1. Put AI into the investment thesis — on both sides of the ledger
Private-capital diligence is moving beyond asking whether a target 'uses AI'. Alvarez & Marsal's 2026 European diligence research reports that 80% of surveyed sponsors were incorporating AI into the investment thesis, while AI disruption also sits among the material risks investors are examining before close.
For an investment committee, the useful question is therefore two-sided: where can AI create credible operating or commercial value, and where could it weaken product differentiation, cost assumptions, customer behavior or the target's existing roadmap?
- Which revenue or margin assumptions explicitly depend on AI?
- Is the company building differentiated capability or mostly consuming third-party models and tools?
- Does the data, architecture and team support the roadmap being underwritten?
- What changes if model capability, pricing or competitive access shifts materially?
2. Treat AI governance as a portfolio operating issue
Saudi governance is becoming more structured. SDAIA's 2026 publications include a National AI Risk Management Framework covering risk identification, assessment, treatment and monitoring. SDAIA also continues to position AI ethics, responsible use, privacy and accountability as practical governance requirements rather than abstract principles.
The portfolio implication is simple: boards and investors need a repeatable way to know which AI systems matter, who owns them, what data they use, which third parties they depend on and what controls apply.
3. Make cyber risk comparable across the portfolio
In July 2026, Saudi Arabia's National Cybersecurity Authority published the National Framework for Cybersecurity Risk Management and had recently consulted on dedicated AI Cybersecurity Guidelines covering governance, defense, resilience and third-party cybersecurity.
For private capital, cyber oversight should move beyond annual questionnaires. A useful portfolio view distinguishes material business services, identity and privileged access, resilience, critical vendors, incident readiness and the technology initiatives most likely to change exposure.
4. Connect data governance to value creation and AI readiness
Saudi PDPL guidance emphasizes data minimization, clear processing purposes, privacy notices, processing records and controls around personal-data handling. For investors, these are not only compliance topics: weak ownership and unclear data flows can slow analytics, AI adoption, integration and exit diligence.
A portfolio company that cannot explain what data it holds, why it is processed, where it moves and who owns it is likely to struggle with both responsible AI adoption and buyer scrutiny.
5. Close the diligence-to-execution gap
A&M's 2026 value-creation research emphasizes earlier, more operational engagement and a continuing gap between diligence assumptions and execution. The technology implication is that material findings need owners, funding, milestones and board visibility after close.
The family office should be able to answer: which portfolio companies carry the highest technology risk, which technology initiatives are most important to value creation, which red flags are actually closing, and which issues need escalation before they become exit problems.