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Business·P Space·Evidence-backed problem·Published 2026-07-13

Governing Enterprise AI Investments: A Decision-Centric Portfolio Framework

Despite enterprises continuing to invest heavily in AI, many initiatives fail to scale or generate sustained business value. Terming this the AI-investment paradox, we argue that it persists because firms govern AI as a broad technology program rather than as a set of discrete, investable decision opportunities embedded within workflows. We address this issue by developing a decision-centric portfolio framework for governing enterprise AI investments. Our framework introduces AI-Investable Process Nodes (AIPNs)…

TRV-2026-0111Peer-reviewedPermanent record — cite & verify
Governing Enterprise AI Investments: A Decision-Centric Portfolio Framework

"Brainstorming" by kevin dooley, CC BY 2.0.

The quick read

By July 2026, the authors described an AI-investment paradox in enterprises: continued heavy investment alongside initiatives that fail to scale. They proposed a decision-centric portfolio framework that reframes governance around discrete investable decision opportunities within workflows, introducing AI-Investable Process Nodes as bounded points where benefits, risks and costs can be assessed ex ante.

Linking investments to identifiable and governable decision nodes matters because it shifts evaluation from broad technology programs to specific workflow outcomes. What remains uncertain from the text is whether the Expected Net Benefit formalization and real options staging actually resolves the paradox in practice, as no empirical implementation or measured business value outcome is reported.

Main points
  • Authors term the pattern the AI-investment paradox where heavy investment does not lead to scaled value
  • Framework introduces AI-Investable Process Nodes (AIPNs) as bounded decision points where AI can alter expected outcomes
  • Node-level value is formalized through Expected Net Benefit and staged using real options logic
  • AIPNs are assembled into a broader portfolio through risk-return principles
Problem

Enterprises governing AI as a broad technology program see many initiatives fail to scale or generate sustained business value

Sources

The debate