Successfully integrating AI into your organisation is not just about technology, it’s about people. Discover how leadership, workforce development, and the right approach can drive meaningful adoption and real impact.
Artificial intelligence (AI) offers unprecedented opportunities for organisational innovation, efficiency, and growth. We cannot approach the implementation of AI, or any technology, as a purely technical project. If we do, we are doomed to fail. The key to leveraging AI effectively lies in driving true adoption, where employees have the skills, confidence and support to use AI meaningfully in their work.
But how can we embed a workforce development strategy into AI implementation? How can we support and upskill large groups at speed? And what are the challenges to look out for?
To explore these questions, James Eynon (Propositions Consultant for Capita Workforce Development) sat down with Atika Arshad (AI Capability Development Lead at the Financial Conduct Authority(FCA)), Matt Lowis (AI, Data and Technology Lead for Capita's Performance and Development Team) and Olivia Lori Kay (Director of Performance & Partnering within Capita’s Workforce Development division).
Understanding your people
Adoption is not possible if you do not understand where people are in their AI journey. Reflecting on the FCA’s approach, Atika emphasises the importance of a needs analysis, identifying personas and assessing existing AI adoption, awareness, and readiness.
This involves actively listening to employees, conducting surveys, and organising workshops to assess their comfort levels and knowledge. Recognising the varying degrees of expertise and readiness ensures that organisations can motivate people to learn, provide the right support to the right groups, and create a benchmark to measure adoption success.
Leadership buy-in
Benchmarking AI readiness is not possible without leadership buy-in, so securing a senior sponsor is a must. Matt says that this is exactly what Capita have:
“Capita is in the unique position of having a CEO who is incredibly technology driven and is really driving the use of these tools throughout the organisation to bring business value. If you don't have that sponsorship, it doesn't really go anywhere.”
For Atika and the FCA, leadership buy-in extends beyond sponsorship - leaders must role model good practice: “Are we thinking about upskilling our leaders? Because if they’re not advocating for this, if they’re not confident in using AI, that engagement is not going to be there."
Providing training and support to leaders can help foster a positive attitude towards AI tools, which in turn influences their teams’ willingness to experiment and adopt new technologies.
Bridging the expectation gap
A significant challenge which may arise during any needs analysis is expectations of AI. James highlights how employees may have preconceived (and sometimes misinformed) notions about AI’s capabilities based on external sources. When AI tools do not perform as expected, it can lead to a disconnection and resistance.
A common example is in organisations where there’s a clear Generative AI policy, encouraging employees to try and use it, but without effective support. Some people will expect the tool to do more than it can, and when it does not achieve that, they’re not motivated to use it again. Organisations must communicate the realistic outcomes of the use of AI tools to bridge this gap.
Human skills and sandboxes: Experimentation is key
The adoption of AI technology is not just about technical skills. Matt and Atika both stress that the role of a human working with AI is to be just that - human:
"Although it's an incredibly powerful creative tool, AI shouldn't replace human skills and human creativity and innovation."
"Gen AI will only give you a recommendation, it does not give you an answer. It's up to you and your human skills to take that recommendation and build it into a good answer."
To maximise AI’s potential, organisations need to develop higher cognitive abilities - such as analytical thinking, problem solving, and ethical reasoning. By fostering these skills and encouraging experimentation, organisations can bridge the gaps and optimise the use of AI technologies.
When it comes to practically developing those skills, Matt says that experimentation is key for Capita: “We’ve created our AI, Data and Technology Academy, which is there to provide all our colleagues with exploration around AI. We've set a security ringfence for MS CoPilot, so it's a safe environment to go and play in. But then it's up to colleagues to go in and really experiment and explore with the tool, because the use cases for individual colleagues could be so diverse, it's impossible to create learning for every eventuality”
This underscores the importance of governance and a supportive learning environment, where employees can explore AI’s potential without fear.
It’s not all about AI
When it comes to embedding AI into an organisation, the focus does not need to be on the tool itself. If true adoption is the goal, people need to see AI for what it enables, rather than its mechanics. Olivia discusses an example of an AI coach pilot at Capita, where the focus on testing AI, through the prism of personal development. By integrating AI into daily workflows in a practical, human-centred way, employees naturally adopt AI practices - not as a technology they must learn, but as a creative partner that enhances their productivity.
This subtle but powerful shift in approach makes AI less intimidating and more valuable to individuals and teams.
Turning AI potential into real-world impact
Adopting new AI tools in the workforce is a multifaceted challenge that requires managing expectations, fostering experimentation, empowering leaders, balancing human skills with technology, and considering ethical implications.
For public sector organisations, this is not just a productivity issue – it’s about delivering better outcomes to citizens, making governance more efficient and future-proofing workforces. To achieve this, leaders must take an active role, not just in approving tools, but in championing their responsible and effective use.
The question is no longer whether to adopt AI, but how to do so effectively, ensuring both technological and human readiness.
Successful AI adoption starts with equipping your workforce with the skills and confidence to use it effectively. Contact us today at Learning@Capita.com to find out how we can support this journey or to learn more, listen to the full podcast conversation.
Find out how we can support your learning and development requirements:
James Eynon
Senior Learning Consultant & Leadership Coach
Since 2015, James has led various L&D initiatives, focusing on practical solutions for learning cultures, data impact, reskilling, and leadership. James’ pragmatic approach to both consultancy and facilitation has resulted in the creation of a new workplace culture model, in which hybrid working is an integral part.
