After the Layoffs: What Will AI Agents Inherit?

Is there anyone who believes that AI agents will eventually do the jobs of employees who have been laid off recently?

We are experiencing many layoffs today, partly driven by expectations that AI will make work more cost-efficient and help employees complete tasks faster. Some leaders and investors believe that increasingly capable AI systems will take over a growing share of work.

The problematic part

Several organizations are approaching AI while still carrying operational problems from previous transformation programs.

Even large programs leave behind fragmented processes, unclear ownership, workarounds, inconsistent controls, and activities that depend heavily on individual knowledge rather than well-defined ways of working.

In those situations, AI does not solve the underlying problems, but, in most cases, AI agents expose and amplify them.

We strongly believe in automation, simplification, and the elimination of low-value or repetitive tasks.

Our vast experience from the past decade working on large transformation programs still leads me to focus on the following question:

How can AI agents create sustainable value?

Organizations first need a clear view of how they want to operate in the future. That means defining the target operating model, understanding process ownership, establishing governance, determining how automated components will execute parts of the workflow, and deciding how people and technology will work together.

The knowledge work challenge

Current AI systems are becoming increasingly capable. They perform best when you understand, manage and design processes with clear objectives and appropriate governance.

Organizational readiness matters

The question is not whether AI agents can perform tasks. The more important question is whether the organization is ready to absorb and operationalize those capabilities in a way that creates business value.

Without that foundation, there is a risk that organizations simply add another layer of technology onto existing complexity rather than achieving the efficiency gains they are seeking.

The importance of leadership

As AI adoption accelerates, strong leadership and sober human thinking are needed to distinguish between what AI can demonstrably do today, what the company's objectives and operations actually require, and where AI agents can become a strong component of process and organizational improvement.