Good morning, {{first_name}}! This week we're covering where the AI moat may ultimately live, private equity’s narrowing long-term performance gap with public markets, pricing power as a core underwriting question, and how cheap AI could create a new form of economic dependence for emerging economies.

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MONTHLY DATA DIVE PRESENTED BY DATASITE

The cost of reaching a given level of AI capability is falling by roughly 10x per year, while most enterprise AI pilots still fail to generate measurable P&L impact.

That gap is where the opportunity sits.

Foundation models remain enormously capital intensive, but technical advantages are being copied faster and open models are closing the performance gap. Applications face a similar problem. If the product is little more than a model wrapped in a user interface, competitors can replicate it quickly.

The more durable advantage sits deeper inside the enterprise. Proprietary operational data, embedded workflows, customer trust, and switching costs are much harder to reproduce. When AI is layered into those assets, it can improve margins while simultaneously making the underlying business more defensible.

Why it matters: For private equity, the best AI investments may not be AI companies at all. Established middle market businesses already own the data, workflows, and customer relationships that models need. The opportunity is to use cheaper AI to strengthen assets PE already understands and owns. (Read Full Report)

TREND TO WATCH

Private equity is still losing the short race, but the gap narrows sharply with time.

At the 1 year mark, Buyout returns sit near 8%, versus roughly 18% for the S&P 500. Over 3 years, the story barely improves, with Buyout around 8% and public equities above 18%.

Stretch the horizon, though, and the picture changes. At 5 years, Buyout returns rise above 10%, while the S&P 500 falls to roughly 12%. By 10 years, the spread is almost gone, with Buyout, All PE, and the S&P 500 clustered around 13% to 14%.

For PE investors, the message is less about outright outperformance and more about horizon discipline. Recent public market strength makes private equity look expensive in the rearview mirror. Over longer periods, that advantage compresses significantly.

The real underwriting question is no longer whether PE beats public markets immediately. It is whether the illiquidity, control, and operational upside justify waiting for the gap to close. (More)

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Learn more.

DILIGENCE CORNER BY 150 DILIGENCE

Pricing can be one of the fastest routes to EBITDA growth, but only if customers stay put.

The chart makes the diligence issue clear. 47% of respondents would not buy the product at all, while the acceptable price range runs from $5.17 to $10.00. That is a wide pricing corridor, but it also masks meaningful sensitivity across customers.

For investors, the question is not whether management can raise prices. It is how much price can move before volume, retention, or customer mix begins to deteriorate.

That means testing willingness to pay and elasticity by segment, not relying on historical increases alone. A brand with low elasticity may have immediate margin headroom. A highly sensitive customer base may turn the same pricing plan into a revenue problem.

The diligence edge is identifying which business you are buying before the value creation plan assumes otherwise. (More)

MACROVIEW

AI adoption is usually framed as a productivity story. But Eduardo Levy Yeyati’s new working paper, Burning the Bridge, argues that imported AI can also create a new form of external dependence.

The mechanism is twofold. First, as firms delegate tasks to foreign-provided agents, domestic capabilities, workers, training pipelines, routines, suppliers, can erode, weakening the ability to bring those tasks back in-house. That can improve the bargaining power of concentrated foreign providers.

Second, agentification can turn part of a domestic wage bill into a recurring foreign-currency payment. If those productivity gains do not generate enough exports or other tradable income, the economy can become more productive while its external constraint tightens.

Why it matters: AI may lower costs today while increasing long-term dependence on foreign providers, foreign infrastructure, and scarce external liquidity. (More)