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The following article is authored by Neil Dhar, Senior Vice President, IBM Consulting Americas
Next week at Think 2026, we'll outline the forces shaping the Enterprise AI Race, forces that apply with particular urgency to private equity. The organizations gaining ground today are not the ones betting on a single model. They are the ones redesigning how their businesses operate, building hybrid architectures that give them control, and deploying AI in ways that orchestrate value that compounds over time.
The private equity industry understands this better than most. The days of pilots and promises are over, and the demand for hard proof (a.k.a. ROI) has begun. Is your revenue accelerating? Can you drive efficiency and profitability at the same time? What does long-term growth look like? These are the questions sitting across the table at every board meeting and investment committee, and the pressure is only intensifying.
This pressure has forced major PE firms to move aggressively to formalize their AI strategies, including exploring joint ventures with leading LLM companies. They're making a calculated bet on AI as the most powerful value‑creation lever the industry has seen in its history, and they recognize that the window to move is now.
The logic is unmistakable. PE firms don't run single businesses, they run portfolios. Which means AI playbooks that work don't just transform one company; they compound across ten, twenty, fifty, hundreds. A workflow reinvented once becomes a repeatable asset. A governance framework built once becomes portfolio infrastructure. That multiplier effect is native to how PE creates value, and it's what makes the intersection of private equity and enterprise AI one of the most consequential arenas in business right now.
The bet is a no-brainer. Execution is where it gets hard.
Here's what we know to be true: competitive advantage won't come from betting on a single LLM. It will come from building AI tailored to your business, shifting to a hybrid strategy that combines custom models, foundation models, and smaller specialized models, all grounded in an architecture that connects your data, your workflows, and your intelligence. In private equity, where the same playbook has to work across an entire portfolio, that distinction isn't academic. It's the difference between value that compounds and value that stalls.
We know this because we lived it. We turned our own operations into the proving ground, analyzing nearly 400 operational workflows and deploying AI solutions across more than 100 so far, coupled with AI governance and enablement.
The result was $4.5B in productivity gains from AI, hybrid cloud, automation and consulting expertise, and proof of what works.
We then took that proof and productized those validated workflows into IBM Enterprise Advantage, a first-of-its-kind asset-based consulting service that enables clients to build and operate their own tailored internal AI platform at scale.
With digital workers, prebuilt tools, and native governance, clients have a headstart rather than a blank slate. And because it's multi-model, they retain the freedom to shift as technology evolves. For private equity, that flexibility determines whether a company is an asset or a liability at exit.
We're bringing this same approach to private equity-backed companies, where the defining question is what changed and can you prove it.
- A major U.S. telecommunications provider is deploying digital workers and prebuilt AI tools from Enterprise Advantage to accelerate the migration of more than 150 critical applications, delivering measurable savings within two quarters.
- Working with a leading insurance administrator, IBM is using agentic AI to overhaul end-to-end claims processing, a function where a single claim can involve dozens of tightly regulated steps across multiple systems. AI agents now read and structure claim documents, perform compliance checks, assess eligibility, and route cases automatically, resulting in faster cycle times, fewer bottlenecks, and an operating model built to scale.
What private equity does here will ripple far beyond its own portfolios. When PE-backed companies deploy production-ready AI across the business, they reset competitive expectations for entire industries, forcing every competitor to respond. That is the Enterprise AI Race playing out in real time.
The choices made today will define portfolio performance for the next decade. Move too slowly and you're handing the advantage to every competitor who didn't. Move without discipline and you're betting the portfolio on a foundation that hasn't been proven. The firms that win will be the ones who understood that distinction early enough to do something about it.
About IBM
IBM is a leading provider of global hybrid cloud and AI, and consulting expertise. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Thousands of governments and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM's hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM's breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and consulting deliver open and flexible options to our clients. All of this is backed by IBM's long-standing commitment to trust, transparency, responsibility, inclusivity and service. Visit www.ibm.com for more information.
Media contact:
IBM
Lily O'Brien
lilyobrien@ibm.com
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