AI currently has a lot of potential, but no textbook guarantees success. Adoption cycles are evolving rapidly, and companies must implement them successfully to leverage the competitive advantage that AI will inevitably deliver.
There is a lot of pressure on CEOs to have the knowledge and vision to enable their companies to successfully integrate AI. However, this can become even more complicated as few of them have technical experience.
The delegation dilemma
Naturally, CEOs are tempted to delegate the responsibility of implementing AI to the CTO, CIO or CISO. Because in most companies it is the managers who have the technical knowledge. However, the shift in responsibility implicitly assumes that AI is not a key strategic asset for the company.
As tempting as it may be to delegate responsibility, the fact is that AI is too important not to be the responsibility of the CEO. Just as they take personal responsibility for M&A strategy, brand positioning or market expansion, AI’s impact on the future of business is too great to be delegated entirely to engineering teams.
To be a modern and effective CEO, you don’t need to be an expert software developer. However, understanding how and why AI drives innovation is useful in creating the cultural environment necessary for it to flourish.
The mirage of artificial intelligence
Too often, CEOs think they know AI because they use ChatGPT for their daily tasks. They see immediate productivity and improved insights and naturally want to translate this into rapid innovation and cost savings for their business.
However, it is necessary to understand that enterprise AI is fundamentally different. Integrating it into workflows will take time, but over time it can have a greater transformational impact than anyone could reasonably imagine.
The path to true innovation will not be linear and the return on investment will not be immediate. This means that business leaders must also adapt to a new way of measuring value.
CEOs who approve AI investments and then ask the CTO for a quick return on investment are missing the point. In most cases, companies are still experimenting with AI; This is completely understandable. This is not a plug and play feature, it is a feature that needs to be tested and refined over time to deliver value.
Looking for immediate returns will not yield the best results. Progressive leaders will support and fund experimentation, knowing that the path to innovation is longer and more behavioral than other technologies.
Let’s take the example of cloud computing. With cloud adoption, CEOs had the luxury of delegating implementation to the CTO and quickly demonstrating whether it worked.
The AI revolution is fundamentally different. While the cloud can bring immediate cost savings and scalability benefits, AI’s greatest value lies in embedding intelligence into core processes, products, and customer experiences—a change that happens over years, not quarters.
CEOs who understand what developers do and have experience developing software are much better equipped to resist chasing immediate profits and losses.
You understand the iterative nature of building AI-based systems, where experiments fail, models change, and success comes from small victories that add up over time.
Therefore, they are more likely to adopt deeper and more advanced AI integration in the medium and long term. This is where the competitive advantage lies, and not the rush to introduce a standardized AI tool that is currently in vogue.
Why it is important to work with technology
The closer CEOs get to technology and its applications, the better they can think more broadly. By understanding AI’s limitations and opportunities on a practical level, they can make more informed strategic decisions for the business.
For example, a CEO who has taken the time to quickly understand design, data challenges, or model refinement will be less swayed by hype and more likely to invest in areas that will have a lasting impact.
On the other hand, CEOs who consider AI only as part of the IT budget risk missing the opportunity to rethink business models, redefine customer value and open entirely new markets.
Leaders in the AI era
CEOs don’t necessarily need to start coding on the weekend. But just as industrial revolution leaders benefited from understanding manufacturing processes, leaders in the AI era will benefit from understanding software development.
Even a basic understanding of how developers build, test and deploy AI-based systems will give CEOs an edge in the decision-making that will determine the winners in this space, as they will be better positioned to actually drive AI innovation within their organizations.
CEOs leading the AI race will resist the idea of immediate returns, embrace the iterative nature of implementation, and invest for the long term. And most importantly, they will close the gap between technology and strategy, not by becoming developers themselves, but by having enough knowledge to lead with confidence.