AI is quietly replacing McKinsey consultants and no one is ready

AI is stepping into McKinsey’s shoes

AI agents are starting to mimic the work of McKinsey consultants, and developers are sharing these abilities openly. From problem-solving to creating slides, AI can now replicate much of the classic consulting workflow directly in your browser.

This shift is powered by open-source libraries like Vercel’s “skills” repository, which hosts tens of thousands of reusable capabilities. Some of these skills are explicitly modeled after consulting methods, making AI more than just a tool; it’s becoming a digital consultant.

Open-source skills are changing the game

Vercel’s library alone has nearly 90,000 skills for AI agents, from coding and copywriting to consulting-style analysis. These can be plugged in without retraining the model, making it easy for anyone to give AI consultant-like abilities.

The most popular consulting skill, labeled “McKinsey consultant,” guides AI through structured problem definition, hypothesis generation, and slide creation. Developers are installing it hundreds of times each week, showing serious traction in the business world.

AI can’t fully replace judgment yet

Despite its growing capabilities, AI lacks a core element of consulting: asking the right questions. Human consultants clarify thinking, uncover assumptions, and ensure deep insights through conversation, which AI agents still struggle to replicate.

Former McKinsey staffers note that AI performs boilerplate analysis well but cannot match the Socratic questioning and nuanced understanding that human consultants bring to the table. The AI slide deck is impressive, but judgment remains the key differentiator.

AI-driven consulting startups are emerging

Startups like PromptQL are building AI analysts that integrate a company’s internal data with foundation models. These tools aim to perform tasks traditionally done by data scientists and engineers while continuously learning and adapting to real-world environments.

By automating routine analysis and data integration, these AI tools can save companies time and money. However, the key challenge remains: understanding relationships between people, data, and revenue to deliver meaningful insights.

The moat is context, not code

McKinsey teams spend weeks embedded in client companies to understand internal nuances, from tribal knowledge to department-specific definitions. AI may crunch numbers, but it struggles to grasp these subtle, context-rich details that make consulting advice valuable.

PromptQL tries to bridge this gap with a shared understanding layer. Every correction or clarification from a team member is permanently integrated, allowing AI to learn context over time, something conventional AI agents usually miss.

Little-known fact: McKinsey & Company operates in over 65 countries and advises thousands of the world’s largest corporations.

Skills libraries are rapidly expanding

After Anthropic introduced “skills” for Claude, thousands of skills have been built and shared. Developers now have access to plug-and-play frameworks that cover a range of consulting tasks, making AI adoption faster than ever.

Business Insider identified dozens of skills explicitly labeled with “consultant” or “McKinsey.” While popularity varies, these frameworks demonstrate that AI is moving into areas once reserved for human strategy experts.

AI is still learning human nuances

Internal definitions, team-specific terminology, and subtle exceptions remain tricky for AI. Unlike humans, models don’t automatically grasp company culture or conflicting interpretations, which limits the depth of their advice.

Developers are experimenting with AI that learns through interaction, but full contextual understanding is still a work in progress. The consultant’s judgment is the hard part AI is just beginning to tackle.

AI skills libraries are democratizing consulting

Open-source skill libraries like Vercel’s make consulting-style analysis accessible to anyone with a browser. You no longer need expensive firm access to generate structured problem-solving frameworks or data-driven slide decks.

This trend could reshape how companies approach strategy, letting smaller businesses tap into techniques previously reserved for top consulting firms. It’s a major shift in the distribution of consulting knowledge.

AI adoption is growing despite limits

Even though AI cannot yet replicate human judgment fully, consulting-related skills are seeing consistent installs and GitHub stars. This indicates developers and businesses are actively experimenting with AI agents for practical consulting tasks.

These early adopters are laying the groundwork for a more automated consulting future, where AI assists humans in repetitive analysis, letting humans focus on critical thinking and strategic decisions.

Little-known fact: The global AI market is projected to reach over $390 billion by 2026, showing how quickly businesses are adopting AI technologies.

Enterprise AI tools face a grounding challenge

AI agents often fail because they lack grounding in company-specific context, like internal definitions or team workflows. Without this grounding, even skilled AI can produce inaccurate or misleading insights.

Platforms like PromptQL try to solve this by letting AI learn from interactions and corrections. The knowledge gained is permanent and shared across the team, slowly building a context-aware AI consultant that gets closer to human-level judgment.

As voice assistants evolve, Apple is reportedly considering OpenAI or Anthropic to power the next generation of Siri, exploring what this could mean for users.

The future of consulting is hybrid

AI agents and human consultants are likely to work side by side, combining automated analysis with judgment and strategic thinking.

Ignoring AI in consulting could leave companies behind. Even partial adoption of these tools can reduce reliance on expensive consulting hours while still benefiting from structured problem-solving and data-driven insights.

This hybrid approach can speed projects while maintaining the depth of insight traditional firms provide.

As questions about tech oversight continue, Microsoft confirms it will no longer involve Chinese engineers in Pentagon projects, explaining a major policy shift.

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This slideshow was made with AI assistance and human editing.

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