AI Changes the Org Chart. What Makes People Valuable?

AI can change the tasks in a company and the structure built around them. On Schwab Network’s NextGen Investing, Matt Britton examines what that means for employees, leadership and the choices facing established technology businesses.

He argues that identifying a worthwhile problem becomes more valuable as tools take on rules-based work. The discussion asks how people can apply critical thinking and build with AI, and how leaders can recognize that contribution inside their organizations.

He introduces the concept of capital rotation. AI is concentrating power in large technology companies that are aggressively automating. Companies like Amazon are reducing headcount and flattening corporate structures. Even when leadership attributes layoffs to “organizational layers,” Matt argues that AI is what enables those layers to disappear. AI agents can move information, make decisions, and execute workflows that once required entire management tiers.

He also highlights what comes next: robotics integrated with AI. When intelligent software becomes embedded into physical systems, companies like Amazon could see unprecedented gains in operational efficiency.

For smaller companies without mega cap resources, Matt makes a pointed argument. Capital is not the limiting factor. Understanding AI and having bold leadership is. He suggests many corporate leaders are managing for personal safety rather than transformation. Founder led companies and decisive CEOs, such as those repositioning their businesses around AI agents, are more likely to survive the shift.

The conversation moves to risk at both the employee and enterprise level. Workers trained to “color inside the lines” face automation risk. Strategic thinkers who understand how to build and deploy AI systems will command outsized value.

At the company level, Matt describes a high stakes environment. Established software firms like Adobe face an innovator’s dilemma: defend legacy subscription revenue or reinvent around AI driven products. Adobe’s rollout of tools like Firefly expands its addressable market, but lowers barriers to entry, intensifying competition from upstarts like Canva. The outcome remains uncertain, and that tension defines the broader SaaS sector.

The discussion concludes with Google as a case study. With a growing number of consumers using AI chat interfaces instead of traditional search, Google must balance protecting its core algorithm driven model while accelerating AI powered experiences. That strategic conflict mirrors the challenge facing many legacy tech leaders today.

The discussion leaves leaders with decisions about people, processes and products. Where can AI improve the work? Which capabilities should an organization build? And how can a business respond while giving its people a clear understanding of their role?

‍