AI is delivering much of what organizations hoped it would. Tasks that once required hours can now be completed in minutes. Documentation, research, testing, configuration assistance, and knowledge retrieval have become dramatically more efficient. 

From a productivity standpoint, that’s a remarkable achievement. But every major shift creates unintended consequences. One of the least discussed consequences of AI is its impact on how junior consulting talent develops. 

The Work Is Changing 

For decades, new consultants learned through contribution. They documented requirements. They built the applications – starting with easy configurations, working their way up to more complex solutions. They supported implementations. Participated in testing and training. Built foundational technical skills through repetition and exposure. Until eventually, they found themselves contributing to the solution design. 

These tasks weren’t simply operational work. They were how consultants developed judgment. Today, many of those activities are increasingly automated or accelerated. The efficiency gains are real. But so is the challenge it creates for developing new talent. 

When organizations eliminate the work that historically created learning opportunities, they must find new ways to create experience. Otherwise, they risk optimizing away the very activities that helped build future consultants. 

The New Talent Model Is Emerging 

At the same time, AI is lowering barriers to learning technical skills. Experienced professionals with deep industry or business experience can now acquire application and platform knowledge faster than ever before.  

Project, Product and Program managers. 

Business and Legacy System analysts. 

Operations leaders. 

Industry Segment experts (Contact Center, Retail, Healthcare, Manufacturing, etc). 

Change managers. 

These individuals often possess years—even decades—of experience navigating complex business environments. Yet many consulting firms and platform end users continue evaluating them primarily through the lens of platform tenure. As a result, highly capable professionals are frequently viewed as inexperienced because they are new to a specific technology stack. 

The Double-Edged Sword 

By limiting entry paths into the industry, we are creating pressure across the entire workforce ecosystem. Emerging consultants are unable to gain practical experience. Experienced professionals struggle to transition into consulting roles despite possessing highly relevant business expertise. Meanwhile, existing mid-level and senior consultants already in the industry are expected to carry increasing responsibility.  

They’re delivering projects, driving AI adoption, managing customer expectations, learning rapidly evolving technologies… but the one thing they are not doing is mentoring their replacement.  

Their burden continues to grow while the talent pipeline behind them constricts. 

The Real Risk 

The greatest risk isn’t a shortage of technology. It’s a shortage of people capable of translating technology into business outcomes. 

As organizations move from AI experimentation to enterprise-wide transformation, success increasingly depends on individuals who can connect technology, business processes, organizational change, and customer objectives. 

Those capabilities cannot be generated overnight. They must be developed intentionally. The future workforce challenge isn’t about replacing consultants with AI. It’s about redesigning how consultants become consultants. 

In the next blog, we’ll explore why the concept of “entry-level” no longer reflects the realities of an AI-powered workforce—and why the future belongs to a different descriptor entirely.