The View from the Top: Leadership in the Age of AI

Thirty years ago, leadership was about intuition, experience, and strategic bets. The best executives had an uncanny ability to see patterns, anticipate industry shifts, and make judgment calls that defined their companies’ future. In my decades in the IT industry, I’ve seen leadership redefined many times through globalisation, the rise of the internet, mobile revolutions, and cloud computing.

But nothing, absolutely nothing, has rewritten the playbook as fast as AI.

AI is forcing us to rethink what it means to be a great leader. It’s changing how we define success, recognise achievement, and maintain a human touch in increasingly automated environments. It’s not just about leading companies anymore — it’s about leading in an ecosystem where AI is a co-pilot, employees are uncertain about their future, and the market moves at speeds no human can fully comprehend.

So, what does leadership look like when AI is everywhere? And how do you lead in a world where algorithms, not instincts, dictate strategy?

In this article, I share three perspectives on redefining leadership. The first two explore the shifting fundamentals driven by AI, and the third introduces new learning emerging from seismic policy and ecosystem changes driven by Trump’s decisions.

Perspective 1: AI Is Ringing in a 180-degree Shift in the Definition of a “Great Leader”

The qualities that made someone a great leader in the past — vision, decisiveness, charisma — aren’t enough in the AI era. Leadership now requires a new kind of adaptability, a new way to measure success and a new approach to people management.

How to Quantify Milestones and Recognise Achievements When So Much Is Automated?

For decades, leaders have measured success by productivity gains, revenue growth, and workforce efficiency. AI upends that equation by automating tasks, making employees more productive but less visible. If a team meets its quarterly goals through AI-driven efficiencies, who gets credit — the employees, the AI, or the leader?

Performance metrics need a rethink. Leaders must look beyond traditional KPIs and focus on:

● AI-driven value creation: How is AI enhancing decision-making and driving innovation?

● Human-AI collaboration: Are employees leveraging AI effectively, or is AI taking over?

● New efficiency benchmarks: What does productivity mean when AI does the heavy lifting?

Recognition also changes. Celebrating individual achievements is harder when AI plays an invisible role in success. Leaders must foster a rewarding culture where human contributions — creativity, problem-solving, and adaptability — alongside AI-driven efficiencies. AI must now optimise for tariff arbitrage, friend-shoring compliance, and sanctions evasion (e.g., AI-driven supply chain rerouting post-China tariffs). A leadership action could be to move away from KPIs measuring “efficiency” to resilience metrics (e.g., AI-simulated trade war scenarios). Thus, credit teams for adaptive wins (e.g., using AI to pivot manufacturing from China to Vietnam).

How do we rethink people skills as human-to-human connections require reprioritisation?

AI is incredible at optimising workflows but can’t build trust, mentor employees, or inspire teams. The paradox? As AI handles more operational tasks that free up time, leaders have more time for people, but many aren’t using it that way.

The risk is clear: automation reduces the number of human interactions in the workplace, and leaders who don’t double down on human skills risk alienating their teams. That means:

● Investing in emotional intelligence (EQ) development

● Prioritising transparent and frequent communication

● Creating spaces for real human collaboration, not just digital interactions

How to Cope with Increased Market Volatility and Employee Cynicism Amid the Rise of AI?

AI moves faster than business cycles. The markets don’t just shift — they churn. Consumer behaviours change overnight. Entire industries transform in months, not years.

Employees are also sceptical. A 2023 Pew Research report found that 62% of workers believe AI will take over most human jobs in the next two decades. Cynicism is rising, and leadership means managing business strategy and employee morale.

To lead through uncertainty, executives must:

● Develop AI fluency and ensure employees understand AI’s role in the company

● Offer reskilling programs that prepare teams for AI-augmented work

● Set realistic expectations — acknowledge AI’s disruptive impact but highlight opportunities

Employees are cynical about AI and geopolitical instability (e.g., layoffs from tech decoupling). Thus, a leadership action can directly use AI to predict workforce disruptions (e.g., modelling job impacts of semiconductor export bans). Alternatively, double down on EQ — address fears of AI and globalisation rollbacks.

How to Tailor Foresight and Road mapping Strategies in a Shifting Technology Landscape?

Strategic planning was helpful as it created and involved people to develop long-term roadmaps based on historical data. AI makes that approach obsolete. Predictive analytics can forecast trends, but those trends shift as rapidly as AI evolves. Leaders need to build flexible, AI-driven strategic models:

● Scenario planning with AI simulations

● Adaptive strategies that change in real-time

● Investment in continuous learning to stay ahead of AI advancements

Trump’s potential return has meant abrupt tech bans (TikTok), trade wars, and subsidy shifts (CHIPS Act 2.0). A leadership action could call for deploying AI-powered policy simulators to stress-test strategies and replacing 5-year plans with 90-day AI-driven sprints.

Perspective 2: The More Things Change, the More They Remain the Same

Despite AI’s impact, certain leadership fundamentals remain unchanged. At the core, business is still about people, relationships, and vision. The best leaders will master AI but won’t forget what truly drives success.

The Importance of Honing High EQ

AI can process terabytes of data in seconds, predict trends before they emerge, and automate complex workflows. But here’s what it can’t do: read the room. It can’t defuse tensions in a high-stakes negotiation, motivate a burned-out team, or intuit when an employee is on the verge of quitting. Due to Trump’s decisions, EQ is in a divided ecosystem. Thus, the leader can use AI sentiment analysis to detect polarisation and human diplomacy to bridge divides.

That’s where emotional intelligence (EQ) comes in. In an era where AI is optimising logic and efficiency, the best leaders will stand out not because of their technical prowess alone — but because they master the human side of leadership:

Communication

AI can analyse sentiment and generate reports but can’t replace a human-to-human connection. Leaders who communicate clearly and authentically will always stand out.

Creativity

AI can suggest ideas, but true innovation comes from human imagination. The most successful leaders will cultivate a culture where creativity thrives alongside AI-driven efficiency.

Empathy

AI lacks empathy. Understanding and addressing employee concerns, fears, and aspirations is more critical than ever.

Diversity

Diverse teams drive better business outcomes. AI can help mitigate bias in hiring, but leaders must ensure that inclusivity remains a priority in company culture.

Leveraging AI as a Lever for Great(er) Leadership

AI isn’t just a tool — it’s a force multiplier. It sharpens decision-making, streamlines operations, and unlocks once-unimaginable efficiencies. But here’s the catch: AI doesn’t lead. That’s still your job.

The best leaders aren’t just adopting AI; they’re wielding it strategically. They’re using it to eliminate inefficiencies, free up resources, and make smarter, faster, and more impactful decisions:

AI for Data Analysis

AI processes vast amounts of data in seconds, uncovering trends humans might miss. Leaders who leverage AI for data-driven decision-making will be able to act with precision.

AI for Cost Reduction and Reallocation

AI cuts costs by automating repetitive tasks. The challenge is knowing where to reinvest those savings to drive growth.

AI for Better Communication

AI-powered tools can personalise messaging at scale, making internal and external communication more effective.

Perspective 3: Leading Through Ecosystem Disruption — The Trump Factor

While AI continues to redefine leadership, recent years have taught us that external policy decisions can dramatically reshape our operating ecosystems. The Trump era introduced policies that have driven transformative changes across multiple dimensions:

Economic Ecosystem

Trump’s deregulation efforts, tax reforms, and policies to boost domestic production fundamentally altered the economic playing field. Market volatility intensified as companies had to adapt to rapid shifts in fiscal policy. Leaders now face the challenge of steering their organisations in an environment where policy changes and restructuring of financial incentives frequently disrupt economic signals.

Political Ecosystem

The political landscape became more polarised and unpredictable during Trump’s tenure. This shift affected domestic governance and influenced public sentiment and consumer behaviour. As leaders navigate this arena, they must now account for heightened political risks and engage with stakeholders who are increasingly attentive to political narratives.

Trade Ecosystem

One of the most visible impacts is in the trade arena. Trump’s tariffs and re-negotiation of trade deals forced companies to reexamine global supply chains and sourcing strategies. Leaders had to develop resilient trade frameworks that could quickly adjust to new tariffs, sanctions, or trade barriers, often reconfiguring international partnerships overnight. AI Opportunity: Real-time tariff optimisation bots (e.g., auto-classifying goods to avoid duties).

Technology Ecosystem

Beyond AI, national security concerns and regulatory shifts reshaped the technology landscape. Policies affecting tech companies — from restrictions on certain Chinese firms to an emphasis on domestic technological innovation — have accelerated the pace at which leaders must adapt. In this context, technological investments are no longer just about competitive advantage but also about regulatory compliance and strategic positioning on the global stage.

Competitive Ecosystem

The combined effect of these policy-driven shifts altered the competitive landscape. Protectionist measures and new trade policies have reinforced the need for businesses to strengthen their domestic competitive edge while remaining agile enough to pivot in the global market. Leaders must prepare for an evolving competitive ecosystem where market forces and governmental policy interventions are rewriting the rules.

Integrating the Trump Legacy into Leadership

Today’s business leaders must reconcile the disruptive potential of AI with the equally potent — and sometimes unpredictable — influences of public policy. It’s not enough to champion technological innovation; leaders must now cultivate a deep understanding of how economic, political, trade, and competitive shifts interact. It means:

- Risk Management: Developing strategic contingency plans for policy-induced disruptions.

- Policy Awareness: Staying informed about regulatory changes and engaging proactively with policymakers.

- Agility: Building organisational structures that quickly respond to technological and geopolitical changes.

- Stakeholder Communication: Crafting clear, consistent messages that reassure employees, investors, and customers amid uncertainty.

The lessons from Trump’s tenure remind us that leadership extends beyond internal strategy — it involves reading and adapting to a dynamic, interconnected global ecosystem. The most successful leaders will harness AI to drive efficiency and innovation and steer their companies through the turbulent waters of policy-induced change.

And Finally, What’s Next for Today’s and Tomorrow’s Business Leaders?

The AI revolution isn’t slowing down. According to a 2024 McKinsey report, AI adoption is accelerating, with 75% of companies planning to integrate AI into core business operations by 2026.

What does this mean for leadership?

It means that vulnerability — acknowledging that technology and external policy can reshape industries — is not a weakness but a form of resilience. It means balancing human intelligence with artificial intelligence, automation with empathy, and strategic foresight with agile risk management.

It also means that leadership in the AI era is about balancing human intelligence with artificial intelligence, automation with empathy, and efficiency with human connection.

Leaders who thrive won’t be those who fear change. They’ll be the ones who embrace it, doubling down on the timeless fundamentals of human connection while deftly adapting to technological and policy-driven disruptions. I’ve seen leadership transform over decades, and AI is the biggest disruptor, yet Trump has trumped AI. But the fundamentals? They endure.

Let me know if you found this perspective valuable or even thought-provoking. Could you comment or send me an email? Let’s discuss the future of leadership, AI, and what’s next.

I was hoping you could write to me at Arvind@am-pmassociates.com.