Practical AI For Private Equity Operating Partners

A structured AI playbook marries tangible performance gains and higher exit valuations

AlixPartners has created a four-point playbook to meet those challenges and identify AI-driven opportunities. The points will align with business goals and serve to establish a plan for successful execution in order to achieve sustainable performance improvements and higher exit valuations.

Operating partners (OPs) are on the front line in identifying artificial intelligence (AI)-enabled solutions that can quickly deliver a measurable impact on value creation across their portfolios—all the way through to exit.

OPs are uniquely positioned to spot, vet, and scale AI use cases. The process requires a thorough assessment of their own capabilities and the readiness of their portfolio companies (portcos) to identify the operational and technical steps in a digital transformation.

Properly equipped OPs can advise portco CEOs about the kinds of changes that are viable. They can direct leadership to explore and adopt AI and machine learning to accelerate and enhance earnings before interest, taxes, depreciation, and amortization (EBITDA) expansion.

AI can provide more levers to enhance profitability, but for many OPs, AI is a new discipline. Our studies have found that more than 80% of AI programs still fail, usually due to misalignment across leadership on which use cases to pursue, user adoption, and lack of clarity on how to measure success. 

OPs must address four critical challenges as they explore value-creating AI solutions:

1. Finding opportunities that enhance performance across diverse portfolios		AI Readiness and Opportunity Mapping Figure out which AI opportunities have meaningful value creation potential – and whether the portco is ready to pursue them
2. Prioritizing use cases that balance immediate returns with strategic positioning		Strategic Roadmap Development Build a phased plan that sets priorities and gives the team a clear path forward
3. Navigating rapidly evolving AI and other technology environments		Execution & Change Management Get models built, deployed, and adopted – while managing change and keeping teams aligned
4. Establishing exit readiness with measurable results matching investment timelines		Value Scaling & Exit Preparation Expand what’s working and show how AI is already creating value–while setting up the story for more to come

1. Finding opportunities that enhance performance across diverse portfolios

AI Readiness and Opportunity Mapping

Identify the AI opportunities

OPs can start by identifying AI opportunities with meaningful value creation potential and the readiness of portcos to pursue them. OPs can then focus time and resources where AI can create the greatest value and identify repeatable use cases that can be scaled.

OPs are looking for an edge and are aggressively exploring ways to monetize data, optimize its value, and drive decision-making. The development, assessment, and prioritization of an initial set of practical use cases such as reducing customer churn is crucial. 

Begin by identifying return on invested capital (ROIC) or EBITDA opportunities across a range of functions with a view to identify how and when AI can affect key metrics, including revenue, margins, and working capital. Map the use cases to ensure they align with the firm’s broader investment thesis and established exit goals.

Is the organization ready? 

OPs, together with portco leadership, also have to confirm the organization’s level of readiness to be able to design, launch, and implement new AI initiatives. The rolling out of AI is typically gated by concerns about complexity and risk, and the identification of entry points requires thorough evaluations of both the opportunity set and available internal resources. Assess readiness across five key areas:

• Data infrastructure
• Technology stack
• Leadership alignment
• Talent and capabilities
• Risk and compliance

Evaluate each area by means of a simple three-point scale, and compile the data to create a heat map for quick interpretation of the findings. The effort will result in a clear visual of where and where not to proceed with pilots of AI initiatives.

Opportunity mapping is key

Now that the organization’s capabilities are clear, it’s time to determine where we can win. Identify high-impact and achievable use cases related to revenue growth, margin expansion, working-capital improvement, and strategic differentiation. In the analysis, the use of a simple impact-versus-feasibility matrix will help in providing a clear picture of where to focus. Classify which use cases result in quick wins or strategic bets and which cases will result in both. The resulting prioritized list will pave the way to building your strategic roadmap.

2. Prioritizing use cases that balance immediate returns with strategic positioning

Strategic Roadmap Development

Build a simple, phased plan with portco leadership to set priorities, maintain focus, and provide opportunities that identify patterns that can be scaled

An effective strategic road map consists of a phased plan, prioritized use cases for each initiative, and alignment with the value creation plan. As with other project management office (PMO) plans, the roadmap should specify clear ownership, set forth success metrics, list the key milestones, and detail the dependencies to drive cross-functional accountability from Day One. 

Stakeholder buy-in is critical

This roadmap and plan must be socialized and approved by all of the key stakeholders in the functions involved. Stakeholders have to support, prioritize, and take ownership of the plan to ensure its success. Without support from all of those in all of the functions involved, an initiative risks becoming stalled midplan, resulting in wasted time, resources, and, in some instances, lost trust between OPs and portco CXOs.

Spot cross-portco patterns to accelerate scale

Share best practices and key learnings once a new AI pilot has proven successful. An OP can identify where these initiatives could be repeated to benefit other companies in the portfolio. Bringing leadership functions together across the portco to share and learn from one another will facilitate faster implementation and have greater impact on value creation.

3. Navigating rapidly evolving AI and other technology environments

Execution & Change Management 

OPs are in pole position to ensure buy-in from portco stakeholders that clears roadblocks and offers clear incentives for participation and accountability for delivery

AI success isn’t about one leader having all the answers; it’s about assembling the right people and empowering them to execute. Leadership trumps technology every time.

OP conversations with CEOs and chief technology officers (CTOs) must include the expense and potential benefits of AI-enabled tools, mapping potential risks as well 
as opportunity costs when selecting where to deploy. This includes providing guidance from the start on how the potential vulnerabilities of AI tools when it comes to cybersecurity protection and governance impacts will be addressed. OPs also have to confirm that the portcos have the necessary internal and external capabilities and resources. 

Drive. Build. Support.

Leaders should focus on building and deploying models armed with the right team of stakeholders, the required resources, and a clear and strategic road map and plan. Establishing a PMO, complete with change management experts, will ease employee adoption while keeping teams aligned. Communicating—and celebrating—key milestones drives employee engagement and adoption across an organization.

In addition to the success metrics identified in the strategic road map, each phase of the project plan should include clear metrics for deployment, performance, and adoption. Through regular communications and progress reporting to stakeholders, OPs and CEOs can partner to ensure the initiative’s success by identifying and removing roadblocks early and helping sustain momentum. 

The performance of AI pilot programs should be integrated with financial evaluations, continually refined, and include clear processes and communication to drive change. This includes the support of continued adoption through targeted training and hands-on guidance. Regularly enhancing AI models by incorporating new data and adapting to shifting patterns will build and sustain accuracy. And as more and more AI initiatives get deployed across the portfolio, OPs have the opportunity to identify more and more areas to scale, such as common vendors, repeatable models, and shared playbooks.

4. Establishing exit readiness with measurable results matching investment timelines

Value Scaling & Exit Preparation

Sellers have to think like the buyers they aim to attract and have to identify the types of opportunities buyers may spot during their due diligence

Establishing AI as a core enterprise competency enables early adopters to gain competitive advantage via tangible improvements in such areas as talent acquisition, workforce planning, and operational efficiency. 

Start with high-impact areas

When preparing for exit, OPs can show how AI is already creating value while setting up the story for more to come. OPs should highlight where AI is already delivering results, point out where efficiencies have been gained, and show buyers where more value can be unlocked post-exit. Focus on quantifying and framing AI impact in both financial and operational terms that support the exit narrative and include successful use cases.

Timing the ability to demonstrate ROI from AI investments with the exit cycle can be tricky but shouldn’t hold back rollouts. Even if AI proof-of-concept (POC) initiatives are still in their early stages, demonstrating expected lift potential to buyers can be beneficial. For example, a POC project for using AI to improve customer service can show a prospective buyer that cost reduction opportunities remain in support of a higher valuation. When the cost and revenue benefits are clearly quantified and communicated, they can support exit narratives that justify meaningful valuation premiums.

Three key steps for OPs when the exit is in sight: 

1. OPs should ensure scaled AI initiatives and POCs are clearly reflected in exit materials.
2. Leadership should work with OPs to pressure-test that AI-driven gains are measurable, defensible, and repeatable
3. OPs and CEOs can collaborate on a plan that positions AI capabilities as a foundation for future value creation

Conclusion

OPs can use this playbook to unlock AI’s outsized impact on performance and exit value. But AI can’t do it alone; it takes an OP who’s developed an initial skill set and who has knowledge of the evolving ecosystem, matched to a business case with a strategic roadmap and coordinated with committed leadership and stakeholders. But it can be done.

We are seeing more and more high-performing companies thoughtfully apply AI and machine learning to increase sales, cut costs, and improve customer satisfaction—all at once—with higher exit valuations to complete a virtuous cycle.

Download the playbook here.