{"id":65640,"date":"2026-06-11T07:24:42","date_gmt":"2026-06-11T07:24:42","guid":{"rendered":"https:\/\/www.elixirr.com\/en-gb\/?p=65640"},"modified":"2026-06-11T08:02:29","modified_gmt":"2026-06-11T08:02:29","slug":"operational-alpha-is-back-in-pe-and-most-value-creation-plans-are-already-out-of-date","status":"publish","type":"post","link":"https:\/\/www.elixirr.com\/en-gb\/operational-alpha-is-back-in-pe-and-most-value-creation-plans-are-already-out-of-date\/","title":{"rendered":"Operational alpha is back in\u00a0PE, and most value creation plans are already out of date"},"content":{"rendered":"\n
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Every serious voice in private equity is converging on the same diagnosis.<\/span>\u00a0<\/span><\/p>\n

Apollo<\/span><\/a>, in January, argued the asset class needs to return to its roots: buy well, improve operations, exit with discipline, because cheap debt and multiple expansion are gone. Bain’s 2026 Global PE Report goes harder, with the line that has been quoted everywhere since February:\u00a0\u2018<\/span>12 is the new 5<\/span><\/a>.\u2019\u00a0The deals that used to clear their return hurdle on\u00a0roughly 5%\u00a0annual EBITDA growth now need 10 to 12. Bain’s advice to GPs is blunt: build durable operating capability rather than marketing it, invest in talent and AI, and move from diagnosing an asset’s full potential to executing from the first day of ownership. Blackstone’s leadership calls AI\u00a0\u2018<\/span>the megatrend of megatrends<\/span><\/a>\u2019\u00a0and has built a 300-strong analytics community across its portfolio.\u00a0<\/span>KKR<\/span><\/a>\u00a0has AI embedded across 225-plus portfolio companies through its Capstone team.<\/span>\u00a0<\/span><\/p>\n

The diagnosis is unanimous. Financial engineering is no longer enough. Operational value creation is back, and AI is meant to be in the plan.<\/span>\u00a0<\/span><\/p>\n

So why are most of the value creation plans still answering half the question?<\/span>\u00a0<\/span><\/p>\n

We\u2019ve\u00a0spent the last year in back-to-back conversations with PE firms and portfolio companies.\u00a0The same four questions keep appearing, with either a clear solution\u00a0emerging\u00a0or managers getting caught flat-footed. The four questions below reflect what\u00a0we’ve\u00a0learned from seeing\u00a0organisations\u00a0tackle these challenges effectively, and where others have struggled.<\/span>\u00a0<\/span><\/p>\n

The variable the industry keeps underpricing<\/h2>\n

Bain and\u00a0StepStone’s\u00a0GP Outlook, published this February,\u00a0contains\u00a0one of the strangest data points of the year. GPs report their best returns from generative AI in deal sourcing and due diligence. Inside their own portfolios, the benefits skew to cost savings, and\u00a0<\/span>nearly 40% of GPs expect no material financial impact from AI in 2026.<\/span><\/a>.<\/span>\u00a0<\/span><\/p>\n

Read that twice. While Blackstone is putting data scientists inside its companies and KKR is doing the same at scale, four in ten GPs are treating AI in their existing book as a cost story or\u00a0a non-event.<\/span>\u00a0<\/span><\/p>\n

That is a mistake, and there is now a cautionary tale big enough that no GP should miss it.<\/span>\u00a0<\/span><\/p>\n

What Chegg should teach every GP<\/h2>\n

If you\u00a0haven’t\u00a0come across it, Chegg is a US-listed education technology company. Its core product was online homework help: students paid a monthly subscription for access to a huge library of textbook solutions and step-by-step answers to academic questions. It was exactly the kind of business private\u00a0equity\u00a0has spent two decades loving. A subscription model\u00a0with predictable revenue\u00a0and\u00a0a\u00a0ten-year content library that looked like a real moat. In\u00a02021\u00a0it was worth around $14.5bn.<\/span>\u00a0<\/span><\/p>\n

Then ChatGPT arrived and Google bolted AI\u00a0overviews onto search. The product became substitutable overnight, and the channel that delivered its customers went dark at the same time. By late 2025\u00a0<\/span>Chegg’s revenue<\/span><\/a>\u00a0had\u00a0roughly halved\u00a0year on year, it had cut close to 45% of its workforce, and a company once worth $14.5bn was worth nearer $100m. A ten-year moat, gone in barely two years.<\/span>\u00a0<\/span><\/p>\n

Here is the part to sit with. Chegg saw it coming and tried to respond. In 2023,\u00a0it launched an AI study tool built in partnership with OpenAI itself. It\u00a0failed to\u00a0hold subscribers, because students who could already use ChatGPT directly had no reason to pay for a wrapper around the same technology. Bolting a generic AI feature onto a business under threat did not save it. Remember that the next time someone walks into a board meeting and presents an\u00a0\u2018AI feature\u2019\u00a0as a moat.<\/span>\u00a0<\/span><\/p>\n

Chegg is extreme, but it is not exotic. The categories private equity has prized for their defensibility are now often the most exposed: vertical SaaS that codified a workflow, BPO and outsourced services, content and publishing, legal,\u00a0marketing\u00a0and customer-support operations. The sticky, recurring-revenue businesses LPs underwrote on.<\/span>\u00a0<\/span><\/p>\n

This is not just my\u00a0read. MIT’s\u00a0\u2018State of AI in Business 2025\u2019, the study behind the widely quoted finding that\u00a0<\/span>95% of corporate<\/span><\/a>\u00a0AI pilots produce no measurable P&L impact, also found that the use cases delivering the strongest returns were AI replacing business process outsourcing, cutting agency costs and automating back-office work. Put plainly: the clearest evidence we have of AI actually working in the enterprise is AI eating exactly the kind of\u00a0labour-heavy service businesses that sit in a lot of portfolios.<\/span>\u00a0<\/span><\/p>\n

If your value creation plan assumed a four-year window of operational improvement on a business AI compresses in eighteen months, you do not have a plan. You have a problem.<\/span>\u00a0<\/span><\/p>\n

So,\u00a0the new playbook has a second leg. Operational value creation in this cycle\u00a0has to\u00a0be AI-literate by default. The firms doing it well are not running a thematic AI bet on the side. They are treating AI as operational hygiene across every company they own.<\/span>\u00a0<\/span><\/p>\n

The four questions I keep being asked<\/h2>\n

These are the conversations\u00a0I’m\u00a0having every week. Operating partners, deal teams, portfolio company\u00a0CEOs\u00a0and the occasional fund principal who has done the\u00a0maths\u00a0and\u00a0realised\u00a0the plan on the shelf is not going to deliver.<\/span>\u00a0<\/span><\/p>\n

1. Which of our investments could AI take to zero?<\/h3>\n

Always the first question, and the one most\u00a0firms\u00a0answer too slowly. It is not a portfolio review. It is\u00a0triage. And triage means separating noise from terminal risk.\u00a0Almost every\u00a0company is under threat from AI in the loose sense that its competitors now have new tools. That is not the question worth board time. The real one is which of these businesses AI could take to zero, the way it\u00a0nearly did\u00a0to Chegg. You are looking for three things:<\/span>\u00a0<\/span><\/p>\n