Tech Explained: How a value-led approach turns your AI playbook into a repeatable advantage | EY in Simple Terms

Artificial intelligence (AI) is reshaping industries, and private equity (PE) is no exception. The same forces driving disruption in portfolio companies are now transforming investment firms themselves. For PE leaders, AI is both a potential threat and a powerful enabler, amplifying human insight, accelerating execution and redefining operational excellence.

The implications of AI span every dimension of a PE firm’s mandate:

• Work smarter and faster: Reimagine how investment teams source deals, make decisions and create value. Find opportunities in leveraging proprietary, non-public data to bring sharper insights and challenge AI-generated, widely accessible outputs
• Manage disruption risk: Understand which business models remain defensible in an AI-enabled economy, which opportunities to pursue and how to mitigate risks.
• Accelerate value creation: Deploy AI at scale across portfolio companies for growth and productivity.

AI is not meant to replace investment professionals. Instead, it can automate and augment routine tasks, giving professionals more time to focus on strategic questions.

Applying AI across the investment cycle

While enthusiasm for AI often centers on portfolio companies, forward-thinking PE firms should consider turning the lens inward, with AI proving to be a force multiplier for speed, precision and insight across the investment lifecycle.

1. Deal origination: faster and smarter target identification

Traditionally, origination has relied on networks, intuition and excel-based screening. Today, the competitive edge belongs to firms that can analyze vast volumes of structured and unstructured data, including market reports, company filings, patents, news and job postings, to uncover emerging investment themes before others.

How AI supports deal origination:

• Continuous sector and long-list mapping: Leverage natural language queries and comprehensive datasets, including financial statements, market analyses, news, public records and digital indicators, to systematically develop and maintain long-lists of potential targets.
• Target lists enhancement: Automatically evaluate and supplement company profiles with relevant information such as ownership structure, competitive insights, social media sentiment, sustainability metrics or intent indicators.
• Event monitoring: Continuously observe developments including funding activities, executive transitions and mergers and acquisitions to identify emerging opportunities and targets aligned with your investment strategy in real time.

The impact: Continuous and proactive AI-enabled target scanning with investment professionals focusing on the strategic curation and review of the most promising opportunities, enhancing both quality of the review but also number of targets assessed.

Driving client success with AI-powered insights

EY supports clients and professionals leveraging Competitive Edge, a proprietary AI-enabled platform that combines data on 31 million companies and 2.6 million transactions with web data and EY knowledge base in one place for accelerated insights.

2. Due diligence: from information overload to insight acceleration

Due diligence is a vital step in the investment process, often requiring significant time and resources. As the volume and complexity of data continue to grow, AI helps investment professionals efficiently analyze large datasets, quickly surface preliminary insights and flag potential concerns. By streamlining data review, AI enables teams to double-down on the deal aspects that matter most.

How AI supports due diligence:

• Drafting diligence scopes: AI can automatically create preliminary scopes and agendas using past cases, market information and research and relevant documentation.
• Extracting insights: AI reviews hundreds of documents or interview transcripts simultaneously, summarizing key takeaways, identifying issues early and flagging discrepancies
• Preparing investment committee materials: AI can help summarize notes and reports into clear, actionable memos to support decision-making.

The impact: Hypothesis-led diligence that validates (or challenges) the thesis faster with higher confidence in conclusions and recommendations

Driving client success with AI-powered insights EY Diligence Edge is an integrated suite of proprietary and third-party tools used during diligence phase, leveraging automation and AI to accelerate data review and analysis, highlight key risks, flag critical issues and deliver tailored deal insights. 3. Value creation: accelerating impact at scale Origination and diligence help identify promising investments, but value creation is what creates future winners. AI is now an important lever for achieving double-digit improvements in both revenue and profitability. Agentic AI takes this further by enabling organizations to reimagine entire workflows and ways of working.

How AI can accelerate and generate repeatable value:

• Create and validate hypotheses already in due diligence: Assess disruption risk and organizational maturity to accelerate target setting and execution post-acquisition.
• Integrate AI into full potential plans: Make AI a standard lever for value creation, focusing on both augmentation and reimagination. This requires availability of capabilities and experiences to identify full range of what is possible. · Curate preferred AI vendors lists: Understand which providers offer differentiated functionality and negotiate pricing for portfolio-wide adoption. · Build and share reusable assets: Develop leading practices, high-impact use cases by function, solution blueprints and change management playbooks for portfolio companies to re-use.
• Automate reporting and performance monitoring: Aggregate data from portfolio companies automatically, flagging anomalies and early signs of operational or financial deterioration.

The impact: Private equity leaders can shift time from manual reporting and analysis to strategic coaching and operational steering, using reusable blueprints for value acceleration and creating a repeatable advantage.

Driving client success with AI-powered insights

EY.ai Value Accelerator quantifies EBITDA impact potential across 17 sectors and multiple functions, enabling rapid prioritization of high-value AI opportunities proven across client projects and for the EY organization as client zero.

Checklist for private equity leaders

Before investing in target markets or while working with portfolio companies, make sure you understand opportunities and risks related to AI:

• Does the company understand both the risks and opportunities of AI for their business and own ability to win in the AI-enabled market? Assess whether the organization recognizes AI’s potential for disruption and has evaluated competitive moves and its own readiness.
• Is there a clear AI strategy with leadership support and talent alignment? Look for a defined ambition that supports strategic goals, clear ownership, a talent agenda and active leadership engagement.
• Are priorities balanced between efficiency and revenue growth? AI has proven to be a strong enabler of both top line and bottom line – key that companies understand both commercial model and operational opportunities for well-rounded approach.
• Does AI support business outcomes and is the impact measured? Experimentation needs to be balanced with scaling into production and real business impact where funding gets allocated based on potential to deliver value and feasibility, and outcomes get monitored with proactive change management.
• Is AI integrated into ongoing change programs, such as digital transformation or cost optimization? AI should be viewed as part of the value creation toolkit, not as a separate initiative and can allow for faster and cheaper change realization.

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Bridging the AI gap: what it takes to win Winning with AI in private equity requires more than ambition as it demands disciplined execution.

Key actions for private equity leaders:

• Define ambition and ownership: Set a clear vision and accountability to guide investment, effort and buy vs. build decisions.
• Reimagine workflows and think beyond solutions: Move beyond incremental improvements to fundamentally redesign how processes are performed, by whole teams and not only selected individuals.
• Invest in broader capabilities including talent, change and governance: Make sure that investments go beyond pure technical capabilities to drive sustained impact.
• · Prioritize high-impact areas and measure results: Focus on initiatives that shift deal economics and create differentiation. Avoid scattered pilots by selecting a few areas to master and iterating for optimal adoption.
• Balance experimentation with scaling: Encourage testing and learning but commit resources to scaling successful solutions and managing change for lasting impact. AI isn’t just a technology; it is a mindset shift for private equity and continuous learning journey ahead. The firms that dare to reimagine workflows and embrace new opportunities in a thoughtful way, through close monitoring of technological advances, will set the pace for the next decade. The future of value creation belongs to those who combine bold vision with disciplined execution. Will your firm lead or follow?

Shaping the future of private equity with confidence

EY professionals support AI-driven transformation in private equity, combining sector expertise with a proven track record of innovation and responsible implementation. For investment firms seeking to move from experimentation to enterprise-wide value, EY teams offer not just technology, but a holistic approach that turns ambition into measurable outcomes.

EY organization’s AI capability is demonstrated by:

• $1 billion invested annually in bespoke software and technology platforms, fueling continuous advancement.
• 30% growth in AI-related revenue in FY25, with over 15,000 professionals delivering AI-led projects for clients.
• 100,000+ technologists and over 1,000 AI agents in development or production.
• 90% of EY professionals have completed foundational AI training, and 161,000 AI badges have been awarded or initiated to date.
• 118 ecosystem alliances and relationships, supporting 55% of overall revenue growth in FY25.
• Industry recognition, including “Generative AI Solution of the Year” for EY.ai EYQ and IDC Leader 2025 for AI Services.

EY organization’s proprietary EY.ai platform unifies sector experience, data and transformation capabilities, enabling clients to build future-proof data foundations and realize value from AI responsibly and at scale.