AI leadership – Live Laugh Love Do

Billions spent, zero returns: The leadership gap derailing AI’s big bet

admin — Thu, 16 Oct 2025 12:42:36 +0000

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Corporate America has already poured tens of billions into AI. Most companies can’t point to a single business result.

The technology works. Employees are using it. What doesn’t work is that we’re asking leaders to drive massive change without equipping them to do it successfully. Until that gap closes, AI will remain stranded capital.

The math is brutal. MIT found that 95% of generative AI pilots at companies are failing. Bain reports organizations spent $30 to $40 billion on generative AI in the past year. And McKinsey found fewer than 1% of companies describe their AI adoption as “mature.” Massive investment, negligible return.

I spent nine years at Salesforce leading through major transformations. The technical side of change is never the hardest part. It’s always the human side that determines whether things succeed or fail.

What nobody’s saying out loud

I keep hearing the same pattern in conversations with executives. They have AI mandates from the top, with no clarity on how to get their people ready, on top of everything else they’re already managing. And there’s this thing they’ll only say in private, “I don’t know what I’m doing.” Nobody does.

In most organizations, leaders are still rewarded for looking certain, staying in control, running tight systems. Take a risk with AI and get it wrong? Most people believe they’ll be punished for failure. Those same behaviors crush the experimentation and trust AI depends on.

Companies are essentially handing leaders technical training and telling them to figure it out. That’s hope, not strategy.

When Bret Taylor became Salesforce’s Chief Product Officer, I got 30 minutes with him as a rising product leader. I knew our approach wasn’t working and spoke from the heart about what I was seeing and how it needed to be better. He could have dismissed it, as I was several levels down. Instead, he listened.

We created an Associate Product Manager program that taught not just technical skills but also critical leadership skills like how to challenge the status quo, navigate conflict, work across teams, and show up under pressure.

We didn’t just mandate change or add a training program. We changed the nature of the conversations teams were having by injecting new thinking and new ways of working at a grassroots level. Then we listened closely to what was working and what was standing in our way and iterated on our approach in real time. That’s how you build lasting change, not by announcing something and hoping everyone figures it out.

Most companies are doing exactly that with AI. Funding tools and training, while neglecting the systemic change needed to drive real transformation.

What the 5% actually do differently

Harvard Business Review analyzed what separates companies where AI pilots succeed from the 95% where they fail. The differentiator isn’t the technology. It’s leadership.

The winning companies do two things at once. They fund technical training and fund developing leadership capacity for transformation. Their leaders can navigate fear and resistance across teams. They create strategic clarity and alignment. They create safety for experimentation and failure. They model risk-taking in uncertainty and hold people accountable to entirely new standards.

That requires real support. Not just workshops, but individualized help for challenging situations. How to have conversations about readiness. How to create psychological safety when someone says they’re afraid of being replaced. How to navigate resistance when it inevitably shows up.

Most companies lack that leadership infrastructure. Gartner found 66% of CEOs say their executive teams lack AI confidence. The leaders who can create clarity and safety in chaos, their teams will become AI-first. The ones who can’t? Their teams will just be busy.

You can’t solve an adaptive challenge with a training program. Leaders need help applying AI to their actual work: their specific role, team, challenges. They need a place to work through fear and uncertainty without career risk. That’s fundamentally different from what most companies are funding, and the 95% failure rate proves it.

Companies are funding the wrong intervention

Companies are treating AI as a technical problem when it’s a leadership capacity problem. Your competitors are making the same calculation right now. Some of them are getting different answers.

AI is forcing us to confront something we should have fixed years ago. We’re asking leaders to navigate unprecedented complexity with the same development approach that hasn’t worked for decades.

The companies that get this right won’t just succeed with AI. They’ll build leadership capacity that outlasts whatever technology comes next.

The billions are already spent. The question is whether they turn into returns or stranded capital. That answer depends entirely on whether you’re willing to fund the leadership gap, not just the technology gap.

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Investing in early-in-career talent is vital to win the AI race

admin — Fri, 22 Aug 2025 06:05:48 +0000

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As the AI era accelerates, some leaders have predicted a wipeout for entry-level white-collar jobs. I understand these concerns as unemployment rates rise for U.S. college graduates. But cutting early-in-career (EIC) talent isn’t a transformation strategy. It’s the start of a slow-motion collapse.

AI is fundamentally changing how we work. People will increasingly oversee more AI agents, changing the way we think about teams. Business leaders must shape what’s next—not shrink from it.

From job elimination to job evolution

EIC employees are AI natives who are already leading the transformation. They intuitively engage with tech, bring creative agility, and have the curiosity needed to thrive in fast-changing environments.

According to the World Economic Forum, job loss between 2025 and 2030 will be more than offset by new roles, leading to a net gain of 78 million jobs. As some roles and tasks phase out, new ones emerge that require skills like AI and data fluency, creative thinking, resilience, and curiosity.

If we don’t protect and modernize the EIC pipeline, we risk widening the skill gaps and stalling the impact and ROI of AI solutions. EIC talent will be tomorrow’s leaders, so we need to build pathways for them today.

The demographic and leadership imperatives

The talent pipeline is narrowing just as the pace of transformation is accelerating.

U.S. birth rates are declining. Fewer 18-year-olds are entering the workforce. Higher education costs are skyrocketing, and many high school graduates are choosing two-year and technical degrees or trade jobs.

That makes every EIC hire even more valuable.

HR leaders help define the structure of the workforce and manage payroll—the largest line on the profit and loss statement—so where we invest matters. EIC roles are often the smartest entry point for workforce planning.

We need to build AI-first cultures rooted in continuous learning, with roles that fuel business and personal growth. That means doubling down on equipping early-career talent with the skills, creativity, and adaptability to lead AI-powered organizations. And our succession pipelines must prioritize leadership capabilities like AI fluency, orchestration, and human-centered change management.

That means focusing on these key steps:

Reimagine strategic workforce planning

As leaders, we must identify the skills AI won’t replace and the skills that matter most to our businesses—from programming and UX design to collaboration, creative problem solving, and empathy. Then we should map those skills to evolving roles. For example, if AI handles research, an entry-level role could evolve into a prompt engineer or curator. Other future roles could include AI safety and ethics coordinators and AI agent trainers for front line workers.

Design new rotations and exposure

Companies that invest in internships build future-ready talent pipelines. Internships today are table stakes. To stand out, we need to build rotational programs, apprenticeships, and real-world experiences that give EIC hires exposure across the business. Reverse mentoring, for example, could give EIC talent a chance to connect directly with senior leaders, while giving those leaders a window into AI-native thinking.

The goal is to retain top talent by creating a culture of growth, mobility, and connection. With clear goals, meaningful work, strong managers, and real learning experiences, EIC talent has the chance to thrive and drive innovation. At ServiceNow, 95.6% of our interns accepted our full-time offers in 2024, proof of meaningful investment.

Embrace AI-first learning for growth and retention

Retaining top talent, especially early-in-career talent, starts with listening followed by meaningful action. Sixty-five percent of EIC workers say they’d stay at least four years at a company if it offered robust development opportunities. We need to show EIC talent how they can grow, and design learning that matches their curiosity.

EIC employees expect learning to be personalized, bite-sized, and built into the workflow. That’s why we launched ServiceNow University—to train our employees and the broader technology ecosystem. It’s working: EIC hires at ServiceNow have a 7% lower attrition rate in their first two years than their peers.

The long game: Invest in young talent and AI

Leaders don’t need to decide between cutting costs and investing in the future. They can do both when they focus on transforming the workforce.

Organizations that lead with intention—those that rethink roles, invest in AI enablement, and reimagine EIC talent—will attract the best minds and shape the next era of innovation.

We all have a lot to learn in this new world, and we should evolve our strategies as we go. But EIC employees are essential. Their fluency with technology, drive to learn, and creative edge are exactly what we need to build the future. We can’t afford to sideline them.

Committing to EIC talent will require a lot of hard work and vision, but with the right strategy, it is possible.

Jacqui Canney is chief people and AI enablement officer at ServiceNow.

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