The AI Mandate - A Comedy of Errors in the Fortune 500
- Cameron Price
- Mar 6
- 4 min read
Imagine this: A Fortune 500 CEO, whose expertise lies in navigating market trends, managing investor expectations, and maximizing shareholder value, receives a directive from the board—"We need to do something with AI."
The board itself, a collection of seasoned executives and financial experts, has little to no understanding of AI beyond headlines promising revolutionary efficiencies, unprecedented automation, and existential risk. But they know one thing: their competitors are "doing AI," and so should they.
The CEO, now under pressure, turns to the natural solution—consultants. These consultants, eager to capitalize on the AI gold rush, present themselves as AI experts. But, in reality, they often have no actual AI experience beyond generic PowerPoint decks and a few buzzword-heavy LinkedIn posts.
The Great AI Consultancy Theater
What follows is a predictable script:
Phase 1: AI Strategy Kickoff – The consultants hold a series of workshops filled with phrases like "low-hanging fruit," "quick wins," and "AI maturity models." No one in the room asks fundamental questions like "What is AI?" or "How does it actually work?" Instead, the focus is on aligning "business objectives with AI capabilities," which, in practice, means listing generic use cases like "AI-powered customer insights" and "automated decision-making’”
A study by Emergn found that many senior executives view major consulting firms as ineffective in corporate transformation projects, suggesting that this trend extends to AI strategies as well (The Times).
Phase 2: The AI Report – After weeks (or months) of research—mostly Googling case studies, benchmarking competitors, and repackaging vendor marketing materials—the consultants produce a glossy, 100-page report. The report is rich in executive-friendly terminology but devoid of any real technical or operational roadmap. It suggests AI-driven transformation but conveniently avoids specifying how to actually implement AI in a meaningful way.
A report by MIT Sloan Management Review indicated that 70% of companies reported minimal or no value from their AI investments, often due to ineffective strategy implementation (MIT Sloan).
Phase 3: The AI Pilot (a.k.a. The POC to Nowhere) – The company funds a small proof of concept (POC), often a chatbot or predictive analytics tool, neither of which solve core business problems. It is handed off to an IT department already stretched thin. The pilot shows some promise but fails to scale, and by the time anyone realizes it’s going nowhere, the consultants are long gone—with their invoices paid in full.
Phase 4: The AI Hangover – A year later, the CEO reports to the board that AI initiatives are "ongoing." There's little to show for the significant amount of capital spent, but the executive team maintains that AI is still a "strategic priority." A new round of consultants is hired to "reassess the AI strategy," and the cycle repeats.
A survey of Fortune 500 companies found that over 56.3% now list AI as a "potential risk" in their SEC filings, illustrating growing skepticism about AI initiatives delivering results (Yahoo Finance).
Why This Keeps Happening
This pattern persists because AI is not just a technology—it’s a hype machine. We experience a similar cycle during the “big data” era a few decades ago. Boards and executives feel the pressure to act, even if they don’t understand what they’re acting on. The consulting industry thrives in this knowledge gap, repackaging the same AI narratives without real expertise or implementation experience.
Boston Consulting Group (BCG) expects AI-related consulting to generate over 20% of its revenue in 2024, reinforcing how AI hype fuels the consulting industry (Financial Times).
Meanwhile, actual AI practitioners—data scientists, engineers, and architects—watch from the sidelines as decisions are made at the top without foundational understanding.
A McKinsey Global Institute report revealed that 45% of consulting work could already be automated using existing AI technology, which ironically suggests consultants advising on AI could be disrupted by AI itself (McKinsey).
Breaking the Cycle
So how can companies avoid the "AI theater" trap?
Start with Education, Not Implementation – Before investing in AI, boards and executives need to understand what AI actually is, what it isn’t, and where it can drive real value. Internal AI literacy should be a priority.
A BCG survey found that only 28% of organizations feel prepared for AI regulations, demonstrating a widespread knowledge gap at the leadership level (BCG).
Identify Real Business Problems, Not Just AI Use Cases – AI should be a tool for solving specific, high-impact business problems—not a vague mandate to "do something with AI."
A report by Atlassian emphasizes the importance of setting specific goals for AI integration, such as streamlining task automation and enhancing project planning, to ensure AI delivers tangible value (Atlassian).
Hire Practitioners, Not Just Consultants – Bringing in AI talent who can build and deploy real models is critical. If external consultants are needed, they should be vetted for actual AI experience, not just strategy expertise.
Microsoft highlights the necessity of assembling a cross-functional team—including IT specialists, data scientists, and business experts—to ensure AI projects are technically sound and aligned with business objectives (Microsoft).
Pilot with Purpose – Instead of launching aimless POCs, companies should start small with clearly defined success metrics and a path to production.
According to CIO.com, defining a comprehensive AI strategy that connects to broader business objectives is essential for successful AI implementation (CIO).
Hold Leadership Accountable – Boards should demand clear, measurable AI outcomes, not just presentations filled with jargon.
Final Thought
AI isn’t magic, but the illusion of AI expertise is a powerful business force. Until Fortune 500 executives and boards take AI seriously—not just as a buzzword but as a discipline requiring deep expertise—the cycle of empty AI mandates will continue. The real winners? The consultants, cashing in while AI remains a corporate mirage.
Join a Data Conversation,
Cameron Price.
References:
The Times – Emergn Study
MIT Sloan – AI Investment Report
Financial Times – BCG AI Revenue
McKinsey AI Report
BCG AI Regulations Survey
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