Amazon CEO Andy Jassy recently shared with employees his ambitious enterprise AI vision. A sweeping plan to deploy AI across products, services, and backend operations — promising faster invention, billions of AI agents, and dramatic efficiency gains.
And buried in that vision is a warning. As CEO Andy Jassy put it, as Amazon rolls out more Generative AI and agents, “we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.”
At the very moment Amazon urges employees to embrace AI, learn fast, and help redesign work — it’s telling them jobs will disappear. No map. No shared plan. Just responsibility pushed onto employees: Get curious. Train yourself. Find where you fit.
It’s a masterclass in how to undermine an enterprise AI transformation before it begins.
Enterprise AI Starts With People, Not Tech
Enterprise AI isn’t about replacing people. It’s about designing what only people can do.
And here’s the paradox: Only people can redesign the work. But they won’t do it — unless they see how they fit in the future.
Without trust, without a clear value proposition, without a shared vision of what work looks like in the AI-powered future, enterprise AI efforts will stall.
And the numbers show why. The PwC 2025 Global AI Jobs Barometer finds that industries best positioned to adopt AI have seen productivity surge, with revenue per employee growing three times faster than in industries slower to embrace AI. What’s driving these gains isn’t just isolated use cases or incremental automation. PwC’s analysis makes clear: the real performance leap comes when AI is treated as a catalyst for enterprise-wide transformation—rethinking how value is created, not just how tasks are executed.
In other words, if the goal is structural change that rethinks entire business functions, AI can’t be treated as an add-on. As Dan Priest, Chief AI Officer at PwC US, put it on The Future of Less Work podcast: “If you’re in the 5, 10, 15% efficiency range, that’s not structural. You need to be in the 30, 40% efficiency range before you can rethink how a function gets managed.”
Enterprise AI requires clean-sheet thinking. Leaders must resist the temptation of incrementalism and instead ask: If we were designing this work from scratch, with AI at the core, what would it look like?
But leadership can’t answer that question alone.
People Won’t Build The Future If They’re Not in It
It’s easy to think technology is the main challenge. It isn’t. The real challenge is human. The people who know the work — those who interact with customers, manage operations, and deliver services — are the ones best placed to redesign it. They see where the friction is, where AI can enhance, and where human judgment remains essential.
But here’s the paradox: to get them to help reinvent work, they have to believe they have a place in what comes next. Otherwise, why would they help design themselves out of a job? If employees fear AI is a cost-cutting tool aimed at replacing them, they will resist or quietly undermine the transformation. As Priest warns: “Don’t underestimate what people will do to undermine change if they don’t see a value proposition for them at the end of that journey.”
When AI is introduced purely as a cost-saving or headcount-reducing measure, it erodes the trust that is essential for success. The PwC report shows that the greatest benefits of AI come not from automation alone, but from empowering workers to create new value. This isn’t a story of workers being sidelined; it’s a story of workers being amplified by technology.
The Trust and Skills That Power Enterprise AI
Organizations that see AI only as a way to cut costs, reduce headcount, or drive productivity gains without regard for their people will undermine their own ambitions. When AI is treated only as a tool for cost-cutting, it limits its potential to what PwC calls thinking small — using AI to do old jobs faster or cheaper. The real power comes from thinking big: using AI to create entirely new capabilities, new business models, and new ways of delivering value. To do that, companies must bring their people along, not leave them behind.
That starts with trust. People need to trust that they have a future in the AI-powered organization. That trust is earned when leaders clearly define how AI augments human value rather than diminishes it — and when workers see themselves in the vision of the future. Without it, transformation efforts will stall, no matter how powerful the technology. As Priest put it, “The leaders who are most visionary and most articulate about what that evolving value proposition looks like will build the most trust in their workforce.”
And it continues with skills. People need the tools to work alongside AI — not just use it, but amplify their impact through it. Skills requirements in AI-exposed roles are evolving at a rate more than twice as fast as just a year ago. The jobs aren’t disappearing. They’re changing. And without intentional upskilling, workers won’t be able to keep pace, and companies won’t unlock AI’s full potential. Simply telling employees, as Amazon’s CEO did, to be curious and re-skill themselves isn’t enough. Organizations must share ownership of this transformation — actively equipping people for the roles AI makes possible.
The future of enterprise AI isn’t a choice between technology or people. It’s technology through people. If enterprise AI is going to deliver on its promise, leaders can’t just deploy systems — they must design the conditions where AI and people thrive together. That means creating a clear, shared map of where people fit in the future of work — and building that future with them, not leaving them to figure it out alone.
