How can private markets firms communicate real technological edge?

Everyone in private markets is talking about AI, but very few are communicating it credibly. AI is dominating conversations ahead of SuperReturn International – from value creation and portfolio management to hiring, governance and the blurring of lines between asset classes.

But as adoption accelerates, so does scepticism. Investors are beginning to distinguish between firms embedding AI meaningfully into their operations and those simply layering new tools onto existing processes. That distinction matters. Across private markets, many firms are still struggling to operationalise AI at scale. Deployment may have surged over the past year, but fragmented systems, unclear accountability and uncertain return on investment remain real roadblocks. Access to AI is no longer the differentiator. Making it work consistently – and explaining how it creates value – is becoming the real test.

Here are six ways private markets firms can communicate genuine technological edge more effectively:

1. Move the conversation from AI adoption to AI implementation

Simply saying a firm is using AI no longer carries much weight. LPs want to understand how AI is being embedded into investment processes in thoughtful, practical ways. That means communicating where AI is actually influencing outcomes in:

• Sourcing and pipeline generation
• Due diligence processes
• Portfolio management and monitoring
• Operational efficiency
• Data analysis and reporting

The firms gaining credibility are those moving beyond experimentation and pilot projects toward tangible results. Investors want evidence that AI is improving speed, insight and decision-making.

2. Position AI as a value creation lever

One of the most notable shifts across the market is the growing emphasis on AI as a value creation tool, a lever for building stronger portfolio companies, improving productivity, and driving operational performance. In a recent BCG survey[1], 57% of PE investors said digital levers were core to value creation planning. What’s more, PE-backed companies that integrate AI capabilities across functions can achieve almost twice the return on invested capital as their peers.

The examples of AI-driven value creation are abundant and ever-growing. Examples include automating manual workflows, boosting operational efficiencies, and expanding margins through AI-enabled demand forecasting, pricing analytics and optimised supply chains.

3. Show solid governance

As AI adoption grows, governance concerns are rising alongside it. Questions are proliferating around oversight, cybersecurity, accountability and model reliability.

Firms should demonstrate not only innovation, but control. That means being prepared to explain:

• Governance frameworks and risk controls around AI deployment
• Approval and oversight structures
• Data management protocols
• Cybersecurity safeguards
• How outputs are validated and monitored

For LPs, governance is increasingly becoming part of the technology story itself.

4. Avoid accumulating “technology debt”

Private markets firms are not immune to a problem affecting many industries today: technology debt. Many are managing a patchwork of systems, tools and data sources, and are under pressure to simplify their tech stacks. In many cases, the issue is no longer access to technology, but whether firms have the infrastructure needed to make it usable at scale. According to SimCorp’s 2026 InvestOps Report[2], 58% of investment managers plan to consolidate technology vendors and platforms, while 54% are focused on modernising technology architecture and data infrastructure.

Sophisticated investors are becoming more aware of the distinction between operational complexity and operational advantage. They want to know whether firms are genuinely transforming how they operate or simply adding new layers onto outdated systems.

Firms that communicate integration clearly will have an edge. That includes demonstrating:

• How systems connect across teams
• How data flows through the organisation
• How insights are operationalised
• How technology investments align with broader strategy

Operational coherence will matter more than the number of AI tools deployed.

5. Treat AI strategy as a talent strategy

The BCG analysis[3] suggests many private equity investors are relying on specialist digital partners and AI consultancies to accelerate implementation, but only 45% of successful firms systematically ensure knowledge transfer to internal teams. External expertise alone is unlikely to create lasting advantage if knowledge remains siloed outside the organisation. Successful AI implementation depends on organisational readiness, upskilling and a clear commitment from leadership. Firms need investment professionals, operating partners and portfolio teams capable of integrating new tools into day-to-day decision-making.

That makes human capital an important part of the AI narrative. Firms will need to show how investment teams are adapting workflows, decision-making and skillsets to integrate AI effectively and for the long term.

6. Data as the real differentiator

As public and private markets converge, and the boundaries between asset classes continue to blur, data infrastructure is becoming increasingly strategic. The challenge is no longer simply collecting data, but integrating and interpreting it effectively.

The firms likely to gain advantage are those with stronger portfolio visibility, integrated reporting systems, faster decision-making capabilities and more connected investment intelligence across strategies. In that environment, data governance and transparency become part of the investment proposition itself.

In many ways, private markets are entering a new phase of AI adoption, one where credibility matters more than experimentation. The firms that stand out may not be those talking most loudly about AI, but those able to show how technology is embedded into their investment processes, portfolio operations, culture and long-term value creation in a robust and measurable way.

References:
[1] https://www.bcg.com/publications/2026/private-equitys-future-digital-first-and-ai-powered
[2] https://www.simcorp.com/resources/insights/white-papers-and-reports/2026/global-investops-report
[3] https://www.bcg.com/publications/2026/private-equitys-future-digital-first-and-ai-powered

This article is published in collaboration with Gregory.