AI Won’t Replace Leaders, But It Will Change How Leadership Works – Opinion by Ruslan Tymofieiev

The rapid development of AI is fueling a growing wave of anxiety across social media, Reddit, Medium, and business circles about whether this new technology cycle will lead to large-scale job losses. And that concern is no longer limited to rank-and-file employees. In 2025, a Dataiku/Harris Poll found that 74% of CEOs believe they could lose their job within two years if they fail to deliver measurable AI results.

Yet Ruslan Tymofieiev, co-founder of the venture fund Adventures Lab and the venture builder CLUST, sees this trajectory differently. In his view, AI is unlikely to make leadership obsolete. What it is far more likely to do is change how leadership works in practice, what leaders focus on, how decisions are prepared, and where human judgment becomes most essential. He thinks that the more important question isn’t whether AI can produce answers faster, but what leadership becomes when answers are suddenly everywhere, while responsibility remains human.

AI is changing how decisions are made

Ruslan is sure, one of the clearest effects of AI inside companies is speed, especially at the leadership level. For senior managers and executives, this often shows up as faster decision preparation. Custom LLMs can help leadership teams synthesize internal reports, compare scenarios, draft executive summaries, and surface risks across multiple data sources. AI meeting tools such as Fireflies, Otter, and tl;dv can automatically transcribe discussions and extract decisions, action items, and follow-ups, reducing the need to reconstruct meetings from memory or scattered notes. 

Workflow automation tools such as n8n and Zapier push this further by removing routine coordination work that often accumulates around top management. For example, a meeting transcript can be automatically turned into a structured summary, with owners and next steps sent to Slack, Notion, Gmail, or a task manager without manual follow-up. That reduces the administrative load around meetings, reporting, and cross-functional follow-through. In addition, it gives leaders more room for the decisions that matter more, capital allocation, strategic prioritization, hiring bets, market timing, partnership choices, and organizational design.

But the leadership is still about navigating ambiguity, interpreting incomplete signals, and making decisions in situations without perfect answers. That part doesn’t disappear with AI and becomes more visible. As analysis becomes faster and more accessible, the value of leadership shifts toward interpretation, prioritization, and judgment.

Why you should learn to work with AI as a strategic tool

The question is no longer whether leaders should use AI, that will soon become standard practice. The real issue is whether they are ready to change how they work because of it. In many companies, AI adoption remains superficial, a few tools are introduced, some repetitive tasks become faster, but the management model itself does not really change. Meetings still run the same way, reporting still depends on manual effort, and leaders continue spending time on work that could already be automated.

That is why experimentation alone isn’t enough, effective leaders treat AI as a co-pilot for analysis, planning, and decision preparation. Used well, it can help structure information, compare scenarios, surface risks, and reduce routine cognitive load. Although it still needs human judgment to interpret context, set direction, and make the final call.

So, the real competition will belong to those who know how to combine AI capabilities with human judgment in a disciplined way. That is where faster execution becomes better leadership, rather than just more automation.

Which skills do leaders need in the AI era?

The strongest leaders in the next few years are unlikely to be those who simply adopt some AI tools. More likely, they will be the ones who understand where AI creates real leverage, where it adds noise, and where human involvement should remain non-negotiable.

That requires a different leadership discipline. Executives need enough practical fluency to see where AI is useful, where it can be misleading, and where teams may start relying on it too passively. Just as importantly, they need to treat AI as part of organizational design.

Nowadays, Ruslan thinks that the most important skills are:

• Strategic thinking. This means knowing which processes should be accelerated, which decisions should remain deeply human, and how AI fits into the company’s longer-term direction.

• Decision-making under uncertainty. Leaders still need to make calls when the data is incomplete, the market is moving, or the trade-offs are not obvious.

• Understanding data and AI outputs. Leaders need to read AI-generated summaries, forecasts, and recommendations critically. That includes spotting weak logic, missing context, biased inputs, or outputs that don’t hold up strategically.

• Building AI-ready organizations. An AI-driven approach is redesigning workflows, clarifying ownership, training teams to use AI responsibly, and deciding where automation should support people versus where judgment should stay fully human.
  

In June 2025, Ruslan Tymofieiev and CLUST’s team made a deliberate move toward an AI-first model. So, they hired a Head of AI, a technical leader responsible for embedding AI into processes across the company. The goal was to rethink how the business will work with AI support in daily operations. It involved training specialists across the company to use AI in their daily work, introducing AI-driven automation in every department, from legal to marketing, and applying AI to higher-level strategic tasks such as market analysis and identifying promising niches for new startup launches.

The risk of over-relying on AI

There is, however, another side to this shift, the more useful AI becomes, the easier it is to give it more authority than it should have. Teams become less critical, managers rely too heavily on polished AI outputs, discussions become shallower, and fewer assumptions get properly challenged. When that happens, leadership becomes weaker.

That is why the real challenge is not AI adoption alone, but disciplined adoption. Companies need AI to increase speed and capacity, but they also need clear boundaries around judgment, ownership, and responsibility.

Ruslan concludes, AI is certainly reshaping leadership. It will change how decisions are prepared, how quickly organizations are expected to move, and which forms of judgment become most valuable. When information is abundant and recommendations arrive instantly, the real differentiator is the ability to stay clear-headed, ask better questions, and make responsible decisions under new conditions.