It is not surprising that the implementation of AI tools has quickly become a boardroom topic.
There is a lot of experimentation going on, and companies will soon face more rigorous, proven use cases that will give them a competitive advantage.
So much so that harnessing the power of AI to drive change requires direct sponsorship from the CEO.
Head of Product, AI at JetBrains.
At the moment, AI is bursting with potential, but without a playbook that guarantees success. Adoption cycles are moving quickly and companies must get the implementation right to leverage the competitive advantage that AI will inevitably bring.
There is enormous pressure on CEOs to have the intuition and vision to enable their companies to successfully integrate AI. However, this is arguably made more complicated when you consider that few of them have any technical experience.
The delegation dilemma
Understandably, CEOs are tempted to delegate responsibility for implementing AI to the CTO, CIO or CISO. After all, in most companies these are the leaders with technical expertise. But shifting responsibility implicitly assumes that AI is not a core strategic activity for the enterprise.
As tempting as shifting responsibility may be, the fact remains that AI is too important not to be a CEO’s responsibility. Just as they take personal ownership of the M&A strategy, brand positioning or market expansion, the impact of AI on the future of the business is too great to be passed on entirely to the engineering teams.
To be an effective modern CEO, you don’t necessarily have to be an experienced software developer. However, gaining insight into how and why AI will drive innovation is an advantage in fostering the right cultural environment in which it can thrive.
The AI mirage
Too often, CEOs think they know AI because they use ChatGPT for daily tasks. They see instant productivity and improved insights, and naturally want to translate that into rapid innovation and cost savings for their organization.
But what they need to understand is that enterprise-level AI is fundamentally different. It will take time to integrate into workflows, but over time it can have a more transformative impact than anyone can realistically imagine.
The path to true innovation will not be linear, and the ROI will not be immediate. That means business leaders must also adapt to a new way of measuring value.
CEOs who approve AI investments and then ask the CTO for quick reimbursement are missing the point. In most cases, organizations are still experimenting with AI; that’s completely understandable. It’s not a plug-and-play feature; it is a capability that must be tested and refined over time to deliver value.
Insisting on immediate returns will not yield the best results. Progressive leaders will endorse – and fund – experimentation, knowing that, unlike other technologies, the path to innovation is longer and more behavioral.
Take cloud computing for example. With cloud adoption, CEOs had the luxury of delegating implementation to the CTO and then getting quick proof of whether it had worked.
The AI revolution is fundamentally different. While cloud adoption could provide immediate cost savings and scalability benefits, AI’s greatest value comes from embedding intelligence into core processes, products and customer experiences – a transformation that happens over years, not quarters.
CEOs who understand what developers do and have experience in software development are much better able to resist chasing immediate P&L impact.
They can relate to the iterative nature of building AI-powered systems, where experiments fail, models change, and success comes from making small wins over time.
As a result, they are more likely to champion deeper, more progressive AI integration in the medium to long term. This is where the competitive advantage lies, rather than racing to adopt an off-the-shelf AI tool that is popular at the moment.
Why working with technology matters
The closer CEOs get to the technology and how it is applied, the more broadly they can think. When they understand the limitations and capabilities of AI on a practical level, they can make more informed strategic decisions for the business.
For example, a CEO who has taken the time to understand rapid engineering, data challenges or model refinement is less likely to be swayed by hype and more likely to invest in areas that will have a lasting impact.
On the other hand, CEOs who consider AI merely as part of their IT budget risk missing the opportunity to reinvent business models, redefine customer value and enter entirely new markets.
Leading the way in the AI era
CEOs don’t necessarily have to start coding on the weekend. But just as leaders in the Industrial Revolution benefited from understanding manufacturing processes, leaders in the AI era will benefit from understanding software development.
Even a fundamental understanding of how developers build, test, and deploy AI-powered systems will give CEOs an edge in making the kinds of decisions that will determine the winners in this space – because they will be in a better place to actually sponsor AI innovation in their companies.
The CEOs who will lead the AI race will resist the idea of immediate returns, embrace the iterative nature of implementation, and invest in the long term. And crucially, they will bridge the gap between technology and strategy – not by becoming developers themselves, but by having enough insight to lead with confidence.
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