Ten Ways in Which Data & AI Can Help Private Equity Accelerate Value Creation

In a time when many organisations are scaling back or rationalising their data capabilities, private equity (PE) as a sector is moving in the opposite direction. Increasingly, value creation discussions in PE involve data, analytics, and AI. As the market rebounds after two turbulent years, this trend is expected to gain momentum. Many firms are not yet data-mature, grappling to identify how and where these tools can drive the greatest impact.

"Often these AI investments feel like lottery tickets; no one seems to know which ones will pay off." – Mid Cap PE Investor

Yet, there are proven benefits to be unlocked through data and AI capabilities. Not every investment needs to be a guessing game. Today, we explore why these matter and pinpoint the areas where data and AI can be most effective.

Pre-Deal: Enhancing the Front Line

Streamlining Origination

Origination remains a labour-intensive process, but data-driven automation and AI are reshaping the landscape. By leveraging machine learning models, PE firms can identify high-potential investment targets faster and with greater precision, automating lead generation and screening. This can give smaller specialist firms a decisive edge in competitive deal sourcing.

"As a firm that invests in technology businesses, it makes sense we should leverage the latest technology in our own business." – Small Cap PE Investor

De-risking Due Diligence

Data has always been foundational to due diligence, yet its limitations in quality, format, or analysis often result in blind spots. Enhanced data capabilities enable firms to rapidly cleanse, integrate, and analyse diverse data sets, providing a more comprehensive picture of potential acquisitions. For instance, anomaly detection models can uncover risks hidden in operational data, while sentiment analysis tools mine customer reviews for insights into brand health. At the same time, generative AI is simplifying the consumption and summarisation of heterogeneous data.

Value Creation: Performance with Precision

The Prioritisation Imperative

Effective value creation plans hinge on prioritisation—understanding which initiatives offer the best return on effort. Analytics can provide scorecards and dashboards that map organisational status quo against impact/effort frameworks, enabling leadership to allocate resources with confidence.

"We are increasingly seeing PE firms use roaming Chief Data Officers (CDOs) to help oversee data strategies across their portfolios. Forty percent of PE firms now utilise a Data Operating Partner model, a significant rise from just twenty percent in 2020. This reflects the growing recognition that data management and analytics capabilities are as critical to portfolio performance as traditional financial and technical expertise." – Jack Denison, Co-founder, Denison Nunn

Accelerating Initiatives

Real-time data fuels faster iteration. Consider pricing strategies: a data-savvy firm might test multiple pricing models within a week, leveraging live customer feedback, while competitors tied to monthly reporting cycles are left behind. This speed compounds value creation, as initiatives can be executed in less time.

Increasing Revenue: Insights into Action

Optimising Sales Efficiency

Few sales teams operate at peak efficiency, and data can change that. Lead scoring powered by AI ensures effort focuses on the most promising opportunities, while propensity models identify when and where customer engagement is most likely to convert. In customer acquisition, segmentation can improve allocation and targeting of media budgets.

Critically, best practices from mature organisations can be applied to portcos to help them avoid expensive mistakes, particularly during phases of rapid growth and investment. Obviously, given the different horizons for listed businesses, one needs to be discerning in identifying the right metrics. The benefits of doing so can have a significant impact on enterprise value.

"For sustained value creation, customer acquisition, conversion, and revenue retention need to operate in a joined up way. At its worst, misaligned KPIs result in value destruction. Take for example the simple KPI of cost to acquire: data and tech can reduce this, however you can often end up with high registrations but no transactions being completed. Joined up metrics such as cost to acquire completed basket ensures the full value map is developed and the full potential can be realised." – Sanjeevan Bala, Group Chief Data & AI Officer, ITV

Mastering Cross-Sell and Upsell

Understanding the what, when, and who of cross-selling is crucial. Advanced analytics highlight opportunities by matching customer profiles to complementary products or services, while AI-driven recommendations improve timing and offer structuring.

Cost Out: Smarter Scaling

Automating Internal Processes

From document processing to coding, automation drives cost reductions across back-office functions. AI-powered tools can streamline workflows, reduce errors, and free up human capital for higher-value tasks. At a portfolio level, playbooks and toolkits allow these optimisation use cases to be scaled efficiently.

"Automation is proving crucial in PE, where tight timelines demand rapid efficiency gains to drive value creation and maximise exit potential—far more critical than listed businesses with longer-term horizons." – Liam Grier, Founder, Inicio Talent

Transforming Customer Care

While chatbot performance divides opinions, augmenting customer service with AI assistants can significantly improve outcomes. AI systems that surface relevant resources or recommend solutions in real-time enable agents to resolve issues faster and more accurately, improving customer satisfaction without compromising personalisation.

Mergers & Acquisitions: Synergies

Elevating Enterprise Value

High-quality data assets are critical differentiators in AI model success. Firms that can demonstrate robust, well-curated datasets not only improve operational performance but also boost valuation during exits, as these assets enhance the potential for AI-driven innovation.

"The appetite for external datasets has grown rapidly over the last few years. [..] External data users now include asset managers, private equity, venture capital, corporates, consultants, central banks, and government entities. The opportunity to monetise portfolio company data by selling to third parties is growing at a rapid pace." – Data-driven value creation in portfolio companies report, PWC

Seamless Integration

Modular systems and strong data governance simplify the complexities of merging disparate entities. Standardised data models and well-documented APIs facilitate smooth integrations, supporting both cost reduction and faster realisation of synergies.

For private equity, the case for investing in data, analytics, and AI is clear. These tools unlock efficiency, enhance decision-making, and enable firms to outperform competitors. As the market heats up, those who act decisively to build these capabilities will be the ones who capture the greatest value.

— Ryan

Cover image by DALL·E