What should employers do on AI skills?

Considering 51% of workers have received less than five hours of AI training – according to our ROI of AI report, there is a clear opportunity for employers to upskill their workforce on AI.

Equipping people with the skills and confidence to use AI will spur further growth - as workers start to see how the technology can reshape their day-to-day.

For leaders wanting to bring AI into their company, understanding skills gaps is the first port of call.

By definition: workforce planning aligns people with current and future business needs, through analysing, forecasting, and mapping workforce supply and demand.

The purpose of workforce planning is to identify current or emerging skills gaps, prepare for future talent needs, and help manage under or over-resourcing.

In this article, we’ll explore everything you need to know about workforce planning, and how to use it to build a future-proof business.

Benefits of workforce planning

There are many benefits to strategic workforce planning, including:

• Aligning your people strategy with your business goals: Ensuring the right people – with the right skills – are in place to support the company’s goals and strategy.
• Preparing for the future: By anticipating workforce challenges and trends, adapting to changes in the market, and developing succession planning.
• Maintaining cost and resource efficiencies: By investing strategically in hiring and training to ensure each team and department has the right level of resource.
• Making data-driven decisions: Using data to make informed choices on talent and training programmes.

The importance of workforce planning today

Businesses will fall behind if they don’t have the right skills in place. Workforce planning is a means to address this challenge – let’s explore the trends reinforcing its importance.

Many leaders are looking at how to future-proof their workforce – with workforce planning one way to identify and tackle AI skills gaps. More than two thirds of leaders (69%) feel their organisation will need different skills to stay competitive by 2030, according to Multiverse. Taking this a step further, a study from IBM found that 40% of workers will have to reskill in the next three years due to AI.

Workforce planning can also be used to address productivity blockers, by mapping out skills gaps and creating a plan to close them. In a Multiverse study, we found an estimated 25 days of productivity are lost from each employee due to data skills gaps, every year.

High employee churn and lower engagement are additional challenges: one study found 90% of UK employees are disengaged from their job. Skill mismatches are one cause – meaning some employees feel their abilities are underutilised or don't align with their current roles.

In response, workforce planning can improve happiness and engagement. It places employees on tasks and projects that are a better fit for their skillset and desired development pathway – and are therefore more fulfilling.

How workforce planning can close skills gaps

The AI era is fuelling a surge in new roles – AI job postings are growing 3.6 times faster than all jobs in the UK, according to PWC’s 2024 AI Jobs Barometer. It puts AI skills high in demand, creating a tight labour market.

For leaders looking to build the right AI skills within their workforce, upskilling existing employees talent may provide a faster, more cost-efficient method than external hiring.

And the appetite from employees is there: 83% of workers think developing their AI skills will help them to drive more value for their employer in the next 12 months.

Workforce planning process – how to do it

The workforce planning process generally follows these steps in a continuous feedback loop:

Workforce planning in a 7-step cycle:

Workforce planning tools and techniques

Now let’s explore how to approach tools and techniques for workforce planning.

The ‘five Rs’ framework is commonly used to align a businesses’ workforce to its goals: ensuring the organisation has the Right People, Right Skills, and Right Roles, at the Right Time, and the Right Cost.

Building on that foundation, real-time monitoring tools can be used to assess productivity, attendance, and engagement levels of employees. Companies can use skills intelligence tools to quickly assess workforce skills and capabilities (like AI), and use this data to inform Learning and Development strategies.

For example, HR teams may decide to build in-demand skills within its existing workforce while flexibly using contract workers for short-term needs – using a model that balances cost, quality, and agility.

Get started with strategic workforce planning

As the era of AI continues to heat up, so will the pressure to find and plan to have the right talent in place. Strategic workforce planning can help you spot what’s needed for success today, while being ready for the challenges of tomorrow.

HR and L&D teams can use a skills inventory as a tool to identify skill gaps, simplify talent management, and support strategic workforce planning.

Crucially, a skills inventory reveals to leaders the specific capabilities that need to be developed to hit company goals.

In this article, we’ll explore everything you need to know about a skills inventory, how to build one, and an example of how one company used a skills analysis to improve efficiency on data tasks.

What is the purpose of a skills inventory?

There are three main reasons for developing a skills inventory:

1. Identifying skills gaps which could be holding you back from growth. A skills inventory helps to quantify the scale of the challenge and the action you need to take.
2. Informing your learning and development strategy by pinpointing the areas that need the most focus. It also supports the creation of tailored employee development plans that support the overall business goals.
3. Creating new opportunities for employees: As well as identifying the skills that employees need to build, a skills inventory can also uncover hidden or underused talent in your workforce – allowing you to open up new upwards or sideways progression pathways for individuals.

What is the difference between a skills inventory and a skills matrix?

Both of these tools can be used to address skills gaps and support your workforce transformation strategy. However, they have key differences:

• A skills inventory is a dataset of all employee skills across a whole organisation.
• A skills matrix focuses on specific skills relevant to individual roles or departments, and includes the scoring captured in the evaluation process.

How to create a skills inventory in 5 steps

Now we understand what a skills inventory is for, let’s look at how to build one.

1) Establish the business goals you want to achieve

Start by setting out the overarching goals and how you hope skills can help you achieve them. One way to do this is by writing a problem statement that explains the challenge you want to overcome. The statement should factor in:

• What is the problem blocking you from?
• What value would solving the problem unlock?
• How will that challenge change if unresolved in the next 12 to 18 months
• How can skills help you reach the goal, or goals, that you want to achieve?

2) Identify the skills needed to hit your goals

To answer your problem statement, next consider what capabilities your workforce will need to achieve your goal outcome.

Group these into skill sets and organise into broader categories, such as soft skills, technical skills, and leadership skills. Qualifications and certifications can also be factored into a skills inventory.

Find out more on the differences between soft skills gaps and technical skills gaps in our guide: ‘What is a skills gap?

3) Conduct an employee skills assessment

Decide on the best way to test or assess the skills of your workforce. Different methods include employee self-assessment (either manually, or using a dedicated skills intelligence tool), skills tests, and performance reviews.

Next, rate proficiency for each skill using a uniform scale (such as 1 to 5) to establish a consistent benchmark.

If you choose to interview one-to-one or if employees are self-evaluating, here are some questions to include:

• What skills do you have that the company could use more effectively?
• How do you rate your proficiency on [skill] out of five?
• Where do you want to focus your personal development in the next six months?

4) Map the results in a skills matrix

The evaluation results can be captured in a skills matrix at an employee, team, or department level.

The tool gives managers and leaders a view of proficiency levels of the desired skills, clearly showing strengths and skills gaps.

Discover our guide: What is a skills matrix?

5) Regularly update your inventory

With skills gaps identified, update your inventory data and treat it like a live document – for example, making updates when an employee training programme has finished and there’s new self-assessment data from employees to input. This is an opportunity to measure the programme’s impact, calculate ROI on employee training and inform your next steps.

Another check-in point is when there are changes and updates to the business strategy. Always think: how will this impact the roadmap of skills you need? Make sure any new requirements are captured in your skills inventory.

Skills inventory example: EDF Energy

Let’s look at how EDF Energy was able to identify their workforce skills gaps and create a skills inventory, with support from Multiverse.

A Multiverse skills analysis assessed EDF employees who use data daily – and it found they were spending 19.9 hours a week on data tasks.

The analysis mapped employee skill levels in areas like predictive modelling, engineering data, producing visualisations, managing spreadsheets and analysing data.

The exercise revealed 50% in potential time savings which could be achieved through data upskilling.

To capitalise on these efficiency gains, EDF launched a Multiverse Data Academy programme, enrolling staff on apprenticeships to build data skills.

Use a skills inventory to close skills gaps

A regularly updated skills inventory supports strategic workforce planning.

By following these steps, leaders can get the right people working on the right projects, faster.

Specific skill gaps can be targeted through learning and development programmes. And leaders can identify the skills needed to stay competitive and ahead of the curve.

Unblocking digital transformation can improve operations in public services – and ultimately better serve the taxpayer. So what can leaders do to drive their digital transformation approach forward?

We recently held a virtual roundtable with representatives from local authorities and the NHS to discuss methods for unlocking success in digital transformation.

We heard from Sarah Wilkins, CDIO for North London NHS Foundation Trust, Tony Clements, CEO at Ealing Council, and Euan Blair, Founder & CEO at Multiverse, on how data and AI strategies can help overcome digital challenges and deliver a seamless service to local communities.

If you’re short on time, these are our five takeaways from the session:

1. Collaboration creates better citizen outcomes

Collaboration is critical for NHS Trusts and local government. It helps continue service between health and social care, resulting in the best patient outcomes.

Tony already has ideas about how to bridge the data divide using AI. He said: “We're in a trial cohort at the moment of designing a generative AI tool that takes social workers’ notes and relational data, turning them into formats that work for clinicians.”

He hopes to remove technology boundaries between the NHS and councils, creating a robust and personalised approach to care.

Sarah told us how the Trust supports collaboration by participating in schemes like the London Care Record. The system shares patient data across organisations to support integrated care.

Gradually, greater collaboration helps to bridge professional, cultural and informational gaps between public services – all to provide better outcomes for local communities.

2. Data is most effective when strategically integrated

Public sector bodies have the opportunity to better integrate data into workflows – helping drive greater productivity and improve decision-making.

Sarah explained: “We’re drowning in data, but we weren’t always using it intelligently, to generate the insights that we need.” To develop the skills to use data more strategically, the Trust partnered with Multiverse to start a Digital Academy, funded by the Apprenticeship Levy.

Today, clinical teams can use their caseload management tool, MaST, to identify patients at risk of going into crisis. It helps them allocate resources accordingly and reduce hospital admissions.

Ealing Council is also taking action to improve its digital transformation approach by enrolling 45 employees in a data academy, with the hope of expanding the partnership further.

Tony says the area is ripe for collaboration: “There's a real opportunity to combine NHS and wider local authority data so that we can move away from some of those lag indicators and move towards earlier predictions.” For example, the team has started using predictive analytics to predict which residents might enter into adult social care soon.

3. AI can accelerate productivity and performance

Teams are also integrating AI into workflows to boost productivity in the public sector.

At Ealing Council, teams use a tool called Magic Notes to minimise the administrative workload associated with adult social work. AI also helps to identify the need for practical interventions - if a final assessment doesn’t match the evidence, the system flags discrepancies for Ealing’s social workers to review.

Tony told us: “The more we can get our social workers doing what they do best, which is working in people’s homes on the things that matter to them, the better.”

Despite some initial scepticism, teams now understand that AI can have significant benefits for their own workloads. Sarah told us: “It's about removing that admin burden from clinicians and freeing them up to work to the top of their licence – and do the things that only they can do as clinicians.

“It helps them focus their attention on the caseload that’s most in need, and give those patients better outcomes.”

4. Upskilling is a critical tool for building data literacy

Sarah and Tony both highlighted the critical role of upskilling to build data literacy. Training enables learners to better interpret data and apply it to decision-making around service design.

Alongside formalised learning, Tony stressed the importance of a distributed model for the training and adoption of new data and AI tools. He explained: “I'm not a chief exec that's going to come in with a centralised transformation programme designed in the back room by a bunch of consultants. Our approach is to put tools directly into people's hands and to establish those use cases through practice.”

He explained: “We’ve been experimenting with Microsoft Copilot, with 300 of our staff initially given licences, to use in the ways that they feel best work for their area of business. We’re bringing that together in what we've called our centre of excellence – where staff learn from each other how they’re using the new tool, and then spread that knowledge and skills laterally, as much as top down.”

Euan agreed with the two-pronged approach, accounting for both tech and skills: “If we want to benefit from the huge potential technology offers, we have to train and skill the incumbent workforce. Tech tooling can create huge amounts of value, but only if it's implemented and people understand it.”

5. Buy-in is needed from top to bottom of the org chart

The panel spoke about the importance of building a future-ready workforce and a culture of continuous learning. But to build that foundation, you need buy-in at all seniority levels.

Sarah stressed the importance of bringing end-users along for the journey, demonstrating the value of digital skills and systems. She said: “It really is about empowering all levels of the organisation. It can't just be top down, or you meet resistance.”

Executive sponsorship for change initiatives is essential. As Euan put it: “You need clear sponsorship from the business at the leadership level across technology and data. If it ends up being an HR and L&D effort only, then it often ends up not fully delivering everything it can.”

For Tony, it’s about change leadership and managing a gradual process: “You can't always get enough buy-in. So sometimes, you've just got to take a moment, be conscious that you are probably pushing the organisation a bit further than it's ready for, and then be prepared to pick up the pieces.”

Digital transformation in public services isn’t just about investing in new technology – people and skills are critical to success. To learn how to boost productivity, deliver better outcomes for communities, and create new opportunities through data and AI skills, speak to our specialist team.