As the landscape of work itself seems to shift beneath this generation’s feet, how can new workers better prepare themselves to become the leading tech-based CEOs of the next generation?
In recent years, AI has become a widely used tool across numerous industries. It has changed the very infrastructure of work, resulting in a complete reprioritization of what new workers need to know and which tools they need to be familiar with. It may be the current crop of leading tech CEOs who are driving advancements toward a more AI-oriented, optimized business future. Still, it is the next generation that will ultimately determine the success of this decision.
Many detractors of AI have decried it as a fad in recent years, while others claim it isn’t going anywhere. But how exactly can the next generation of workers prepare for the future ahead? What does it take to lead in this new landscape? Five founders and executives share the skills and mindsets they believe will define tomorrow’s most effective tech leaders.
CEOs Need to Understand How Systems Operate
Shenal Vanderwall, founder of Meeedly, believes that as AI enables entirely new product categories, CEOs must understand the systems that underpin them.
“If you’re an entrepreneur these days… understanding how systems work is very important for two things. One is for the operational background of it. The second is for the growth of your own company… Many of the tools that are there nowadays, you can learn by yourself—but the moment you don’t, you have to have someone else do it for you,” Vanderwall says.
He transformed his company from a meeting engagement tracker into a leader in “Meeting Coordination Infrastructure” by deeply engaging with systems architecture and automation.
“There are millions of product companies that come in every single day, and maybe one or two actually make it every day. That’s purely because people don’t understand that integration part that needs to happen from your customer to their workflows.”
Vanderwall also pioneered an AI-first approach to market education, training LLMs to surface Meeedly’s new category organically.
“We are one of the emerging categories, so nobody knows about the category that we actually built. The way we use AI is implementing and educating existing platforms about us. If you go to ChatGPT, they already know about us; we have trained all those models that people go and ask about, and we have done it in a smart way.”
The Importance of Managing Context
Danielle Dafni, Founder & CEO of Speechbox, believes that the role of the AI-era CEO is shifting from managing headcount to managing context.
“The context is everything… You have one source of truth: the information that all agents need to collaborate with and to understand: what the tasks are, the capabilities, the KPIs, and the responsibilities. The difference between the people who can use agents versus those who can’t is whether you understand how to build this context and the ongoing process with them,” Dafni says.
Her company is actively testing a model where a small human team orchestrates more than 50 AI agents, proving that extreme focus on a single goal is the new competitive edge.
“Right now, my only proof is that we can do the zero-to-one with a very small, lean team; but on the other side, we have more than 50 agents. So it’s about building the technological side beside the people, beside the team members, and checking if we can get to product-market fit that way.”
Dafni further argues that leaders must now excel at context engineering: defining tasks, KPIs, and a single source of truth for AI agents.
“There are so many tools out there, and so many experts telling you to try everything. No, you don’t need to try everything—you need to understand where you want to go and focus on that specific destination. I am very passionate about everything that happens now in terms of tools, but I resist using everything because I know I will go out of focus.”
Balancing AI with Human Insight
Jennifer Hill of ThoughtRiver believes that as AI becomes embedded in legal and contract workflows, CEOs must balance innovation with human oversight.
She details, “I think it can be an easy excuse to remove humans from the equation, and that’s not a good thing to do… We don’t want to remove so many people that things can’t get solved. There will always be areas where the human and the AI need to work together.”
Hill also emphasizes that the most critical leadership skill remains deeply human: understanding people, connecting with them, aligning teams around change, and communicating with clarity.
“Understand people and get as much experience as you can working with different types of people in different situations, because leadership looks different in every context. Figuring out how to make a connection with people, how to align a team around a vision and a purpose, how to communicate crisply—those are all things that actually make for really strong leadership.”
Hill further warns that removing the human from AI-assisted processes risks “computer says no” frustrations that erode client trust.
“The biggest thing that often gets missed, particularly now that you have generative tools, is the expectations around accuracy. We want it to work like a magic wand and be Instagram easy. But depending on the complexity of the task, the importance of the outcome, and the kind of data involved, expectations need to be managed.”
Asking the Right Questions
Joshua Maddux, Founder & CEO of 95Visual, has found that effective AI adoption starts with the right question: What problem am I solving? “You need to not look at tool A or tool B; you need to look at what is the problem that needs to be solved. Think about it like hiring: we’d write a job description, we’d write requirements. But instead, what we’re doing with AI is grabbing the first shiny object we see and trying to make it fit. And when it doesn’t fit, we’re forcing every employee to support that incapable tool.”
He stresses that CEOs must also prioritize risk management, assessing security, data privacy, and long-term sustainability before committing to any AI platform.
“Is it sustainable? You don’t hire 100 employees for two days, because that’s not going to work. So is it sustainable to build the whole business model around using a third-party LLM at X price point per token? That company we’re relying on isn’t profitable. What happens when they decide next year to double their cost per token?”
Maddux also coaches clients to treat AI like a new hire; define the need first, then evaluate tools against real requirements.
He details, “ChatGPT is a three-year-old. Like, you’re talking to a three-year-old… Augmenting, great. Adding tools, great. Testing things out, great; let’s see if it scales up. But sweeping infrastructure changes are hard. I remind people all the time: these are tools that are supposed to be helping and supporting the staff, not the other way around.”
The Value of Judgment
Geoff Wasserman, Founder of Spark Imagine, thinks that the CEO’s most valuable asset in the AI era isn’t technical fluency; it’s judgment. He frames the CEO’s evolving role as “orchestrator;” managing people, processes, and AI systems in concert—and insists that consistency, not novelty, is the true hallmark of enduring leadership.
“The next generation of CEOs won’t win because they’re better managers. They’ll win because they’re better orchestrators. AI makes execution cheaper, and judgment becomes more valuable… A lot of times AI will be confidently wrong. It’s so important that as a CEO, you have the judgment to know when to make the call and say, this is not the right answer.”
Wasserman also believes that as AI becomes cheaper and faster to execute, the premium shifts entirely to human ability to spot what AI confidently gets wrong.
“The old CEO is managing people. In the future, CEOs are moving more toward managing systems, which include people, processes, and AI. It’s a more sophisticated, more complex system orchestration, and it’s a shift in the way that leadership is moving.”
He goes on to elaborate that, “The advice I would give is consistency. Don’t give up. You have to keep consistently showing up. The first products that I tested didn’t work… You have to be consistent, and you have to keep showing up every day.”
Final Thoughts
While the AI era doesn’t necessarily require CEOs to become engineers, it does require them to be willing to think in systems, lead with clarity, and exercise sharp judgment about when to trust AI and when to override it. Across industries, successful leaders are those who view AI as a partner rather than a helper crutch, staying sharply focused on the human benefits that technology aims to deliver.
