Agile Mindset: The Key to Thriving in the AI‑Driven Era

There is no business, organisation, team or individual that won’t be impacted by AI. The shift has already started as people use ChatGPT to boost their own productivity at work. Software developers use AI coding agents to produce code faster. Companies build AI agents to redesign and streamline their business processes as we speak.

Despite all the hype, many organisations will struggle with the true adoption of AI. Making the most out of new technology also needs a mindset and culture shift.

Embracing agile thinking will give you a headstart.

AI enforces the upskilling of people

In the rapidly changing environment powered by AI, a continuous learning mindset is not an option; it’s a must.

If you, as a leader, have been happy with people taking 1-2 training courses per year from the company’s learning catalogue, it’s better to start thinking about how to lead organisational learning and development in the new situation.

Studies show that roughly 8-15% of people’s time must be spent just to keep up with the pace of change. This equals roughly one day every two weeks. If you want to be a major player in a technology product domain, you may need to spend up to 20% of your time learning new skills on average.

The technology edge will always be commoditised

If you go back far enough in time, you know that major technological breakthroughs will get commoditised. It happened to electricity and the internet. It happens to AI much faster, as everyone globally can access the same large language models and tools the same day.

When technology like AI becomes more available and accessible, incumbent businesses are threatened by disruption. Businesses can feel secure and continue operating as if nothing has happened. They only see that new technology is a way to improve productivity and save costs.

Nimble players with fresh ideas and thinking can disrupt entire industries. They have no business to protect, and they can augment new technology to move into underserved areas of business.

When everyone has access to the same tools and technology, something else becomes the differentiator.

Can we benefit from AI-powered individuals and systems

The Theory of Constraints suggests that bottlenecks will determine the speed of flow. If we make one part of the system faster, a new bottleneck will appear somewhere else.

The speed of product design, coding and testing has always been the bottleneck in product delivery. With AI tools, you can usually increase delivery speed by 20-30%, and perhaps more.

While there is a good chance that delivery is no longer a bottleneck, it moves somewhere else. Perhaps the way we make product or funding decisions slows us down. Perhaps customers are happy getting the features they have asked for, but we also build features with low quality or low adoption rates. We might generate a massive amount of technical debt while delivering faster. The outcomes we hope to achieve from adopting AI might still be lagging.

The point is to continuously explore and study the value chain as a whole and optimise customer and business value. Methods like Value Stream Mapping can help identify such issues and emerging bottlenecks.

Essential skills in the AI era 2025-2030

The World Economic Forum (WEF) stated at the beginning of 2025 that employers expect 39% of workers’ core skills to change by 2030.

“… in the next five years, technological skills are projected to grow in importance more rapidly than any other type of skills. Among these, AI and big data top the list as the fastest-growing skills, followed closely by networks, cybersecurity and technological literacy. Complementing these technological skills, creative thinking and two socio-emotional attitudes – resilience, flexibility, and agility, along with curiosity and lifelong learning – are also seen as rising in importance.”

Understandably, tech skills like AI are the bleeding edge of learning and development. Hence, training and learning take up most of the time and attention.

Just learning new tech is not enough

Using AI tools and building optimised workflows with AI Agents does not automatically produce winning products, services and businesses. AI can augment the creation of better products and systems, but humans remain the primary force in generating insights and value for their customers and society. The WEF 2025 report also highlighted important complementary human skills like creativity, resilience, flexibility, agility, analytical and systems thinking as of great importance when adopting new technology. This is where agile values and principles come into play. Agile teams and organisations that already encourage teams to take calculated risks, explore, experiment, and bounce back from setbacks will likely be successful in the era of technological breakthroughs.

Agile is a way to think about what matters

Often, people think agile is about following a process or framework, such as Scrum or SAFe. But in fact, it’s a mindset and a thinking tool. Scrum and SAFe are primarily about routines and execution, and they may not be feasible in all contexts.

New technologies challenge our routines and ways of working. What we used to do in the past will no longer always work.

Our purpose, values, and mindsets last longer and change less often. I find that agile principles remain clear, valid, and actionable.

Principles like continuous learning and improvement, trust, working together with customers, conversation, collaboration, frequent delivery, aim for simplicity, and self-organisation – they are irreplaceable. They still hold true also in the era of AI.

The more uncertain the outlook is, the more agility we need. Processes and routines should evolve instead.

Tech adoption and culture shift should go hand in hand

AI will make the culture and organisational efficiency more visible. While AI improves productivity in one area, new bottlenecks may emerge in another. To achieve more than just marginal gains in productivity and customer satisfaction, we need a holistic approach rather than local optimisations.

AI adoption does not happen without a shift in culture and the way we think. Agile organisations are well equipped for change as they have already embraced responding to change.