AI Won’t Just Impact Consulting: It Changes How to Engage Experts

Executive Editor Tim King discusses how Anthropic’s new AI consulting venture—backed by Blackstone and Goldman Sachs—signals more than disruption in professional services. It marks a fundamental shift in how expertise itself is created, distributed, and learned in the age of AI.

At the surface level, the story is straightforward. AI companies are no longer content to sell models alone. They are moving into the services layer, where the real enterprise value has historically been captured. Anthropic’s approach centers on embedding intelligence directly into workflows, allowing systems to act, adapt, and improve continuously inside the business rather than advising from the outside.

That is the disruption most observers are focused on. It is meaningful, and it will reshape the consulting landscape. But the more important implication sits beneath it.

The deeper shift is the collapse of retrospective expertise as the dominant model for learning and decision-making. Traditional consulting has always relied on accumulated knowledge. Even at its highest levels, it draws from past engagements, historical data, and generalized best practices. That model assumes stability. It assumes that what worked before will remain relevant long enough to be applied again. AI removes that stability.

In this environment, the core question changes. It is no longer about who has seen a problem before. It is about who is actively navigating it now.

This is where the real significance of Anthropic’s move becomes clear. By embedding AI systems and practitioners directly into operating environments, they are not simply delivering outcomes. They are creating continuous exposure to the current state of play. The value is not only in what the system produces, but in what organizations learn while those systems are in motion.

What emerges is a new model of learning that is already beginning to take hold across enterprise environments.

State-of-Play Learning Defined

• Learning derived from active, in-motion practitioners
• Insight generated in real time rather than retrospectively
• Continuous exposure to evolving systems and decisions
• Context-rich, situational knowledge instead of generalized frameworks

This model does not replace traditional learning in theory. In practice, it quickly becomes the dominant form because it aligns with the speed and complexity of AI-driven change.

The implications extend well beyond consulting. They reshape how leaders build judgment, how organizations develop capability, and how expertise itself is valued. Insight is no longer something acquired periodically and applied later. It is something developed continuously through proximity to execution.

This is precisely the gap that peer-driven models are beginning to fill, and it is the foundation behind Mesh Expert Groups. While AI firms like Anthropic are embedding intelligence into systems, Mesh is embedding leaders into environments of shared, real-time experience. The objective is not to deliver static knowledge or retrospective advice. It is to create structured proximity to transformation as it happens.

Where Mesh Expert Groups Fit

This approach reflects a broader shift in how organizations must think about capability development. The most effective learning environments are no longer content libraries or one-time engagements. They are dynamic networks that evolve alongside the technology and the challenges it creates.

For organizations, this means rethinking how expertise is sourced and applied.

• External advisory alone is no longer sufficient
• Static training models cannot keep pace with AI evolution
• Continuous access to real-world execution becomes critical

For individual leaders, the shift is just as pronounced. The advantage will not come from consuming more information. It will come from positioning as close as possible to real-time transformation and learning directly from those operating within it.

Anthropic’s move may be framed as a challenge to the consulting industry, but its broader significance is harder to ignore. It represents a redefinition of how expertise is created, how it flows, and how it is learned.

And in that world, the most valuable insight will not come from those who can best explain the past. It will come from those closest to the state of play.

Anthropic’s Move, Defined

• Anthropic is launching an AI-native consulting venture valued at approximately $1.5 billion
• Backed by Blackstone, Goldman Sachs, and Hellman & Friedman
• Designed to embed AI systems directly into enterprise operations
• Focused on execution, not advisory or slide-based strategy
• Positioned to compete with firms like McKinsey & Company, Bain & Company, and Accenture