API sprawl and application proliferation have grown faster than organizations can understand, govern, or cost what has been built, creating hidden liabilities. Generative AI spending is now intensifying the same foundational reckoning at a faster pace. The shift resembles early cloud migration, where companies with strong engineering foundations, clear domain-driven architectures, and psychologically safe, agile cultures transitioned more smoothly. Organizations lacking these capabilities flounder. Difficulty accounting for AI spend is tied to a long-running divide between engineering and business, where requirements are thrown over the wall and teams lack a shared language. Without visibility and alignment, companies build on unstable foundations and struggle to connect technical work to customer outcomes.
"As a result, engineers struggle to articulate technical challenges in a way that business stakeholders understand, and vice versa. I go into a lot of business groups that don't know what their engineers are saying or doing, or have any bridge to connect the dots, Lane said."
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