The Real AI Challenge Isn’t the Tech. It’s the Talent


AI’s biggest challenge isn’t innovation; it’s empowering people with the skills and governance needed for responsible, inclusive adoption.

AI (Artificial Intelligence) Appreciation Day is an opportunity to celebrate progress and reflect on potential. AI’s influence is now undeniable, shaping how we work, solve problems, and think about the future of nearly every industry. But amidst the excitement over new models and billion-pound investments, one core challenge continues to hold back meaningful adoption: the readiness of people, not just the technology.

The hype cycle is familiar. Excitement builds, tools emerge, early adopters race ahead, and the rest scramble to catch up. But unlike other waves of innovation, AI introduces a level of complexity that can’t be resolved with off-the-shelf solutions or surface-level training. As AI continues to evolve, the ability to implement and scale it sustainably depends far more on human capability than on the tools themselves.

From Excitement to Execution: A Widening Skills Gap

In practice, many organisations are struggling to bridge the gap between aspiration and execution. AI pilots may look promising in isolation, but often stall before reaching full deployment. Under the surface, there is a recurring pattern: projects built on shallow understanding, automation tools managed by non-technical users, or code deployed without a grasp of its implications.

These aren’t just teething problems. They reflect a deeper issue in how we approach workforce development for AI. We often hear about an AI “skills gap,” but what we’re really facing is a design problem in how we think about education, access, and inclusion. Too much of the conversation focuses on high-end, specialised roles, when in reality successful adoption depends on a broader, more practical set of skills distributed across the organisation.

The real question isn’t just whether we have data scientists, but whether we have people who can identify valuable use cases, test ideas safely, manage ethical risks, and seamlessly integrate AI into existing workflows.

Building a Workforce That Learns, Adapts, and Evolves

What we’re seeing in many sectors is a growing need for individuals who can navigate ambiguity, work across disciplines, and continuously adapt as AI tools evolve. That doesn’t always mean having a formal background in tech.

Many of the most impactful professionals working with AI today started in non-traditional pathways. They may have learned on the job, come through vocational training, or shifted careers midstream. What they share is curiosity, problem-solving ability, and an understanding of how technology fits into the real-world challenges their teams face.

The importance of practical, hands-on learning can’t be overstated. Theoretical knowledge alone won’t help someone troubleshoot a broken AI workflow or decide whether a process is suitable for automation. We need to empower people across the organisation, not just those with ‘engineer’ in their job title, to use AI confidently and responsibly.

Simplicity Is Not a Strategy

There’s a persistent belief that AI can be “plugged in” to solve complex problems without significant change to people or process. But truly effective AI adoption requires foundational work: rethinking workflows, building robust infrastructure, training teams to spot bias, and embedding responsible governance.

This is not about doing more with less. It’s about doing better with different by reshaping how we define roles, value skills, and build collaboration between human judgment and machine capabilities.

And crucially, that kind of transformation must be inclusive. If AI is to deliver on its promise, it must do so in a way that reflects the diversity of the people it serves. That starts by ensuring people from all backgrounds have access to the tools, training, and opportunities to shape its future.

Rethinking Investment Priorities

Recent government commitments to AI investment, such as the £3.25 billion pledged in the UK, are welcome signals of intent. Initiatives like the TechFirst scheme, which aims to equip a million young people with AI and digital skills, also mark meaningful progress. But the challenge now is sustaining that momentum and ensuring that support extends beyond early headlines and reaches the people and communities who need it most.

Public and private investment must move beyond figures and into long-term, inclusive support for workforce readiness. That means more grassroots training programmes, broader industry partnerships, and more accessible entry points into digital and AI-related careers.

As we reflect on AI Appreciation Day, we should celebrate the progress being made in technology. But we must also stay grounded in the reality that success depends not just on smarter models, but on more confident people.  Because the real value of AI is not in the tools themselves. It’s in the people who understand when those tools are almost right and know what to do next.

By Ash Gawthorp, Chief Technology Officer at Ten10.

Ash is a Co-Founder and the CTO of Ten10, and created the Ten10 Tech Academy programme in 2013. He is passionate about giving people the opportunity to start and develop a career in technology, regardless of background.