The Next Phase Of Enterprise AI: Why LLM Consolidation Is Inevitable

InnovationThe Next Phase Of Enterprise AI: Why LLM Consolidation Is InevitableByMayur Khandelwal,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 20, 2026, 08:00am EDTMayur Khandelwal is a Vice President at EXL, where he leads the Data and AI Practice for Life & Annuities and Group Benefits insurance. getty​Every quarter, I sit across from senior executives at major enterprises who are asking the same question, just with increasing urgency: Which AI model should we bet on?It's a reasonable question and an exhausting one. The large language model (LLM) market today presents a paradox: The abundance of choice has become its own form of risk. At last count, enterprises could select from dozens of commercially available foundation models, spanning OpenAI, Anthropic, Google, Meta, Mistral, Cohere and a growing list of regional and domain-specific entrants. According to a 2025 survey by Global Market Insights, the top five providers—Anthropic, AWS, Google, Microsoft and OpenAI—collectively held 78% of the enterprise LLM market share in 2024, a figure that signals the beginning of concentration, not the end of fragmentation.Additionally, a 2025 Andreessen Horowitz analysis found that 37% of enterprises now run five or more models in production simultaneously. And a Menlo Ventures 2025 report noted that enterprise LLM API spending more than doubled from $3.5 billion to $8.4 billion in less than a year. Organizations are spending faster than they're strategizing, and the multimodel complexity is catching up with them.I've watched this pattern play out in regulated industries particularly sharply. When every business unit is free to procure its own model, you end up with fragmented governance, inconsistent outputs and data residency risks that no compliance team signed off on. The sprawl looks like optionalit...