In this thought-provoking article, Cambridge Spark CEO Dr. Raoul-Gabriel Urma explores why the most in-demand AI skills go beyond coding, highlighting the critical role of human intelligence in shaping the future of technology.
After speaking with more than 10 AI leaders on my podcast, one thing became clear: it's the combination of technical skills with distinctly human abilities that creates a real competitive advantage.
Ask most CEOs what skills they need to thrive in the AI age, and they’ll point to quantitative skills and technical expertise. They’re not wrong; technical expertise is foundational. But after speaking with more than 10 AI leaders on my podcast, one thing became clear: it’s the combination of technical skills with distinctly human abilities that creates a real competitive advantage.
Think: entrepreneurial mindset, learning agility, critical thinking, data and AI fluency, and systems thinking.
Why do we need these skills now? Because static roles are vanishing. Every job consists of tasks, and AI is automating, augmenting, or dramatically accelerating their completion.
Take software engineers: they can now automate a large part of unit testing, augment code analysis, and generate code far beyond simple boilerplate.
The result? Most jobs need to be re-imagined within the context of AI. That means companies can no longer rely on siloed technical training for specific roles. Instead, they need to cultivate transferable, strategic skills – across the entire organisation.
The good news is that these skills are teachable. Here are the most important skills to prioritise and how to integrate them into your organisation.
1. Entrepreneurial mindset
Professor Howard Stevenson of Harvard Business School defines entrepreneurship as “the pursuit of opportunity beyond the resources you currently control”. I believe that this ability to deliver real value to people, regardless of resource constraints, remains one of the most powerful human skills in an AI-enabled world. It’s this conviction that led me to found Cambridge Spark.
The key is figuring out how to deliver more value with less. Today, “vibe coding” makes this easier than ever before by accelerating entrepreneurial execution and allowing value to be demonstrated to customers much faster.
But even with AI, you still need to understand your customers, align stakeholders, sell ideas, and influence decisions. As Cassandra Vukorep puts it: “Sales, sales, sales. Everybody should learn more about sales.” And Cassandra isn’t just talking about direct sales, she’s also talking about selling ideas, strategies, and priorities to the rest of your organisation.
The best way to integrate this skill? Provide opportunities for collaboration between people from different areas of the business. This could involve data analysts leading product ideation sessions or presenting insights to the C-suite.
2. Learning Agility
In an AI-integrated workplace, one of the most vital skills is learning how to learn. And it’s often completely overlooked. The ability to adapt, unlearn existing practices, and acquire new knowledge quickly is now essential – not just for technical teams but for everyone.
Dave Treat, CTO of Pearson, told me on the podcast that the top trait he looks for in hires is “a love of continuous learning.”
If you want to integrate this skill into your organisation, start by empowering people to understand their individual learning style. With this knowledge, you can provide multiple modalities of learning and create personalised learning paths, which get people where they need to be quicker.
3. Critical thinking
AI is powerful. But it’s not always right. And the risk of blind trust in automated outputs is real. That’s why critical thinking is non-negotiable. Every employee needs to be equipped to question, challenge, and analyse the input and output of AI tools.
Professor Alastair Beresford believes the key is asking the right questions. How has the AI come to that conclusion? Is this data representative? What assumptions are being made? Think of it like teaching maths to kids even though calculators exist: If they don’t understand the process, they can’t spot errors. The same applies to AI. To integrate this skill throughout your organisation, you need to establish a culture of open-mindedness and encourage employees at all levels to challenge processes and outputs.
4. Data & AI fluency
You don’t need to be a data scientist to work effectively with AI – but you do need to understand the underlying fundamentals. AI fluency means knowing what these technologies can do (and what they can’t), where to apply them, and how to use them to enhance your work. Data fluency is just as essential. As Cassandra Vukorep, Chief Data Officer at Lloyds, told me on the podcast: “all employees should understand the importance of data ownership so they can make informed decisions when sharing data.”
To ensure your people (and not just the tech teams) are AI and data fluent, you need to invest in targeted and comprehensive data and AI skills training programmes that include expert-led sessions and practical tasks, like those offered by Cambridge Spark.
5. Systems thinking
AI doesn’t just change tasks – it changes entire workflows and systems. Systems thinking is the ability to see how different parts of an organisation connect and influence each other, rather than viewing them in isolation.
This skill becomes critical with AI because implementations can have ripple effects. Rolling out an AI chatbot might seem like a simple customer service decision, but it affects IT infrastructure, training protocols, product feedback loops, and more. Furthermore, with AI agents, we’re moving beyond simple query-and-answer interactions toward orchestrated networks of agents working together as integrated systems.
If you want to integrate this skill, you need to help your people understand how AI can make the organisation more efficient and effective – at the systems level. That starts by encouraging cross-team collaboration and giving people visibility into how decisions and data flow across the organisation.
Final thoughts
As AI continues to reshape job roles and workflows across every industry, organisations are recognising they have to change. And fast.
At the core of that is the need to upskill your people.
To truly realise the value of your investments in tech and thrive in a competitive market, you must focus on the differentiators: the human skills that enable people to create value in any and every role.