Why change management and human engagement are non-negotiable when leading through AI

Artificial intelligence (AI) is changing everything — how we work, how we lead and how we think about the future. But if there’s one thing I’ve learned in my journey as a CFO, it’s this: technology doesn’t transform a company. People do.

AI is powerful, yes. It can automate processes, accelerate insights and unlock new business models. But none of that matters if your teams aren’t ready to embrace it. That’s why I believe the real differentiators in AI adoption are effective change management and unwavering human oversight.

When we began introducing AI tools into our finance organization, I didn’t start with a software rollout. I started with a conversation. I asked my team: What worries you about AI? What excites you? What do you need to feel confident about it?

The answers were honest and revealing. Some feared potential job losses. Others worried about giving up control. Many simply didn’t know what AI could do. And they’re not alone. A 2025 Pew Research survey found that 52% of U.S. workers are worried about AI’s long-term impact on their careers. Another poll showed that 71% of Americans fear AI will lead to permanent job reductions.

That’s why I treated our AI rollout as a change-management journey. We identified 'AI champions' — early adopters who were curious and eager to learn. We built tiered training programmes and created safe spaces for experimentation. We started small, automating routine tasks, like financial reporting. And we celebrated every win.

As the tools began freeing up time for deeper analysis and strategic thinking, scepticism turned into excitement. People saw that AI was empowering them and that shift in mindset was everything.

I’ve always believed that AI should amplify human judgment, not supplant it. No algorithm, no matter how advanced, can replicate the nuance, ethics and intuition of a skilled professional.

We’ve seen what happens when human oversight is missing. Take one company's AI recruiting tool, which was trained on historical data and ended up systematically discriminating against women. Or a sovereign government's 2020 exam grading algorithm, which downgraded 39% of student scores, disproportionately affecting those from underprivileged schools.

These examples are cautionary tales. At HPE, we embed human reviews into every critical AI process. Our Investor Relations team uses AI to draft earnings scripts and anticipate analyst questions, but every output is reviewed and refined by professionals. It’s not about replacing expertise. It’s about amplifying it.

And we’re not alone. A 2025 CompTIA report found that 79% of companies that tried eliminating human tasks with AI ended up backtracking when the technology fell short. That’s a powerful reminder: AI needs human judgment to succeed.

One of the most rewarding parts of this journey has been watching our teams grow in confidence. When we launched our global AI training initiative, we paired finance employees with data scientists to solve real-world problems. We encouraged curiosity, experimentation and collaboration.

Today, our analysts use CFO Insights, an AI-powered analytics agent that we co-developed, to get on-demand answers from financial data. Our accountants leverage AI-assisted reconciliation tools to accelerate close cycles. And, most importantly, our people question and refine AI outputs. They’re not passive recipients — they’re active partners.

Externally, the need for AI literacy is clear. A 2025 Resume Now survey found that 89% of workers are concerned about AI’s impact on job security. Yet, many are taking the initiative: 55% are researching AI skills on their own and 42% have enrolled in training.

Companies must meet them halfway. One in three companies now mandates AI training and 85% value certifications to validate staff knowledge. At HPE, thousands of employees have completed AI training and many have earned internal badges as 'AI Advocates' or 'Citizen Developers.' That’s the kind of momentum that drives transformation.

If you’re a leader navigating AI adoption, here’s what I’ve learned:

Choose a task with clear outcomes — like reducing report time or improving forecast accuracy. Celebrate early wins and share metrics beyond ROI, including trust and engagement.

Track success across compliance, employee sentiment and stakeholder confidence. Use structured evaluation, not anecdotal feedback.

Communicate the 'why' behind AI adoption. Offer training, mentorship and hands-on experimentation. Lead by example.

Establish governance frameworks and human-in-the-loop checkpoints. Train teams to critically assess AI outputs and empower them to make informed decisions.

Normalize AI use across workflows. Recognize employees who innovate with AI. Make AI proficiency as standard as spreadsheet skills.

Not every AI experiment will succeed. Treat failures as learning opportunities. Adapt and refine continuously.

AI isn’t going to replace leaders, but those who harness it effectively will outperform those who ignore it. The divide won’t be between companies that use AI and those that don’t. It will be between those who integrate AI thoughtfully and those who implement it carelessly.

Let’s harness AI not just for efficiency, but as a catalyst for inclusive, ethical and transformative growth. The choices we make today will shape the future of work, society and the global economy. In the age of AI, it’s our humanity that will set us apart.