The next test for private markets isn't growth

• Competitive advantage in private markets is shifting from data access and accumulation toward connected intelligence, analytics and decision-making at scale.
• Combining public and private market intelligence provides deeper context for valuation, risk assessment and investment decisions. 
• The most effective investment outcomes are enabled by the combination of trusted data, advanced analytics, AI capabilities and human judgement delivered within the workflow.

For much of the past decade, the private markets story has been defined by growth.

Assets under management have expanded, new pools of capital have entered the market and investors have increasingly looked beyond traditional asset classes in pursuit of diversification and long-term returns. As a result, private markets have become a more established component of institutional portfolios around the world. But growth alone is no longer the most interesting story.

As private markets mature, the source of competitive advantage is beginning to shift. For many years, success was often associated with access: access to capital, investment opportunities and information. Today, investors face a different challenge. The focus is increasingly on how organisations can transform fragmented information into intelligence that supports faster, more informed decision-making across the investment lifecycle. Importantly, private assets can no longer be assessed in isolation. The most informed investment decisions increasingly come from combining private-market intelligence with public market context, including comparables, financing conditions, sector performance, transaction activity and broader market signals.

The next competitive advantage will not come from accumulating more data. It will come from turning disconnected information into intelligence that creates clearer insight and stronger conviction. In my previous insight, Building the data foundations for private markets, I discussed the importance of establishing stronger foundations to support the continued evolution of the asset class. Today, attention is increasingly turning to what comes next: extracting greater value from those foundations by connecting information, applying analytics and generating intelligence that supports action.

The obstacles facing investors today are very different from those of a decade ago. Historically, much of the industry's focus was on gaining access to opportunities and building exposure to the asset class. Today, firms are evaluating a far broader universe of managers, funds, strategies and investments than ever before. At the same time, investment teams must navigate rising expectations around governance, transparency and performance while responding to changing market conditions with greater speed.

Investors now have access to expanding volumes of private company information, fund data, transaction activity, research and market intelligence, alongside public market data, financing trends, sector performance and economic indicators. The challenge is no longer information scarcity. The differentiator is the ability to identify the signals that matter and apply them consistently across investment decisions.

In other words, the progression is no longer simply about collecting information. It is about transforming data into analytics, and analytics into intelligence. The organisations best positioned for the future will be those that can operationalise that intelligence across their investment processes.

One of the most significant shifts underway is the growing convergence between public and private market analysis. Private market investors increasingly recognise that understanding an opportunity requires more than evaluating a single company, fund or asset. It requires understanding how that opportunity sits within the broader market environment.

Investors are increasingly looking to connect private company information with public comparables, financing conditions, sector performance, capital market activity, transaction trends and wider economic signals. Bringing these perspectives together creates a richer understanding of valuation, performance, risk and opportunity.

This broader context enables investment teams to benchmark more effectively, identify emerging trends earlier and assess investments with greater confidence. As public and private markets become more interconnected, the ability to unify these traditionally separate sources of insight is becoming an increasingly important source of differentiation.

Let’s consider the diligence process for a private company. Traditionally, an investor might analyse the company’s financials, management projections and transaction history. A more connected approach could place those fundamentals alongside public-company comparables, recent M&A valuations, private financing activity, credit conditions and sector trends.

The analysis can then go further. Changes in hiring, management, ownership, borrowing activity, news or other operating signals can provide additional context around the trajectory of the business. Relationships between the company, its sponsor, executives, lenders, advisers and comparable investments can reveal patterns that are difficult to see when each dataset is considered independently.

The objective is not simply to put more information in front of an investor. It is to connect those signals so they can answer more useful questions: Is the company outperforming relevant peers? Is financing becoming more expensive? Is leverage moving differently from the sector? How does its valuation compare with similar public and private transactions? Are there early indicators that its growth or risk profile is changing? 

That is the difference between having data and creating intelligence.

AI is accelerating this evolution.

Investment professionals are increasingly exploring how AI can help synthesise large volumes of data, uncover relationships across datasets and identify patterns that may otherwise remain hidden. This is particularly valuable as investors seek to evaluate opportunities across an expanding set of public and private market inputs.  Applied effectively, AI can enhance research, due diligence, portfolio monitoring and opportunity identification. However, AI is only as effective as the data that powers it. Trusted, structured and contextual information remains essential. Without strong foundations, organisations risk generating more noise rather than more meaningful outcomes. 

The greatest opportunity lies in combining high-quality data, advanced analytics, AI-enabled capabilities and human judgement. Technology can help investors process complexity at scale, but experience and context remain critical in determining how intelligence is applied. Importantly, this creates an opportunity to move beyond purely backward-looking analysis. Private markets have traditionally relied heavily on reported information, which by its nature describes what has already happened. As datasets become more connected and analytical capabilities improve, investors can begin identifying indicators of what may be changing. 

For a private company, that might mean combining financial performance with hiring momentum, financing activity, sector conditions, transaction data and other operating metrics to better understand its growth trajectory or financial health. At the fund and manager level, investors can examine performance persistence across vintages, deployment patterns, distributions, portfolio outcomes and fundraising activity to develop a more complete understanding of performance and risk. None of these indicators replaces fundamental analysis or investment judgement. Their value lies in helping investment professionals focus attention more effectively, ask better questions and recognise changes earlier. 

Equally important is where intelligence is delivered. The value of information is no longer determined solely by the quality of a dataset. Increasingly, value comes from delivering relevant intelligence within an investor's workflow and at the point of decision.

Whether evaluating a new opportunity, assessing portfolio exposure, monitoring market developments or preparing for an investment committee discussion, investment professionals need seamless access to connected intelligence that supports action. The most valuable insights are often those delivered in context, embedded within daily workflows and available precisely when decisions are being made.

As organisations seek to improve efficiency and consistency, integrating intelligence directly into investment workflows is becoming just as important as access to the underlying information itself. Benchmarking is another area where connected intelligence can change the investment process. As institutional portfolios increasingly combine public and private assets, investors need to understand performance and risk across the whole portfolio rather than within separate asset-class silos. A private equity investment, for example, can be assessed not only against other private funds or transactions, but also against relevant public-market exposures, sectors and factors.

Over time, this creates the potential for a more integrated approach to portfolio analysis — connecting public and private holdings to understand performance attribution, concentration, risk and liquidity through a common investment lens. For investment committees and portfolio managers, that broader context can provide a much clearer answer to a fundamental question: what is actually driving the performance and risk of the total portfolio?

One of the defining characteristics of today's private markets environment is scale. Investment strategies continue to diversify, portfolios continue to expand and organisations are managing increasingly sophisticated investment ecosystems.

This means scale can no longer be measured solely by assets under management. Increasingly, it reflects an organisation's ability to scale institutional intelligence and judgement across a growing number of opportunities, investment teams and portfolio companies. The challenge is enabling investment professionals to make high-quality decisions consistently without compromising governance, oversight or accountability.

Achieving that requires organisations to connect insights across teams, functions and asset classes so that knowledge can be applied consistently across the organisation. True scale is achieved when organisations can expand decision-making capacity while maintaining confidence in the quality and integrity of those decisions.

Looking ahead, it is possible to imagine AI-enabled workflows helping investors answer increasingly sophisticated questions. An investment professional might ask: Show me the private healthcare companies in my portfolio whose revenue growth is slowing, leverage is increasing relative to peers and financing costs have risen, and identify the market, company and management factors that may explain why. Answering a question of that nature requires far more than a language model. It depends on connected company, financial, ownership, transaction, credit, market and relationship data, all linked to the same entities and placed within the appropriate investment context.

This is where the next phase of innovation in private markets is likely to emerge. As investment environments become more sophisticated, investors will place greater emphasis on the operating models, information frameworks and decision-support capabilities that enable investment teams to make better-informed decisions with greater confidence and consistency. 

Private markets have already demonstrated their ability to attract capital, expand investment opportunities and become a core component of institutional portfolios. The next phase of the market's evolution will be defined by something different.

As private markets mature, competitive advantage is shifting from access and data accumulation toward connected intelligence, analytics and decision-making at scale. Success will increasingly depend on an organisation's ability to combine trusted data, public and private market context, advanced analytics, human judgement and workflow integration to support investment decisions throughout the lifecycle.

The next chapter of private markets will not be defined by who has the most data, but by who can connect it, contextualise it and turn it into intelligence that improves investment decisions.

Whether you're raising capital, sourcing deals, analysing fund performance, or staying ahead of market trends, LSEG delivers Private Markets data, news and insights you need to turn data into dealmaking. Identify, analyse and monitor global private markets with our comprehensive coverage, robust capabilities and granular, hard-to-find details delivered whenever, wherever and however you need.