Inside Equity Firms' Portfolio AI-Driven Acquisition Strategy: Apollo's Portfolio Value Creation Model
- The article analyzes Apollo's strategy for its portfolio companies, indicating that Apollo’s AI strategies align with 2025 private equity trends, thereby enabling what they call value creation.
- According to industry case studies, AI serves as an enabler, likely improving portfolio performance.
- The evidence suggests that structured AI approaches, such as those employed by Apollo, can drive competitive advantages.
- There is potential for challenges, such as data readiness, but Apollo's methods address these effectively.
- There is no clear evidence that these initiatives are resulting in a decrease in employee numbers.
- AI initiatives are likely to reduce physical work for employees by automating repetitive, manual, or time-consuming tasks.
Private Equity
This is an investment class in which firms raise capital to acquire and manage private companies or take public companies private, ultimately aiming to sell them for a profit. These investments usually demand substantial capital commitments over several years.
Apollo Global Management is actively integrating AI into its portfolio companies to enhance competitiveness and value, as outlined in the article “Building AI Capabilities Into Portfolio Companies at Apollo” by Thomas H. Davenport and Randy Bean, published on June 17, 2025, in MIT Sloan Management Review. Their approach involves focusing on AI for digital transformation, identifying “value pools” such as product engineering and customer care, and employing a structured process for implementing AI. They also launched the $25 million Evolve incubator in 2024 to nurture AI startups and have seen success in case studies, such as Cengage and Yahoo.
The figure below shows a mind map of the strategy.
- Strategic Focus on AI: Led by Vikram Mahidhar, head of Apollo's Data, Digital, and AI team, the firm has prioritized AI to drive value creation. Mahidhar, with prior experience at Genpact and Deloitte, identified “value pools” such as product engineering, cloud transformation, sales and marketing, finance, AI, operations, and customer care transformation, with AI serving as an enabler for most.
- Structured AI Implementation: The process begins with pre-investment assessments of AI's industry impact, followed by detailed diligence (often with the assistance of external consultants) to identify specific AI use cases, which require a senior-level commitment to tools and talent. Apollo's leadership, including David Sambur, co-head of equity, emphasized generating value through digital capabilities.
- AI Incubator: In 2024, Apollo partnered with 25madison to launch the 25m Evolve incubator, nurturing 11 B2B AI startups that address capabilities such as supply chain resiliency and reputation management, aiming to supply portfolio companies and broader markets.
- Portfolio Case Studies: Successful implementations include:
- Cengage: Executing eight AI projects, achieving cost reductions (e.g., 40% in content production, 15-20% in lead generation) and launching AI products like Infosec Skills Navigator and Student Assistant, serving 1 million students.
- Yahoo: AI-driven productivity gains exceed 20% in engineering, with over 10,000 lines of AI-generated code accepted daily, and enterprise-wide AI copilots saving one hour per user weekly.
- Barnes Group: Used generative AI to index technical documents, improving service technician efficiency, yielding a fivefold return on investment in the first year.
- Univar Solutions: Deployed an AI-driven sales agent to reengage dormant customers, achieving a 30% engagement rate in a pilot.
- Broader Implications: Apollo's disciplined approach highlights AI's immediate, tangible value, making it a foundational tool for private equity value creation, as evidenced by analyzing 15,000 software purchase agreements to reduce procurement costs by over 65%.
- Research suggests that AI is increasingly seen as a value-creation lever rather than just a standalone investment opportunity. Akin Gump Strauss Hauer & Feld LLP (2025) notes that amid the hype surrounding generative AI, private equity investors are focusing on leveraging AI to transform business models and improve operational efficiencies. This aligns with Apollo's strategy of integrating AI into its portfolio companies. Large deals, like Blackstone's $16 billion purchase of Airtrunk in Q3 2024, show this. This illustrates the importance of tech infrastructure.
- FTI Consulting (2024) outlines three key strategies for AI-driven value creation in 2025: transforming core business models, centralizing AI orchestration at the firm level, and incorporating AI transformation into sell-side narratives and buy-side diligence. Apollo's AI incubator and structured implementation process exemplify these strategies, particularly by centralizing orchestration through Mahidhar’s team.
- Structured approaches are likely to enhance AI outcomes, as noted by the Harvard Business Review (Mahidhar & Davenport, 2025). The article examines how private equity firms secure executive buy-in, attract top talent (e.g., operating partners), and assess the potential impact of AI, drawing on Apollo's methodology. This includes evaluating workforce automation, data readiness, and competitive positioning, which Apollo addresses through pre-investment assessments and thorough diligence.
- Bain & Company (2025) reports that while most private equity firms are in the test-and-learn phase with generative AI, leading firms are beginning to see tangible returns. A survey of investors, representing $3.2 trillion in assets under management, conducted in September 2024, found that nearly 20% of portfolio companies have operationalized generative AI use cases with concrete results. Apollo's case studies, such as Cengage's 40% cost reduction, exemplify this progression, indicating a competitive advantage for early adopters.
- The evidence suggests that private equity plays a significant role in supporting AI innovation. The American Investment Council (2025) highlights that private equity has invested over $200 billion since 2020 in AI-supporting infrastructure, including data centers, semiconductors, and energy infrastructure. This ecosystem enables AI adoption, which Apollo leverages through its portfolio companies, such as Barnes Group's generative AI solution for technical documents.
- The World Economic Forum (2025) notes that only 2% of private equity firms expect significant AI-driven value in 2025, but 93% anticipate moderate to substantial benefits within three to five years. This suggests Apollo's early adoption positions it ahead of the curve, potentially gaining a competitive edge as AI's impact grows. This is supported by industry reports, such as BlueFlame AI (2025), which lists 10 AI use cases for 2025, including simplifying due diligence and enhancing portfolio performance.
- There are potential challenges in AI adoption, including data readiness and workforce transitions. Private Equity International (2024) notes that while more general partners (GPs), limited partners (LPs), and portfolio companies are adopting advanced technologies, issues still need to be addressed. Apollo's structured approach, which includes investing in talent and securing senior-level commitment, tackles these issues, as demonstrated by the hiring of Katia Walsh to lead AI initiatives.
- Leeway Hertz (2023) explains how AI facilitates proactive deal sourcing by leveraging the increasing global data volume, expected to reach 163 zettabytes by 2025, with 80% of this data being unstructured. Apollo's pre-investment assessments likely include similar data-driven insights, enhancing the diligence process.
- Bain & Company's Private Equity Outlook for 2025 (2025) suggests that funds with clear, differentiated strategies will outperform as dealmaking recovers. Apollo's AI focus, including its incubator and case studies, could be a key differentiator, aligning with the industry's recovery from recent challenges, as noted in the report.
Aspect | Apollo's Approach | Industry Trend (2025) |
|---|---|---|
Focus | AI as an enabler for value pools (e.g., sales, care) | AI is viewed as a value-creation lever, not a standalone |
Implementation | Structured process, pre-investment diligence | Structured approaches, executive buy-in, talent |
Innovation | 25m Evolve incubator for AI startups | Significant investments in AI infrastructure ($200B since 2020) |
Outcomes | Tangible returns (e.g., 40% cost reduction at Cengage) | 20% of firms operationalizing AI, seeing returns |
Challenges | Addresses data readiness and talent through investment | Data readiness and workforce transitions noted as issues. |
This table highlights Apollo's alignment with industry trends, especially in structured implementation and innovation.
Furthermore, Apollo's approach addresses industry-wide challenges. For example, Apollo meets the demand for data readiness and workforce adaptation through its structured implementation and investment in talent. In addition, the firm's early adoption of AI positions it to benefit from the anticipated growth in AI-driven value over the next three to five years, as noted by the World Economic Forum. Apollo's strategy also takes a forward-looking perspective. By centralizing AI orchestration and incorporating it into investment processes, as suggested by FTI Consulting, Apollo is preparing for a future where AI becomes a foundational element of private equity success. The firm's AI incubator further strengthens its competitive edge by nurturing startups that can provide innovative solutions to its portfolio companies.
In conclusion, Apollo Global Management’s integration of AI into its portfolio companies demonstrates how private equity can use technology to create more value. By blending strategic foresight with practical execution, Apollo is gaining immediate benefits and preparing for long-term growth in an AI-driven future. As the private equity industry continues to adopt AI, firms that follow similar structured and innovative strategies will likely lead the way in redefining value creation in the sector.
Note: Description of Figure I
Description of the mind map titled "Apollo's Digital & AI Strategy," which outlines the firm's journey, key players, strategic components, and innovation initiatives.
1. Strategic Shift
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Timeline: Started about five years ago.
Focus Areas: Digital transformation, analytics, and AI.
Structural Move: Created a portfolio operations team to support implementation.
Key Driver: David Sambur (Partner, Co-head of Equity) strongly promoted generating value through digital capabilities across portfolio companies.
Vikram Mahidhar (joined in 2021)
Role: Head of the Data, Digital, and AI team.
Background:
Led AI at Genpact.
Managed AI at a Genpact-acquired startup.
Early AI leader at Deloitte.
Katia Walsh
Joined later to help execute AI initiatives.
Former Chief Digital & AI Officer at multiple firms.
Apollo identified impactful areas where digital tech, especially AI, could create value:
Product Engineering
Cloud Transformation
Sales & Marketing
Finance
AI (seen as a key enabler for others)
Operations
Customer Care Transformation
A clear plan to use AI in portfolio companies:
Pre-Investment:
Assess AI’s effect on the target company and its industry.
Forecast potential impact based on current AI trends.
Use Case Identification:
Exclude high-risk options.
Focus on low-risk, high-reward opportunities.
Due Diligence:
Work with external consultants.
Examine AI's role in existing products and projects.
Implementation Plan:
Develop a roadmap for AI deployment after acquisition.
Get executive support and invest in AI talent and tools.
Mahidhar’s team offers:
Recommended AI tools
Vendor ideas
Senior hires
Consultants
Goal: Help companies become self-sufficient, with optional support.
Launched in 2024 with VC firm 25madison.
Purpose: Support disruptive B2B AI startups that:
Help Apollo portfolio companies.
Grow into scalable AI software providers.
Current Status: 11 startups working on:
Supply chain resilience
Manufacturing response
Reputation management
Goal: Develop repeatable and scalable AI use cases for business
References
Final Remarks
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