Why private markets platforms must now scale with intent

Across private equity, private credit and real assets, managers are contending with rising scrutiny from Limited Partners (LPs) and regulators, sustained pressure on fees and an increasingly competitive war for talent. At the same time, expectations around data quality, transparency and speed of insight have shifted decisively. What was once “good enough” is no longer sufficient.

In this environment, investment management technology, data and operating model maturity are no longer back-office considerations. They have become strategic differentiators.

The forces reshaping private markets are well understood, but their combined impact is now unavoidable for managers operating at scale.

Firms are managing larger, more complex portfolios, often across multiple strategies and bespoke structures. LPs expect timely, tailored and auditable reporting, alongside deeper insight into portfolio performance, ESG metrics and risk exposure across increasingly complex portfolios. Regulators are demanding faster disclosures and greater transparency, particularly around governance, liquidity and valuation discipline. Internally, deal teams and operations functions are under strain, with legacy processes, spreadsheets and fragmented systems creating risk, rework and dependency on key individuals.

Margin pressure compounds these challenges. As fees compress, the ability to scale without linear growth in headcount becomes critical. Yet many managers remain constrained by operating models that rely heavily on manual intervention and informal controls.

The increasing prevalence of semi-liquid and evergreen structures, designed to broaden access to private markets and attract retail capital, adds a further layer of complexity. These vehicles introduce more frequent dealing cycles, requiring valuations to be performed at least monthly and, in some cases, daily Net Asset value (NAV) calculations.

This shift materially raises the bar for data accuracy, reconciliation and control. Managers must become comfortable standing behind higher frequency NAV positions, which in turn demands tighter integration between internal portfolio systems, fund administrators and external data sources such as bank feeds and custody records.

What was once a quarterly, committee-led exercise is becoming a continuous operational capability – reinforcing the need for robust data foundations, automated workflows and clear governance.

As private markets platforms grow, operating models must evolve. Early-stage firms often succeed through agility and individual expertise, but this model does not scale indefinitely. More mature platforms professionalise core processes, supported by clear roles, consistent data models and embedded governance and controls.

This maturity journey is not about bureaucracy. It is about freeing high-value talent to focus on judgement and value creation, rather than data wrangling and process coordination. Firms that invest in operating model clarity are better placed to absorb growth, onboard new strategies and respond to external scrutiny without disruption.

PwC’s perspective is clear: Sustainable scale in private markets is enabled by the deliberate alignment of technology, data and operating model design.

Leading firms are moving away from monolithic systems and ad hoc solutions towards modular architectures that reflect the investment lifecycle end-to-end. Rather than forcing compromise through “one-size-fits-all” platforms, they are integrating best-of-breed tools across deal origination, portfolio monitoring, valuations, investor reporting and fund operations. A robust data platform sits at the centre, enabling consistency, governance and reuse of information across internal and external stakeholders.

Crucially, success is not defined by the sophistication of tools alone. Many firms have experimented with advanced technologies, including AI, yet struggled to translate pilots into measurable value. The differentiator is execution discipline: Clear ownership of data, well-defined workflows and change enablement that brings investment, finance and operations teams along the journey.

Workflow enablement is no longer a niche capability in private markets, but its adoption has been uneven. To date, meaningful investment has largely been led by the largest and most complex managers, where scale, regulatory exposure and cross-functional coordination demands have made manual processes unsustainable.

For many mid-sized firms, core activities such as deal close and reporting are still coordinated through email and spreadsheets. While workable at smaller scale, these approaches become fragile as complexity increases.

What is changing is the cost and accessibility of workflow technology. Low-code, cloud-based platforms are reducing implementation time and total cost of ownership, lowering barriers for a wider range of managers. As a result, workflow enablement is moving rapidly from a differentiator of large platforms to a practical, scalable control mechanism for firms seeking growth without linear cost increase.

Despite years of investment, data fragmentation remains one of the most persistent challenges across private markets. Asset-level information arrives in a wide range of unstructured formats, from spreadsheets and PDFs to bespoke presentations. The same data is often requested by multiple internal teams for different purposes, creating duplication and frustration for teams at portfolio companies.

Spreadsheet dependency is a symptom of this fragmentation. While flexible, spreadsheets introduce opacity, version control risk and key-person dependency. They also limit the ability to perform scenario analysis, cross-portfolio insights and timely reporting.

Firms that address data foundations head-on, through standardised data dictionaries, improved ingestion capabilities and centralised data platforms, unlock disproportionate benefits. Confidence in data quality becomes the enabler for automation, analytics and increasingly, artificial intelligence (AI).

AI has captured the attention of private markets leaders. Many firms are already deploying AI across the investment lifecycle, particularly in deal origination and due diligence. Yet only a minority have fully operationalised use cases with tangible, repeatable impact.

The lesson is clear: AI success depends less on model sophistication and more on data readiness, governance and workflow integration. Without trusted data and clearly defined processes, AI risks amplifying existing inefficiencies rather than resolving them.

A pragmatic approach is emerging. Leading firms “rent” AI tools to learn, “buy” proven solutions to scale and selectively “build” proprietary capabilities where differentiation matters. Over time, AI is expected to become table stakes in areas such as portfolio monitoring, valuations and investor reporting, but only for firms that have laid the right foundations.

Aligned with this perspective, PwC’s recent analysis on how private equity survives AI highlights that roughly half of firms now view generative and agentic AI as transformative to their operations over the next three years, underscoring that thoughtful technology adoption is central to competitive differentiation across the investment lifecycle.

Portfolio monitoring is undergoing a quiet but increasingly profound evolution. Historically focused on periodic financial reporting, it is now expected to support proactive investment oversight, risk identification and value creation.

More advanced platforms combine financial, operational and sustainability data, enabling automated anomaly detection, forward-looking analysis and scenario modelling. Integration with portfolio company systems is beginning to provide near-real-time visibility, reducing reporting lag and enabling earlier intervention.

Importantly, portfolio monitoring is no longer a concern solely for General Partners (GPs). LPs are increasingly seeking deeper, more consistent insight into underlying exposures, driving demand for better data ingestion, structuring and transparency at fund and portfolio level.

PwC’s “Private Equity Digital Transformation” research, first published in 2024, highlights that inconsistent portfolio monitoring and continued reliance on spreadsheets remain material constraints on value creation. These fundamentals continue to hold true today, reinforcing a long-standing PwC perspective that purposeful investment in data platforms and analytics is essential to accelerate decision-making and unlock competitive advantage.

These operational and technological imperatives are echoed in PwC’s 2025 Global Asset & Wealth Management Report, which projects that private markets will drive more than half of global asset management revenues by 2030 and underscores how technology and digital ecosystems are central to future competitive advantage.

For COOs, CTOs, CFOs and Managing Partners, several implications stand out:

• Treat technology and data as strategic assets, not support functions.
• Invest in foundations first: Data quality, governance and workflow clarity.
• Adopt modular architectures that evolve with the business.
• Be pragmatic with AI, focusing on value, not novelty.
• View transformation as a journey, not a one-off programme.

We work alongside private markets clients at each stage of this journey, from assessing current-state maturity and defining target operating models, through technology selection, workflow enablement and implementation. Our specialist teams combine deep knowledge of private markets with technology expertise, supporting clients to scale with confidence and intent.

The opportunity is clear. With the right foundations, private markets platforms can meet rising expectations, unlock insight and continue to grow without losing the entrepreneurial edge that defines the sector.