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      Private equity is entering a new era of value creation. As traditional levers such as multiple expansion, financial engineering, and cost optimisation become increasingly constrained, leaders are looking beyond conventional approaches to drive differentiated returns. Operational alpha has emerged as a critical source of value creation, and Artificial Intelligence (AI) is rapidly becoming one of its most powerful enablers.

      AI is no longer viewed solely as a technology tool or productivity enhancer. Forward-looking private equity firms are embedding AI throughout the investment lifecycle to improve investment selection, strengthen transaction outcomes, accelerate value capture, and enhance exit readiness. At the same time, investors are increasingly assessing the AI maturity of target companies, including their data assets, governance frameworks, technology architecture, and ability to scale AI, as indicators of future competitiveness and long-term value creation.

      This evolution is creating a clear distinction between firms that use AI to improve processes and those that use it to fundamentally improve investment outcomes.

      Nilesh Patel

      Partner, Private Equity Value Creation – Technology

      KPMG in the UK

      Better investment decisions through AI-enabled diligence

      The quality of investment outcomes is often determined before a deal is signed. While traditional due diligence remains essential, it can struggle to keep pace with the volume, complexity, and diversity of information available in modern transactions. AI is transforming the diligence process by enabling investors to assess opportunities and risks with greater speed, depth, and precision.

      Key applications include:

      • Enhanced data analysis:

        AI can rapidly process vast volumes of structured and unstructured data, including financial records, operational metrics, commercial information, contracts, and customer data to identify patterns, trends, and anomalies that may otherwise remain hidden. This enables investors to develop a more comprehensive understanding of a target's performance, potential risks, and growth opportunities.

      • Comprehensive market assessment:

        By analysing competitive dynamics, customer sentiment, industry trends, and broader market signals, AI provides a more holistic view of a target's market position and growth potential. These insights help investors assess strategic fit, validate investment hypotheses, and identify areas for differentiation.

      • Assessing AI maturity and scalability:

        An increasingly important aspect of diligence is understanding the target's AI readiness. Investors are evaluating the quality and accessibility of data, existing AI use cases, governance structures, technology platforms, and the organisation’s ability to scale AI capabilities. Strong AI foundations can represent a significant source of future value creation and competitive advantage.

      • Streamlined diligence processes:

        AI-powered tools can automate the collection, classification, and review of diligence materials, improve accessibility, and reduce administrative burden. This allows deal teams to focus more time on strategic analysis and decision-making while accelerating transaction timelines.

      KPMG's AI-enabled due diligence methodology brings these capabilities together through specialised AI agents that scan virtual data rooms and financial datasets to instantly surface emerging trends, potential risks, and areas requiring deeper investigation. By identifying the most critical issues early, deal teams can focus their attention on the areas that matter most and drive informed decision-making.

      The approach is further enhanced through a secure chatbot capability that allows teams to process management reports, diligence packs, and supporting documentation using natural language queries. This enables rapid hypothesis testing, identification of evidence gaps, and traceability of conclusions back to underlying source materials. By rapidly separating critical insights from less relevant information, AI enables deal teams to refine information requests, accelerate analysis, and make better-informed decisions throughout the diligence process.

      The result is not simply faster diligence, but higher-quality investment decisions supported by deeper insights and stronger conviction.

      Identifying value creation opportunities during deal

      Private equity firms are increasingly using AI not only to evaluate assets but also to shape their value creation strategy before acquisition. By analysing a broader set of data sources and generating predictive insights, AI can help investors identify opportunities that extend beyond traditional diligence approaches.

      • Identifying value drivers:

        AI can uncover operational, commercial, and strategic drivers of value by analysing historical performance, industry benchmarks, employee sentiment, customer behaviour, supplier relationships, and other data sources. These insights can reveal opportunities for revenue growth, margin enhancement, operational efficiencies, and cost synergies that may not be evident through conventional analysis.

      • Workforce optimisation

        As AI agents and digital labour reshape operating models, KPMG Mystro™ helps investors and management teams identify where AI can augment the workforce, improve productivity, and create value by modelling future-state workforce structures and quantifying ROI opportunities. It also enables organisations to assess alternative operating models, reuse AI capabilities across functions, and prioritise transformation initiatives that deliver the greatest operational and financial returns.

      • Contract Analysis Tool

        AI can also help uncover risks and value creation opportunities hidden within large volumes of contractual documentation. A practical example of AI in action is KPMG's Contract Analysis Tool, which automates the extraction of key contractual data across high volumes of agreements, enabling deal teams to identify risks, uncover synergy opportunities, and develop more detailed integration or separation plans with focused SME oversight.

      • Strategic opportunity identification:

        AI can continuously analyse market developments, emerging technologies, and competitive movements to identify acquisition opportunities and value creation themes. This enables investors to position portfolio companies more effectively and capitalise on emerging trends.

      • Predictive scenario modelling:

        AI-enabled predictive analytics can evaluate multiple value creation scenarios and assess their outcomes. By modelling different strategic options, investors can better understand potential risks, allocate resources more effectively, and prioritise initiatives with the greatest potential impact on enterprise value. These capabilities can be applied across commercial, operational, technology, and workforce transformation initiatives, helping management teams make more informed investment and execution decisions.

      Realising AI value requires more than deploying new tools. KPMG helps investors assess AI readiness, data maturity, and technology foundations to identify high-impact opportunities, optimise AI investments, and accelerate the path from experimentation to measurable business value.

      These capabilities allow investors to develop a more informed and actionable value creation plan before Day One, helping accelerate execution and maximise return potential.

      Accelerating integration and value realisation

      The success of an investment is often determined by how quickly and effectively value creation initiatives are executed after closing. AI is becoming a critical component of post-deal integration, supporting the rapid realisation of synergies while reducing execution risk.

      To realise the full value of a transaction, organisations must address critical considerations such as data compatibility, system interoperability, technology architecture, and the alignment of AI capabilities with strategic objectives. When deployed effectively, AI can play a pivotal role in accelerating integration, reducing complexity, and supporting key value realisation activities.

      • Data discovery and harmonisation:

        AI can identify, classify, and consolidate data across organisations, helping create a unified view of critical business information. Enhanced visibility improves decision-making and lays the foundation for scalable operating models.

      • Risk identification and mitigation:

        AI can proactively identify integration risks, including data privacy concerns, regulatory compliance issues, cybersecurity vulnerabilities, and operational disruptions. Early detection enables organisations to address risks before they impact integration outcomes.

      • Process automation:

        AI-powered solutions can automate repetitive and resource-intensive activities such as data migration, reconciliation, system configuration, reporting, and workflow management. This can significantly reduce manual effort, improve consistency, and accelerate integration timelines.

      • Continuous monitoring and optimisation:

        Following integration, AI can provide real-time visibility into operational performance, constructive collaboration delivery, and value creation initiatives. Advanced analytics can identify bottlenecks, emerging risks, and opportunities for improvement, helping management teams maintain momentum and maximise value realisation.

      By accelerating constructive collaboration realisation, enhancing decision-making, and mitigating integration risks, AI can help organisations achieve deal objectives faster and maximise value creation outcomes.

      AI as a driver of exit value

      As adoption of AI accelerates, buyers are increasingly evaluating AI capabilities as part of their assessment of enterprise value. AI is no longer solely an operational enabler; it is becoming a vital component of the equity story.

      Organisations that demonstrate mature AI capabilities can benefit from:

      • Scalable, data-driven operating models
      • Improved productivity and operational efficiency
      • Enhanced customer experience and revenue growth
      • Stronger governance and risk management frameworks
      • Sustainable competitive advantages through proprietary data and AI-enabled capabilities

      To help buyers evaluate these capabilities, KPMG's AI Due Diligence and IT Assessment frameworks provide a structured view of a company's technology architecture, data assets, AI maturity, governance practices, and infrastructure readiness. This enables investors to distinguish genuinely embedded AI capabilities from superficial "AI washing" and better assess whether AI can act as a meaningful driver of future value creation.

      The assessment extends beyond technology into core business functions. KPMG's AI-enabled Finance Maturity Assessment examines the extent to which finance organisations have adopted automation, advanced analytics, and AI-driven decision-making. By evaluating the maturity, scalability, and resilience of finance operations, buyers gain deeper insights into the strength of the underlying operating model and its ability to support future growth.

      Increasingly, buyers are also assessing whether AI capabilities can scale sustainably. This includes evaluating the strength of underlying data foundations, governance frameworks, technology infrastructure, and the organisation's ability to manage AI operating costs effectively. Companies that demonstrate disciplined AI cost management, high-quality data ecosystems, and clear pathways to realising value from AI are often better positioned to support valuation premiums and differentiate themselves during exit processes.

      For portfolio companies, demonstrating measurable AI-enabled value creation is no longer simply a transformation success story. It is increasingly a source of competitive and valuation advantage. Companies that can clearly evidence mature AI capabilities, strong governance frameworks, scalable technology foundations, and AI-enabled financial and operational performance are often better positioned to attract investor interest, expand the pool of potential buyers, and strengthen valuation outcomes at exit.

      What does this mean for private equity leaders?

      AI is rapidly becoming a defining factor in how private equity firms’ source, evaluate, transform, and exit investments. While traditional value creation levers remain important, AI offers a new and increasingly powerful avenue for generating operational alpha across the investment lifecycle.

      For private equity leaders, three questions are becoming increasingly important:

      • Are we leveraging AI to improve investment decisions and diligence outcomes?
      • Are we evaluating AI maturity and scalability as part of our investment thesis?
      • Are we embedding AI into our portfolio value creation and integration strategies?

      The firms that can answer "yes" to all three will be best positioned to create differentiated returns in an increasingly competitive market.

      How KPMG can help

      At KPMG, we help private equity firms unlock AI-driven value across the investment lifecycle. Combining deep deal expertise, AI-enabled diligence methodologies, and value creation capabilities, we help investors identify genuine opportunities for value creation while distinguishing sustainable AI advantages from "AI washing."

      From AI-powered diligence and investment thesis development to post-deal integration, value realisation, and exit readiness, KPMG helps clients harness AI to accelerate outcomes, reduce execution risk, and create sustainable operational alpha.

      Our value creation insights

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