The AI Advantage Will Belong to Leaders Who Know What Questions to Ask 

Jason Sosa works where artificial intelligence becomes an operational, strategic and human challenge. As an AI futurist, technologist and founder, he focuses on agentic AI, enterprise adoption, automation and the risks leaders must understand as intelligent systems become more capable. 

His perspective is shaped by years spent building at the frontier of emerging technology, from AI start-ups to senior technology leadership. That makes his view relevant for organisations trying to separate AI hype from practical value while protecting human judgement, governance and long-term decision-making. 

In this exclusive interview with the Champions Speakers Agency, Jason explains where human judgement remains irreplaceable, why many AI pilots fail to create operational value, and why leaders need a long-term view as AI capability accelerates. 

Question 1. As AI lowers the barrier to domains once protected by specialist language, where does human judgement still create strategic advantage? 

Jason Sosa: We’re entering a time where a lot of the language around medical technology, finance and legal work, which was gatekept for many years, is breaking down. While those words and terms are still necessary to use AI, it does democratise the entire process. 

I can use Claude Code and do things where I would not previously have needed to know what those technical terms mean. But when you think about it, having an understanding of the inner structures of how code works, how finance works or how legal works still matters. Even though they are coded in this language, they are much easier to wield in an AI world when you understand that coded language. 

Human judgement is going to be the ultimate win in a world of AI because, while everyone else is racing from zero to intermediate, you’re already there. If you have intermediate knowledge across many domains, you have an advantage in knowing what questions to ask, rather than simply wanting AI to do it all for you. 

I think we will come to a point when AI will do it all for us. But, for now, being able to direct your own intention means human judgement is going to rely on your ability to string together those words and understand the relationship between seemingly disparate ideas. That is where human judgement has tremendous value in this coming world. 

Question 2. Why do so many AI pilots fail to convert into operational value, and what does that reveal about the gap between technical capability and organisational readiness? 

Jason Sosa: What causes AI pilots to fail often is not technology. It is human. 

From small companies to large corporations, there is a tendency to think you can add a box on the assembly line, sprinkle some AI dust and solve the problem. That is an unfair way to look at how to apply AI. 

When people do not see immediate results, they are quick to say it does not work, the hype is over and we should go back to using an abacus. Of course, we are not going to do that. But a lot of people realise that many of these AI tools are technical, and the humans who have to participate in them need to understand what these tools are and what the capabilities of these machines now enable. 

Often, the business side only understands the business case, and the developers only understand the technical side. There is a massive chasm between what is possible and what is going to add value. That is where I see the biggest gap. 

It is also a mindset issue. Too often, it is seen as one and done: we did AI last quarter, now let’s move on. It is more of a seed-and-grow mindset. That is the most helpful approach for any organisation that wants to participate in this. 

It is also about how you implement AI as an organisational transformation. How do you shift people? That is always going to be the difficult part of implementing AI in any organisation, especially when shareholder interests are moving you in certain directions. 

Question 3. In a market where AI capability is accelerating exponentially, how should leaders think about long-term technology decisions without losing control of risk? 

Jason Sosa: Long-term is a relative term in the world of AI. When you look at the world of exponentials, in the next 10 years we have 30 doublings, based on the fact that AI is doubling about every six months in performance. 

That means, in the next 10 years, we will see a billionfold improvement in the performance of artificial intelligence. So 10 years is a tremendous amount of time in the world of AI. 

This year, we are probably going to experience AI improving itself and the beginning of what is called the singularity. We have about a 10-year horizon before these systems are autonomous, before they are moving at a pace and with knowledge so quick that it outpaces our ability to control or corral them. That will be especially true in corporate environments. 

This presents a whole range of opportunities. It also presents a lot of risk, with bad actors behind the scenes who do not wait for approvals or quarterly budgets. That is where we will see tremendous value in those who can run fast enough, and those who are brave enough to embrace these tools quickly. 

This exclusive interview with Jason Sosa was conducted by Tabish Ali of the Motivational Speakers Agency.