Scaling Data & AI Value Across PE Portfolios
AI-boosting EBITDA & Valuation
Why Should PE Funds Invest In AI-Enabling Their Portfolio Companies?
Creating AI Value within a portfolio company will drive its financial performance and expand its valuation multiple.
Scaling AI Transformation across a fund’s portfolio decreases risks and costs, while making sure that AI opportunities for growth are systematically seized.
ai value for pE funds
AI Transformation can boost several components of a portfolio company’s EBITDA:
- Revenue and Market Share growth thanks to better products and data-driven sales & marketing,
- Lower costs through operational efficiencies,
- Higher margins thanks to pricing optimization and improved customer experience.
Beyond making better products and transforming the experience of existing customers, AI innovation generates new revenue streams and attracts entirely new client segments.
Data and AI Insights become products in their own right and enable new business models.
Turning a traditional, data-rich company into an AI-first company improves its financial KPIs. But that’s only half the valuation story.
Data/AI capabilities and business model innovation underpin a credible thesis for long-term future growth and market leadership that gets reflected in increased valuation multiples.
An AI-First company not only knows how to turn its own data into gold. It also has learned to connect with and integrate data from customers, suppliers and partners.
A smart strategic buyer will recognize and value this structural transformation at its fair price.
AI Transformation - PE Lifecycle
Our End-To-End Approach To Create AI Value For PE Investors
1. Screening
How will AI affect this particular industry in the long run? What is its current stage of disruption?
Once these questions are answered, the AI value potential of target companies can be assessed using simple AI Maturity metrics.
2. Due Diligence
What is the target AI end-state for this short-listed company? What is the current gap, and how much can be expected to be filled during the holding period? What are the related costs and risks?
Sizing the opportunity and cost helps to set the right price. It also establishes AI credibility with attractive targets.
3. Deal Making
Based on a high-level plan for the AI Transformation of the target company, executive commitment can be secured, e.g. with covenants.
This can be achieved by tying the release of funding instalments to the achievement of AI Maturity thresholds and AI ROI targets.
4. Holding & Growing
As the portfolio company increases its ability to create value from its data, the ROI of AI is tracked with and driven by operational KPIs.
The most marketable aspect of the AI Transformation lies in building the operational capability to create sustainable AI value: data-driven people, processes and structure.
5. Exit
Financials (EBITDA gains attributable to AI) demonstrate the hard-currency value delivered by the AI-transformed portfolio company.
Additionally, the organization’s ability to amaze customers with AI, to create new data revenue streams and enter new markets (all evidenced by AI Maturity metrics) helps justify the expanded valuation multiple.
6. Post-Exit Support
A strategic buyer with an ambitious integration roadmap will value continuity in the AI Transformation support. This will help reduce the risk profile of the transaction
AI Transformation At Scale Across PE Portfolios
The Rationale For Running AI Initiatives At Fund Level
Cross-portfolio AI programs mean faster learning, a larger brain to collaborate on common issues, and economies of scale.
In short, accelerated ROI across the board.
Accelerated Learning Curve
Multi-company AI education programs enable participants to learn from each other and benchmark themselves against their peers.
This interactive and competitive setup is even more potent when combined with AI case studies based on real data and business challenges from participating companies.
Training programs running across a portfolio enable such sharing, as critical confidentiality issues are removed thanks to common ownership.
Cross-Portfolio Innovation & Projects
As participants from different industries work together during AI trainings, collaboration networks coalesce, and out-of-the-box innovation arises. Shared lessons learned accelerate the AI Maturation process across portfolio companies.
Opportunistic joint projects on common challenges, like Data Infrastructure, AI for SCM or AI for HR, further the benefits of scale.
Economies of Scale
Data & AI technology is not cheap, and costs can become a drag on ROI. Cross-portfolio purchasing initiatives increase bargaining power towards vendors and enable the sharing of critical deployment resources.