AI concepts in a generic sense will never support how I can help a consulting firm move from a 20m valuation to a 50m valuation in five years. Concepts do not tell me what the what the company should do, when the company should do it, and why the company should do it. Thirty years of experience as a CPA (inactive), JD, and a business advisor have taught me that transformative changes in business value are seldom driven by P&L results.
The far more important number is the sales multiple and the most important drivers of the sales multiple are earnings quality, sustainable competitive advantage, and recurring revenue. A company cannot automate its way to prosperity. A company cannot automate back office functions or utilize publicly available service delivery tools to drive their business multiple.
We did not guess at what types of initiatives would drive the business multiple. We developed and pressure tested four different models that basically achieved the same result. More importantly, they helped us isolate and quantify where the vast majority of value is hidden and they surfaced the path for unlocking the hidden value. Value increases are primarily due to AI deployments that create structural advantages over competitors.
Over the past two years, nearly every major consulting organization has introduced a framework designed to help companies measure the return on AI investments. McKinsey speaks about organizational agility and decision velocity. PwC focuses on transformation readiness and AI maturity. Deloitte emphasizes enterprise reinvention and operating model evolution. KPMG discusses long-term capability creation and strategic adaptability.
At a conceptual level, the concepts are sound. The business logic is strong. It just does not explain what types of transformative change needs to happen to create transformative value.
The majority of AI ROI models in the market speak in terms of contextual improvements rather than direct causation of financial outcomes. They evaluate adoption, workflows, acceleration, collaboration, knowledge sharing, and employee productivity. Those measurements can certainly indicate that an organization is becoming more efficient. However, efficiency alone does not necessarily translate into enterprise value. This distinction matters far more than most organizations realize.
A professional service firm may reduce proposal time by 40%. A second firm may dramatically accelerate cross-function decision making. A third firm may implement AI powered knowledge systems that make tribal knowledge transparent. In each case, the operations are better than they were. They just bear no relationship to rapid business growth.
Every AI implementation initiative should answer the following questions. Are earnings more sustainable and more predictable moving forward? Does it drive structural advantages over competitors? Do the structural advantages create pricing power? How will the pricing power be used? Will the company raise prices to drive re-investable cash flow? Will the company reduce prices to weaken competitors? These are the most important questions and they need to be asked before the initiative begins.
The challenge for the large consulting firms is that AI is not like a traditional capital investment. ROI calculations are generally easy because the investment and the benefits are easily traceable. A company purchased equipment, upgraded a manufacturing line, expanded a warehouse, or implemented a new ERP system. The financial effects could often be traced with reasonable precision.
AI operates very differently. It transcends each layer of an organization. It influences service delivery costs, the quality of revenues, the reduction of business risks, and the price the buyer would pay to acquire the business. The impact spreads across multiple functions at once, which makes direct attribution extraordinarily difficult.
As a result, many AI ROI discussions are typically based on concepts rather than math. Firms discuss strategic capabilities, organizational agility, cost reductions, and future readiness because value is much harder to isolate. Yet from an ownership or valuation perspective, these concepts are way to fuzzy to quantify.
This is where the conversation around AI ROI must evolve to be useful and transformative. The real issue is not whether AI improves productivity. The only important issue is whether AI initiatives maximize business value.
Take the 5-minute Multiple Gap Scorecard and see whether your AI investments are building enterprise value or just making you more efficient. Please DM me and I will send you a copy of the Multiple Gap Scorecard.