This article is based on a talk delivered by Matt Rawlins at the CIPD Festival of Work.
Everyone wants AI skills.
The problem is that almost everyone is looking for them in the same place.
Across every industry, organisations are trying to recruit AI specialists, data experts and digital transformation leaders. The demand is huge, the talent pool is limited and salaries continue to rise.
It's an understandable reaction. AI has the potential to transform the way we work, so hiring someone who already has those skills feels like the quickest route forward.
But after speaking to HR and learning leaders across the UK, I've come to a different conclusion.
If your long-term goal is to build an AI-ready organisation, hiring external experts shouldn't be your first move.
Your first investment should be in the people who already work for you.
The AI skills gap isn't just a recruitment problem
The conversation around AI often starts with recruitment.
"We need AI people."
"We need data people."
"We need someone who understands automation."
But those conversations can distract organisations from a more important question.
What capability are we actually trying to build?
Hiring an AI specialist might solve an immediate resource gap, but it doesn't automatically create an AI-enabled organisation.
Real digital transformation happens when AI becomes part of everyday decision-making across finance, HR, operations, marketing and customer service - not when all the knowledge sits with one individual or an external consultancy.
That's why the organisations making the biggest progress aren't simply buying expertise.
They're building capability across their existing workforce.
Your employees already have the one thing you can't recruit
Technical skills can be developed.
Business knowledge takes years to build.
That's easy to forget when organisations focus solely on recruitment.
An external AI consultant may understand the latest technologies, but they still need to learn your business. They need to understand your processes, your systems, your customers, your culture and the countless operational details that influence how work gets done.
Your existing employees already know all of that.
They know where the bottlenecks are.
They know which reports take half a day to produce.
They know which spreadsheets everyone quietly dreads opening.
They know where time is wasted because they experience those frustrations every single day.
Teaching someone how to use AI is often much quicker than teaching someone how your organisation works.
That's why investing in your own people creates value that extends far beyond the initial learning programme.
Instead of importing capability, you're growing it from within.
The real cost of hiring AI expertise
Recruitment costs are only part of the equation.
When organisations bring in consultants or specialist contractors, they often gain rapid access to knowledge and experience. That's valuable.
But it's also temporary.
Once the project finishes, the consultant leaves.
The knowledge leaves with them.
Six months later, another challenge appears and the organisation finds itself buying expertise all over again.
Upskilling your own workforce creates a very different outcome.
Every employee who develops new AI and digital skills becomes another person capable of spotting opportunities, improving processes and helping colleagues adopt new ways of working.
Capability doesn't disappear when the project ends.
It compounds.
That's one of the biggest advantages of workforce upskilling. Every investment continues delivering value long after the learning itself has finished.
Digital transformation succeeds because of people, not technology
One of the biggest misconceptions I encounter is that digital transformation starts with choosing the right technology.
It doesn't.
Technology is the easy part.
Adoption is where organisations succeed or fail.
The businesses making real progress are creating internal advocates - people who understand both the technology and the practical realities of their department.
I often describe these people as Digital Champions.
They don't have to be developers or technical specialists.
They're simply people who are curious, enthusiastic and willing to explore better ways of working.
Give those people the opportunity to develop their AI skills and they'll often become catalysts for change within their own teams.
Instead of change being imposed from the top down, it spreads through trusted colleagues who understand the day-to-day challenges everyone faces.
That's a far more sustainable model for transformation.
Start by finding the work nobody enjoys
If you're wondering where AI can make the biggest difference, don't start with the technology.
Start with your people.
Ask every team one simple question:
"What's the most repetitive part of your week?"
The answers are usually remarkably similar.
Manual data entry.
Writing routine reports.
Summarising lengthy meetings.
Copying information between systems.
Managing calendars.
Updating trackers.
These aren't high-value activities.
They're simply necessary tasks that consume hours every week.
I sometimes refer to this as the "soul-crushing task audit."
If a task is repetitive, manual and predictable, it's probably a strong candidate for automation.
This exercise does two important things.
First, it quickly identifies where AI can deliver immediate productivity gains.
Second, it helps employees see AI as a practical tool that removes frustration rather than something designed to replace jobs.
That's an important distinction.
Successful AI adoption isn't about replacing people.
It's about allowing people to spend more time on work that genuinely requires human judgement, creativity and collaboration.
The funding may already be there
Another assumption I hear regularly is that developing AI capability will require significant new investment.
For many organisations, that's simply not true.
Apprenticeship funding already provides an opportunity to develop digital, data and AI capability within existing teams.
Unfortunately, many employers still associate apprenticeships with entry-level recruitment or school leavers.
That view is outdated.
Today's apprenticeships support professionals at every stage of their career and cover advanced skills in data, digital technologies and artificial intelligence.
Rather than viewing apprenticeships purely as a recruitment route, organisations should see them for what they've become: one of the most effective ways to futureproof an existing workforce.
AI capability isn't something you buy
The organisations that thrive over the next decade won't necessarily be those with the largest AI budgets.
They'll be the ones that build a workforce confident enough to embrace new technologies, challenge existing ways of working and continually improve how work gets done.
Technology will continue evolving.
New AI tools will emerge.
Job roles will change.
The organisations best prepared for that future won't be those that rely on external expertise every time something changes.
They'll be the ones that have invested in their people.
Because AI capability isn't something you buy.
It's something you build.
And the best place to start building it is with the people who already know your organisation better than anyone else.
Ready to build AI capability from within?
Kaplan's Data and Technology apprenticeships are designed to help organisations develop the digital, data and AI skills they need to thrive.
Whether you're looking to develop future AI Champions, strengthen your data capability or accelerate digital transformation across your organisation, our programmes combine practical learning with immediate workplace impact.
For senior leaders shaping AI strategy, we also offer specialist executive programmes in:
Together, these programmes help organisations build AI capability at every level -from operational teams implementing AI day-to-day through to leaders responsible for strategy, governance and organisational change.
Explore our Data and Technology apprenticeship programmes to discover how you can build lasting AI capability within your workforce.