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Overcoming The Top AI Challenges for PE Portfolio Companies in 2025

By January 27, 2025No Comments

If you’re leading a portfolio company and wondering how to make AI work for you, you’re not alone. Private equity (PE) firms are constantly seeking innovative ways to create value in their portfolio, and AI has emerged as a pivotal asset with exciting opportunities for growth. 

Despite its groundbreaking potential, navigating AI adoption can feel like walking a tightrope – particularly for PE-backed businesses operating under tight timelines and close oversight. With AI adoption becoming a competitive necessity across industries, how do you overcome these hurdles?

In this blog post, we will explore five key AI challenges that portfolio companies are likely to face in 2025 and offer actionable strategies to help you overcome them.


1. Talent Shortages in a Competitive Market

The demand for skilled AI professionals has never been higher, but the supply remains limited. Finding specialists in niche areas like natural language processing (NLP), computer vision, and machine learning engineering is particularly difficult – and retaining them can be just as tough. 

For portfolio companies, the challenge is even more prominent. You are not just competing with other businesses for talent, you’re up against deep-pocketed tech giants and agile startups.

How to Overcome It:

  • Think global. Tap into remote or fractional talent from a broader talent pool to access expertise on-demand, especially for short-term or niche projects.
  • Upskill existing employees. With the right training and support, they can step into critical AI roles.
  • Build partnerships with higher education and research institutions to engage with emerging talent before others do.

2. Budget Constraints and Resource Allocation

AI can feel like an expensive gamble, especially for PE-backed companies under pressure to cut costs and deliver quick returns. Between hiring specialists, setting up data infrastructure, and acquiring the right tools, it’s easy to feel stretched too thin to make it work.

But AI doesn’t have to break the bank. Strategic planning can help you make big moves with small budgets.

How to Overcome It:

  • Start small. Test the waters with small-scale pilot projects that demonstrate ROI before scaling up.
  • Focus on high-impact, low-cost applications. For example, AI applications like process automation can deliver quick wins and measurable results.
  • Leverage fractional talent. Bring in experienced AI professionals on a project-by-project basis, cutting costs without compromising quality.

3. Data Readiness and Quality Issues

AI thrives on high-quality, structured data. Unfortunately, for many portfolio companies, data readiness is a significant hurdle. Legacy systems, inconsistent formats, and siloed databases make it difficult to provide the structured and accessible data AI models require.

Add to this the fact that many PE-backed businesses are undergoing digital transformations after investment, and you’ve got a perfect storm of challenges. Without a solid foundation, even the most sophisticated AI tools will struggle to deliver results.

How to Overcome It:

  • Conduct a data audit. Begin by assessing your existing data for quality, availability, and structure. Identify gaps and weaknesses that could derail AI initiatives.
  • Invest in data infrastructure by Implementing tools to clean, integrate, and maintain data.
  • Build scalable data pipelines. Engage experienced data engineers to build scalable, automated pipelines that ensure your systems are AI-ready now and adaptable for future needs.

4. Uncertainty About ROI

For C-suite executives, the big question often isn’t can AI work – it’s will it deliver measurable value? Concerns about upfront costs, implementation hurdles, and unproven technologies often make stakeholders hesitant to greenlight projects.

This skepticism isn’t unfounded. Without clear goals and metrics, AI investments can feel like a gamble. But with the right approach, you can transform uncertainty into confidence.

How to Overcome It:

  • Start with clear use cases. Focus on initiatives with well-defined, quantifiable outcomes, such as predictive maintenance, customer segmentation, or cost-saving automation.
  • Define KPIs early, monitor rigorously, and build stakeholder trust by tracking progress.
  • Aim for quick wins with projects that can deliver tangible results quickly, helping to build momentum and secure buy-in for larger initiatives. 
  • Stay flexible and be prepared to pivot based on results. This ensures that resources are always allocated to the highest-impact opportunities.

5. Scaling AI Across the Organisation

Many portfolio companies begin their AI journey with small, isolated pilot projects. While these pilots can highlight potential, scaling AI across an organisation poses an entirely different challenge. It requires more than just technical knowledge – it demands alignment across teams, sustained resources, and a culture that embraces change.

Without a clear strategy, scaling efforts risk stalling due to competing priorities and fragmented workflows.

How to Overcome It:

  • Develop a scaling roadmap to gradually expand successful AI initiatives across teams and departments, ensuring alignment with broader business goals.
  • Cross-department collaboration is key to ensure AI tools integrate seamlessly with existing workflows.
  • Build agile teams: Combine in-house staff with external experts to maintain continuity while accessing specialised skills as needed.

AI adoption is no longer optional for PE portfolio companies. It’s a necessity to stay competitive and create value in 2025. However, success requires addressing challenges head on with strategic planning and innovative solutions.

Strategies like accessing fractional AI talent, focusing on high-impact projects, and investing in robust data foundations will help portfolio companies overcome barriers and make the most of AI’s immense potential.

Ready to start your AI journey? Success begins with a clear strategy and partnering with the right experts. If you’re looking to access AI expertise for your portfolio company, we’re here to help. Get in touch today.

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