Leadership in the Age of AI: Can Leaders Still Stay Relevant?

Artificial intelligence can now analyse a market faster than most strategy teams, model risk more precisely than most finance directors, and draft a cleaner memo than most chiefs of staff. So here’s the uncomfortable question every leader eventually has to sit with: if a machine can out-analyse you, out-calculate you, and increasingly out-predict you, what exactly is left for you to lead?

It’s not a comfortable question. But it’s the right one for this era.

Every industry conversation about artificial intelligence eventually circles back to leadership. Not because leaders need to become data scientists overnight, but because technology is moving faster than most organisations’ capacity to lead through it. Generative AI, machine learning, and intelligent automation are no longer emerging tools sitting in an innovation lab somewhere they are quietly running inside customer service, hiring, credit decisions, fraud detection, and strategy rooms across the region. Which brings us back to the real question: can human leadership still stay relevant?

Why This “New Era” Feels Different

Leaders have navigated new technology before the internet, mobile, cloud computing, each one triggered its own wave of anxious “will this replace us?” conversations. What makes the artificial intelligence era feel different is speed and scope. Digital transformation used to touch one function at a time. Generative AI touches almost every function at once: how a business makes decisions, how a team communicates, how a customer is served, how a strategy is built.

This is precisely why leadership in the age of artificial intelligence has become one of the most discussed topics in business publications today, from Harvard Business Review to MIT Sloan Management Review. And the consistent insight across this research isn’t that leaders need to out-code the machines. It’s that the leadership skill set that mattered in the last era of digital innovation is not automatically the one that will matter in this one.

What Singapore’s Own AI Story Reveals About the Leader’s Real Job

You don’t need to look overseas for proof of how artificial intelligence is reshaping business. DBS Bank, headquartered right here in Singapore, offers one of the most closely studied AI transformation stories in global banking closely enough that Harvard Business School built its first-ever Asian bank case study around it.

The numbers alone are striking. DBS now runs more than 800 AI models across roughly 350 use cases, and the bank’s own reporting puts the economic value generated through AI at S$750 million in 2024, with an expectation of crossing S$1 billion in 2025. Its Gen AI-powered career coaching tool, iCoach, has been used by employees who report improved work performance, stronger workplace relationships, and better communication as a result. Intelligent automation has cut manual processing time for routine transactions dramatically, and AI-driven fraud detection systems now flag suspicious activity with a level of accuracy no manual review process could match.

Here’s the part every leader should pay attention to, though: none of this happened because DBS decided technology alone would drive the business forward. Group CEO Tan Su Shan has described the bank’s ambition as building an “AI-enabled bank with a heart” blending machine intelligence with human empathy to protect the trust customers place in the institution. Long before the results showed up on a scorecard, DBS built an internal ethical framework called PURE ensuring every AI use case is Purposeful, Unsurprising, Respectful, and Explainable and it made completion of PURE training mandatory for every single employee, not just the data science team.

In other words, the technology didn’t drive the transformation. Leadership did. The bank’s leadership team made a strategic choice about culture, ethics, and trust before it made a choice about which model to deploy. That’s the real lesson for every organisation eyeing its own AI roadmap: the hardest part of digital transformation was never the algorithm.

What Machines Still Can’t Do and Why That’s Your Opening

McKinsey’s research on building leaders for the AI era is blunt about this: artificial intelligence can draft your emails, summarise your meetings, model your risk, and even outline arguments on both sides of a decision. 

What it cannot do is set an aspiration people actually want to follow, make a genuinely hard call under uncertainty, build trust among stakeholders who disagree with each other, or hold a team member accountable in a way that lands with respect rather than resentment. That work the actual work of leadership remains stubbornly, valuably human.

This is where emotional intelligence stops being a “nice to have” on a leadership competency framework and becomes the differentiator. Research popularised by Daniel Goleman in the Harvard Business Review found that close to 90% of what separates outstanding senior leaders from average ones has little to do with raw cognitive horsepower it comes down to emotional intelligence. 

As artificial intelligence absorbs more of the analytical and technical workload, the leadership premium shifts even further toward the human skills machines cannot replicate: empathy, judgement, self-awareness, and the ability to read a room a spreadsheet will never show you.

McKinsey’s own workforce research adds a sobering data point to this: over 70% of the skills employers value today apply to both automatable and non-automatable work, but a meaningful share of human capability judgement, relationship-building, creativity remains entirely irreplaceable, at least for now. 

The organisations getting real value from AI aren’t the ones with the most sophisticated model. They’re the ones whose leaders understood which decisions still need a human signature.

The Leadership Skills That Matter More, Not Less

At the 2025 MIT Sloan CIO Symposium, technology executives were asked what leadership trait matters most in the AI era. The most common answer wasn’t data literacy or technical skill it was courage. 

As Liberty Mutual’s CIO Monica Caldas put it, leading through this era takes the courage to challenge your own beliefs about how things should work while they’re still evolving underneath you.

That single insight captures what’s actually being asked of leaders today. Four capabilities in particular are rising to the top of every serious leadership conversation:

Human-AI collaboration. Leaders need enough technical fluency to know what artificial intelligence can and can’t reasonably do, so they can design work where humans and machines complement each other rather than compete.

Ethical stewardship. As DBS’s PURE framework shows, trust doesn’t happen by accident. Someone has to decide, deliberately, what responsible and ethical use of data and AI actually looks like inside their organisation and then hold the whole company to it.

Change leadership. Digital transformation fails far more often from resistance, unclear expectations, and cultural friction than from bad technology. Leading change well, not just announcing it, is now a core leadership skill rather than a project management task.

Emotional and social intelligence. Empathy, active listening, conflict navigation, and the ability to build genuine trust these are increasingly cited by executives as the fastest-growing skills gap in their organisations, ahead of even the technical ones.

MIT Sloan Management Review has gone as far as suggesting that AI-driven transformation now demands an entirely new kind of leadership role one built to bridge technical strategy with organisational psychology and culture change, because most stalled AI initiatives fail not from weak algorithms but from leadership systems and culture that were never prepared for AI-enabled work in the first place.

How Leaders Can Prepare Their Organisation for What’s Next

If you’re leading a team, a department, or an entire organisation through this shift, a few practical moves make the difference between AI as a genuine advantage and AI as an expensive experiment that never scales.

Decide what “human-only” decisions look like before you need to. Not every decision should be automated, and not every decision should be manual either. Get clear, as a leadership team, on which calls require human judgement, accountability, and context, and protect those deliberately.

Invest in people at the same pace you invest in technology. DBS didn’t wait for disruption to force reskilling it launched a professional conversion programme back in 2017, years ahead of the current AI wave, and has continued investing in upskilling thousands of employees since. The organisations that will still be relevant in five years are treating capability-building as strategy, not as an HR afterthought.

Build the trust infrastructure first. Whether it’s a formal framework like PURE or something simpler, your team and your customers need to understand how decisions involving AI are made, and why. Trust, once lost, is expensive to rebuild and far more expensive than the AI system itself.

Model the behaviour you want your team to adopt. If leadership treats generative AI as a shortcut around thinking, teams will too. If leadership treats it as a tool that frees people up for higher-value judgement, strategy, and relationships, culture follows.

Keep learning in public. The fastest-moving leaders aren’t the ones who already know everything about artificial intelligence they’re the ones willing to say “I don’t know yet, let’s find out together,” and build that experimentation into how the organisation works.

Can Leaders Still Stay Relevant?

Relevance was never really about being the smartest person in the room, even before artificial intelligence arrived. It was about being the person your team trusted to make the hard call, hold the line when it mattered, and create the conditions where good work and good people could thrive.

Artificial intelligence changes the tools. It doesn’t change that job description. The leaders who stay relevant in this new era won’t be the ones who compete with the machine on speed or memory. They’ll be the ones who double down on the parts of leadership no algorithm has ever been able to replace vision, trust, empathy, sound decision making, and the willingness to make genuinely difficult decisions and own them.

As DBS’s own journey shows, the organisations getting the most value from AI aren’t the ones with the flashiest technology. They’re the ones whose leaders decided, deliberately and early, what role human judgement would continue to play while everything else changed around it. That’s what effective digital leadership looks like: using AI to enhance human capability, not replace it, while driving digital transformation with purpose and clarity.

At Deep Impact, this is exactly the conversation we help leadership teams have not “how do we adopt AI faster?” but “who do we need to become as leaders so our people, and our organisation, thrive because of it?” Through leadership development, decision making frameworks, and practical digital leadership strategies, we help organisations drive digital transformation without losing the human qualities that create lasting performance. If you’re navigating what this shift means for your leadership team, we can connect ! 

Frequently Asked Questions

Will artificial intelligence replace leaders? 

No. but it will replace leaders who define their value purely through technical or analytical skill. AI can handle much of the data-crunching, drafting, and pattern-spotting that used to fill a leader’s day. What it can’t do is set direction people believe in, build trust across a team, or take accountability for a genuinely difficult decision. That work stays human.

What leadership skills matter most in the age of AI? 

Emotional intelligence, ethical judgement, change leadership, and the ability to collaborate effectively with AI systems are consistently ranked as the most important leadership skills right now arguably more important than deep technical expertise, according to research from McKinsey company and MIT Sloan Management Review.

How should organisations prepare their leaders for AI-driven change? 

Start with people, not just platforms. Build clarity on which decisions stay human, invest in reskilling ahead of disruption rather than after it, create an ethical framework for how AI is used, and make sure leaders are modelling thoughtful adoption rather than either blind resistance or blind reliance.

Read more: Preparing for AI at Work: Lessons from the DBS Singapore Case Study