Why 'Consultant' and 'Admin' Have Lost All Meaning in the AI Era (And What We Should Use Instead)

I saw a LinkedIn post recently that stopped me in my tracks.

A transformation expert was fighting against everything people assume when they hear "consultant":

"Most people hear 'consultant' and picture one of three things:

->A strategist who disappears after the kickoff

→ A deck machine that never gets near implementation

→ A senior face who hands off to a junior bench"

His frustration was palpable: "That's not how we work."

But here's what struck me most—he had to spend his entire post explaining what he's NOT instead of clearly communicating what he IS.

That's the labeling crisis facing businesses during the AI era.

The Words That No Longer Work

Here's the challenge: traditional business titles have grown to encompass so much expertise that they've lost their ability to communicate specific value.

When someone says they're a "System Administrator," it could mean:

• Strategic systems architect designing value flow optimization
• Data specialist analyzing performance across business functions
• Workflow expert automating complex organizational processes
• Technical problem-solver handling systems integration challenges
• Configuration specialist managing routine maintenance tasks

All incredibly valuable work—but impossible to distinguish from the title alone.

The same evolution has happened with "Business Consultant":

• Strategic advisor focused on sustainable transformation planning
• Hands-on implementer who stays until systems optimize value creation
• Training specialist who builds lasting team capability
• Technical expert solving complex integration challenges
• Process optimizer who removes barriers to natural value flow

Each represents genuine expertise and professional dedication. The challenge isn't the quality of work—it's that the labels no longer help organizations find the right expertise for their specific value creation needs.

The Cost of Confusion

This labeling crisis hurts everyone:

For Experts, it means:

• Fighting against negative assumptions instead of communicating value
• Spending positioning energy on what you're NOT rather than what you ARE
• Competing in a race to the bottom because roles seem interchangeable
• Constantly explaining your actual approach and methodology

For Organizations, it means:

• Guessing what kind of help you're actually getting
• Disappointment when expectations don't match reality
• Difficulty finding the right expertise for specific value creation challenges
• Paying for unclear value propositions

For the Business Ecosystem, it means:

• Professional stagnation as everyone fights for the same meaningless labels
• Quality perception problems when labels don't guarantee capability
• Missed opportunities for specialization and collaboration
• Confusion that slows adoption of value-optimizing approaches

The AI Era Makes This Worse

Here's what's changed: AI can now handle much of what we traditionally referred to as "business improvement work."

• Building automation workflows? AI can do that.
• Creating performance reports? AI handles it.
• Setting up basic integrations? AI's got it covered.
• Configuring standard processes? AI does it faster.

But AI can't:

• Design system architecture that enables natural value flow without your business context
• Lead transformation that requires human change management and relationship building
• Deliver learning experiences that build lasting team capability for value optimization

The problem is that our current labels fail to distinguish between work that AI can do and work that requires uniquely human expertise in value creation.

When someone says "System Administrator," are they talking about routine maintenance that AI can handle, or strategic systems thinking that requires human insight into value flow optimization?

When someone says "Business Consultant," are they offering generic analysis that AI can generate, or p artnership through complex transformation that requires human judgment about value creation?

You can't tell—and that's the problem.

What We Need Instead

The collaboration economy—where experts succeed by working together to create and multiply value rather than competing to extract it—requires professional categories that immediately communicate value creation capability.

We need labels that tell you:

• What kind of value this expert actually creates
• How they approach client relationships and transformation outcomes
• What specific capability you can expect to receive
• How they collaborate with other experts when comprehensive solutions require multiple types of expertise

Most importantly, we need categories that reflect the AI era reality: humans focus on uniquely valuable work that enables natural value flow while AI handles routine implementation.

The Path Forward

It's time to evolve beyond "Consultant" and "Admin" for business transformation.

The business ecosystem deserves professional categories that:

• Communicate value immediately without requiring explanation
• Distinguish human expertise from AI-automatable tasks
• Enable natural collaboration between complementary experts
• Build client confidence through clear expectations about value creation

Three Categories for the AI Era

I believe we need three distinct professional categories that capture how expertise creates value when AI handles routine implementation:

The Value-First Architect designs business systems that enable the natural flow of value over the long term. While AI can build anything quickly, Architects determine what should be built, how it should integrate with business models, and why this approach creates sustainable value multiplication. They ensure implementation success through strategic design and hands-on oversight.

The Value-First Coach guides transformation that actually transforms how value moves through organizations. Instead of creating strategies and disappearing, Coaches partner with teams through entire change journeys, building internal capability while ensuring value optimization results are achieved and sustained.

The Value-First Educator turns expert knowledge into systematic learning that scales value creation capability. Rather than generic content creation, Educators design learning experiences from proven value flow optimizations, working with teams until they can confidently apply value-first thinking to their specific business challenges.

Each category immediately communicates what kind of value you'll receive, how the expert approaches their work, and how they collaborate with others when comprehensive transformation requires multiple types of expertise.

Why This Solves the Collaboration Challenge

These categories naturally enable the collaboration economy because they're designed around complementary value creation rather than competitive positioning:

• Architects excel at designing systems that enable value flow
• Coaches excel at guiding human adoption and optimization of those systems
• Educators excel at building capability that sustains and evolves value creation

When an organization needs comprehensive transformation, these experts naturally collaborate rather than compete, because each contributes unique value that multiplies the others' impact.

The AI Partnership Advantage

Notice how each category positions AI as partner rather than threat:

• Architects use AI to handle implementation while focusing on strategic design
• Coaches use AI to generate analysis while focusing on human partnership through change
• Educators use AI to create content while focusing on learning architecture that builds capability

This reflects the Value-First principle that AI should multiply human capability, not replace it.

Beyond Business: Universal Application

While these categories emerged from business transformation challenges, they apply to any field where:

• AI can handle routine implementation
• Human expertise creates unique value through strategic thinking
• Collaboration multiplies impact better than competition
• Value creation requires both technical capability and human partnership

Whether you're working in healthcare, education, manufacturing, technology, or any other field facing AI-era transformation, these categories can clarify how human expertise creates value that AI amplifies rather than replaces.

The Implementation Reality

Organizations using these categories report:

• Clearer hiring decisions because they know exactly what expertise they're getting
• Better project outcomes because expectations align with capabilities from the start
• Natural expert collaboration because categories complement rather than compete
• Reduced vendor confusion because value propositions communicate clearly
• Faster transformation because the right expertise gets applied to the right challenges

Is This Evolution Inevitable?

The business world is already moving toward these distinctions. Successful professionals are naturally specializing into architectural thinking, coaching partnerships, or capability building.

The question isn't whether professional categories will evolve—it's whether we'll consciously guide that evolution toward clarity that serves everyone.

The Future of Professional Value

Because the experts in our business ecosystem deserve better than fighting against meaningless labels.

And the organizations we serve deserve clarity about the value they're receiving.

The AI era demands professional categories that reflect how humans create unique value in partnership with artificial intelligence, not in competition with it.

The collaboration economy requires labels that enable natural partnership between complementary experts rather than forcing artificial competition for unclear positioning.

And value-first transformation needs categories that immediately communicate capability for enabling natural value flow rather than requiring lengthy explanations of what you're NOT.

What's your experience with unclear professional labels in business transformation? Have you found yourself explaining what you're NOT instead of clearly communicating what you ARE?

Let's start a conversation about evolving our professional categories for the AI era—categories that enable collaboration and clearly communicate the unique value humans provide in partnership with artificial intelligence.