When auditing firm KPMG tried to pay its own auditors less by claiming AI can automate their work, it sent a disastrous public signal. By arguing for the commoditization of its core service, KPMG accidentally announced to the world that its own business model is under direct threat from automation.

The assumption that AI will create trillions in corporate profit overlooks a key economic reality: only 1% of global GDP is profit above the cost of capital. Intense competition in AI will likely drive prices down, meaning the vast majority of economic benefits will be passed to consumers, not captured by a few monopolistic companies.

Beyond simple productivity gains, AI will eliminate the need for entire service-based transactions, such as paying for basic legal documents or second medical opinions. This substitution of paid services with free AI output can act as a direct deflationary headwind, a counterintuitive effect to the typical AI-fueled growth narrative.

While AI expands software's capabilities, vendors may not capture the value. Companies could use AI to build solutions in-house more cheaply. Furthermore, traditional "per-seat" pricing models are undermined when AI reduces the number of employees required, potentially shrinking revenue even as the software delivers more value.

Confusing credit-based AI pricing models will likely be replaced by a straightforward value proposition: selling AI agents at a fixed price equivalent to the cost of one human worker who can perform the work of ten. This simplifies budgeting and clearly communicates ROI to CFOs.

As agencies adopt AI to increase efficiency, clients will rightfully question traditional pricing models based on billable hours. This creates an "arbitrage" problem, forcing agencies to redefine and justify their value based on strategic insight and outcomes, not just the labor involved.

While law firms have an inherent conflict with AI due to the billable hour model, the push for adoption is coming from their clients. Corporations are now sending formal requests to their legal counsel, requiring them to use AI tools for efficiency and cost savings, thereby forcing the industry to adapt despite its traditional economic incentives.

Marks questions whether companies will use AI-driven cost savings to boost profit margins or if competition will force them into price wars. If the latter occurs, the primary beneficiaries of AI's efficiency will be customers, not shareholders, limiting the technology's impact on corporate profitability.

When formal data and anecdotes about AI's impact disagree, trust the anecdotes. Reports of clients like KPMG demanding lower fees from auditors due to AI are a stronger leading indicator of economic shifts than broad surveys showing no productivity gains. These isolated incidents signal the beginning of a widespread market transformation.