AWS CEO Matt Garman believes AI will fundamentally change how people work, not wipe out employment entirely. While some industry leaders predict AI could eliminate half of all entry-level white-collar jobs within five years, Garman argues that technology historically destroys individual positions but creates new ones. To back up his optimism, Amazon is hiring 11,000 interns and new graduates this year, even as the company has cut roughly 30,000 corporate jobs since last October.

Garman, who joined Amazon as an MBA intern in 2005 before AWS even launched, has a unique vantage point on the AI economy. He became CEO of AWS in June 2024, overseeing a roughly $130 billion-a-year business that sits underneath much of the AI boom. AWS is the primary training partner for Anthropic, has signed compute deals with OpenAI worth up to $100 billion, and this year plans to spend some $200 billion on capital expenditures, the bulk of it on AI infrastructure.

The tension between Garman's optimism and Amazon's own workforce reductions is striking. Last year, Garman called replacing junior employees with AI "one of the dumbest things I've ever heard," and told Wired that never hiring junior people is a "non-starter for anyone trying to build a long-term company." Yet Amazon's CEO, Andy Jassy, has written that AI will "reduce our total corporate workforce" in the years ahead, with plans to replace half a million jobs with robots.

Why Is AI Adoption Happening Faster Than Previous Tech Shifts?

Garman points to a crucial difference between the AI revolution and the cloud computing shift he witnessed over the past two decades. When AWS launched, it took 20 years for most workloads to migrate from on-premises data centers to the cloud. AI adoption, by contrast, is moving at a dramatically accelerated pace. Garman explained that businesses no longer feel they have 20 years to prepare for AI; instead, they believe they have roughly 20 months.

Two factors are driving this acceleration. First, the cloud and AI are complementary technologies that compound each other's impact. Without cloud infrastructure, AI models couldn't scale as quickly or be deployed as easily. Second, competitive pressure is intense. Companies fear falling behind if they don't adopt AI tools rapidly, creating a sense of urgency that didn't exist during the cloud transition.

How to Prepare Your Career for AI-Driven Workplace Changes

• Embrace continuous learning: Garman emphasized that the most durable skill is a simple willingness to learn. If your job today looks vastly different from what it will be in two years, adaptability becomes your greatest asset.
• Develop complementary skills: Rather than competing directly with AI tools, focus on skills that work alongside them. Understanding how to use AI agents and software tools will become as essential as learning Excel was in previous decades.
• Seek roles that combine human judgment with AI capabilities: Amazon is building software that does white-collar work, including a developer agent, a security agent, an "agentic teammate" suite called Q Business, and an AI recruiter called Amazon Connect Talent. Jobs that combine human oversight with AI execution will likely be in high demand.

Garman's argument mirrors a historical pattern. Excel eliminated jobs for people who calculated by hand, but those workers learned to use computers, and the overall labor force expanded. He believes AI will follow a similar trajectory, though the speed of change will be much faster than previous technological transitions.

What Do Enterprise Customers Actually See From AI Investments?

From his position running AWS, Garman has a window into what enterprises are actually doing with AI. He noted that almost everyone is experimenting with AI, but the results vary widely. Some companies have run early experiments without seeing huge returns on their investment, while others are beginning to figure out how to deploy AI effectively in their operations.

This variation suggests that the AI opportunity isn't automatic. Companies that simply apply new models to old processes may not see meaningful gains. Those that fundamentally rethink workflows and business processes, however, are discovering genuine competitive advantages. The difference between success and failure often comes down to whether organizations view AI as a tool to speed up existing work or as a catalyst for reimagining how work gets done.

"Wipe out and change are different things," Garman said when pressed on predictions that AI could eliminate half of all entry-level white-collar jobs within five years.

Matt Garman, CEO of AWS

Garman's optimism doesn't mean job displacement won't happen. Amazon's own moves suggest significant workforce reductions are coming. But his argument is that the net effect of AI adoption will be job transformation rather than net job destruction. The challenge for workers, companies, and policymakers is managing that transition period when some roles disappear faster than new ones emerge. For now, Amazon's decision to hire 11,000 interns and junior employees suggests the company is betting that new opportunities will indeed materialize.