Almost every Private Equity firm we have spoken to this year is running an AI pilot. Far fewer Private Markets firms have a plan for production.
At SuperReturn CFO/COO 2026, Harpreet Lakhan, Director, set out what the move takes.
Start with the use case
With AI use cases in every function, the first question is where to start. Our library of 70+ AI use cases maps them by complexity, value, and team. Technology-led programs often spend heavily with little to show for it.
Pilots prove what is possible
A general AI tool can turn a PDF and a spreadsheet into a convincing output in minutes. Our session example took five minutes in Claude. Pilots like this rely on shortcuts, manual workarounds, and data cleansed offline, so the result stays local to its builder. They still prove feasibility and help build sponsorship.
Production takes a different path
Reaching a pilot and reaching production are separate paths, with different effort, time, and investment. Production means AI output that the whole firm can trust. It rests on three foundations:
- Decide: agree on the strategy, target operating model, budget, and sponsorship.
- Build: add the integration, automation, orchestration, and controls that the pilot skipped.
- Sustain: rollout is only the start, so monitor for drift and update as workflows change.
Trusted AI runs on governed data
In our ATLAS demo, a portfolio company emails a new board pack and financials. The AI starts a workflow rather than publishing a report. It adds prior-period data and news research, then flags issues for the investment team. Each step relies on:
- One mastered record per portfolio company
- Provenance back to the source document
- A full audit trail with human review
The final output may look similar, but the governance behind it is very different.
ATLAS shortens the path to production
Designed for Private Capital, the ATLAS AI Accelerator gives your firm:
- Consolidated, AI-ready data, connected to all your systems and sources
- AI outputs that can be trusted at scale, with full audit history
- The data engine your AI team needs to scale every use case
To move your firm from AI pilots to enterprise, institutionalized AI production, contact us. We will show how ATLAS fits your AI environment.
AI advisory built for Private Capital
Our AI Advisory practice supports firms at four levels:
- Governance and operating model
- Enterprise AI rollout and training
- Forward-deployed AI engineering
- Scaled AI enablement with ATLAS
Our team has advised 200+ Private Capital managers across Private Equity, Private Credit, Real Estate, Infrastructure, and Secondaries.
Request a free 30-minute AI consultation, or contact info@hollandmountain.com.
