Full Breakdown
The Rise of AI in Consulting: Mimicking McKinsey's Approach
3/20/2026, 11:39:06 PM
The Emergence of AI Consulting Tools
In recent years, artificial intelligence (AI) has begun to transform the consulting landscape, with tools designed to replicate the methodologies of established firms like McKinsey & Company. Vercel, an AI startup valued at over $9 billion, has introduced a "skills" library that includes nearly 90,000 reusable skills for AI agents. Among these, at least four skills are labeled with the term "McKinsey," and 26 are categorized as "consultant." The most popular of these, titled "mckinsey-consultant," has gained traction, averaging 445 installs per week since its launch on January 25.
How AI Mimics Consulting Practices
The "mckinsey-consultant" skill is designed to guide AI through processes such as defining problems, generating hypotheses, conducting structured analysis, and creating presentations, effectively mimicking the workflow of a traditional McKinsey consultant. This innovation follows the introduction of "skills" by Anthropic for its chatbot Claude, which has inspired developers to create and share thousands of similar capabilities.
Critique of AI's Consulting Capabilities
Despite the growing popularity of AI tools, experts argue that they fall short of replicating the true value provided by human consultants. Arvind Vasudevan, a former McKinsey employee, emphasized that AI agents lack the essential ability to engage in Socratic questioning and deep conversations that clarify thinking and uncover unstated assumptions. He noted that the AI's analysis often amounts to boilerplate responses rather than the nuanced insights that characterize human consultants.
The Business Impact of AI in Consulting
Companies like PromptQL, an AI enterprise platform co-founded by Tanmai Gopal, are already generating significant revenue by offering AI-driven analysis. PromptQL enables clients to build custom AI analysts that integrate internal data with existing foundation models. Gopal highlighted that the primary challenge for AI tools is understanding the intricate relationships between people, data, and revenue within organizations. He pointed out that traditional consulting firms like McKinsey spend considerable time embedded within client companies to grasp their unique operational contexts, which is crucial for delivering valuable advice.
The Limitations of Current AI Models
Gopal further explained that many enterprise AI tools fail because they lack contextual grounding, often making assumptions rather than asking clarifying questions or learning from feedback. He argued that the real value of consulting lies not in the deliverables, such as slide decks, but in the judgment and contextual understanding that human consultants provide. As AI continues to evolve, it must overcome these contextual limitations to become a more effective substitute for traditional consulting practices.
What's Next for AI in Consulting?
As AI technology advances, the consulting industry may see further integration of AI tools that strive to bridge the gap between automated analysis and the nuanced understanding that human consultants offer. The ongoing development of AI capabilities will likely shape the future of consulting, challenging traditional models while also highlighting the irreplaceable value of human insight.
