The Complexity Tax: Why Enterprise AI Stalls Before It Starts

InnovationThe Complexity Tax: Why Enterprise AI Stalls Before It StartsByMurali Swaminathan,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)May 29, 2026, 11:15am EDTMurali Swaminathan is the Chief Technology Officer at Freshworks. gettyEvery major technology wave lands on top of whatever was already there. The internet landed on client-server architectures that weren't built for it. SaaS landed on on-premise procurement cycles that didn't know what to do with it. Cloud landed on security models designed for data centers. ​AI is landing on all of it at once, and the foundation can't absorb the weight.​I've been building enterprise software through every one of those transitions. The pattern is remarkably consistent. The constraint has never been the technology itself, but the complexity underneath it. This is called the complexity tax: the invisible cost organizations pay, cycle after cycle, to keep systems stitched together well enough to function. AI doesn't create the tax, but it makes the bill impossible to ignore.​How The Tax Accumulates​Complexity tax rarely traces back to a single bad decision. It builds through a series of reasonable ones.​A support team picks a ticketing tool that solves a real problem. IT adopts a different platform for internal requests. Finance runs a third system for approvals. Each system works fine on its own. But eventually the business expects them to work together, so teams start stitching integrations across them: API calls, middleware, manual handoffs and the CSV export someone still runs every Tuesday morning.​​The weight grows so gradually that teams stop noticing it. But if an AI agent is introduced and needs to operate across those systems—verifying identity in one, checking policy in another, executing an action in a third and logging the result in a fourt...