Across boardrooms and strategy sessions, one theme dominates the private equity playbook: harnessing the promise of AI to unlock new value across portfolio companies. Generative AI has captured executive imagination, with its potential to double productivity, reinvent products and transform operating models.

Despite the progress made, the outcomes are still in their early stages. Many AI initiatives are currently in pilot mode, focusing on specific applications rather than achieving broader, impactful results. This is particularly evident for private equity firms with varied portfolios. However, there is great potential to enhance collaboration among R&D teams, improve data quality and modernize infrastructure. By addressing these challenges, we can unlock efficiencies, reduce costs and accelerate innovation cycles for even greater success.

What’s missing is not ambition, but orchestration.

The need for a scalable innovation backbone

Private equity firms have long centralized functions like procurement, legal, or finance to drive efficiencies. The same philosophy now needs to be applied to AI and product innovation. Instead of each portfolio company working in silos, a shared backbone can support:

• AI-native product development, tailored to each portfolio company’s market
• Reusable agents that drive operational efficiency across IT, finance, HR and legal
• Rapid integration and modernization of data platforms to support AI scalability
• Engineering and R&D governance aligned to measurable business outcomes

Such an approach not only speeds up experimentation but also ensures that successful initiatives can be replicated across the portfolio, turning pilots into platforms.

Outcomes that matter

When powered by a robust R&D Center of Excellence model, private equity firms can unlock measurable and repeatable outcomes across four key dimensions:

1. Accelerated time-to-value
   1. Faster release cycles and reduced time-to-market through standardized GenAI “recipes,” automation accelerators and rapid prototyping of agents (e.g., sales, claims, user behavior) supported by a unified tech stack.
   2. On-demand LLMOps, model tuning, validation and observability embedded into the development lifecycle, improving launch readiness and overall impact.
2. Scaled operational efficiency
   1. Enterprise productivity agents streamline high-effort tasks across IT, finance, legal, HR and operations, driving 15–25% gains and eliminating duplicate work through shared tooling and frameworks.
   2. Intelligent platforms like HCLTech’s AIForce accelerate the software development lifecycle (DevOps, testing, etc.), shortening release timelines by at least 30%.
3. Consistency and governance across portfolio
   1. R&D visibility improves across engineering KPIs, enabling portfolio-wide benchmarking, while CxOs set measurable outcomes (EBITDA uplift, release frequency, time-to-feature) that are tracked centrally.
   2. Modernized DevSecOps and cloud-native blueprints ensure architectural consistency and reduce technical debt across inherited or carved-out companies.
4. Tangible financial and innovation impact
   1. Common data infrastructure, reusable accelerators and platform-level efficiencies reduce costs and improve speed, customer experience and innovation metrics.
   2. PE leaders can manage AI transformation with the same rigor as financial performance, driving accountability, repeatability and outcome orientation across the portfolio.

Critically, it enables private equity leaders to track AI impact with the same rigor as financial performance, bringing accountability, repeatability and strategic alignment into the heart of innovation.

How HCLTech helps bring this vision to life

HCLTech’s dedicated Private Equity Practice works exclusively with PE operating partners and value creation teams to design and operationalize scalable, center-led R&D and AI innovation frameworks.

Our approach blends:

• Deep engineering and AI expertise across verticals
• Proven playbooks for modernizing legacy platforms and accelerating cloud/data readiness
• Productivity agents and GenAI solutions that have delivered 15–25% gains for global enterprises
• Flexible commercial models aligned to outcomes, not just effort

What sets us apart is not just our technical depth, but the trust clients place in us. HCLTech is the only provider to be rated a Customer Choice in all six Gartner Peer Insights ‘Voice of the Customer’ IT services reports—spanning public cloud IT services, data center outsourcing, managed network services, cloud ERP services, outsourced digital workplace services and custom software development.

This recognition—entirely based on client feedback—underscores our ability to deliver consistent, high-performance solutions across the full spectrum of enterprise IT. Each category represents a core pillar of digital transformation and our presence across all of them is a strong signal of the value we bring to complex enterprise environments.

We’ve seen firsthand how this shared model can compress timelines, reduce costs and increase enterprise value, helping PE leaders move from potential to performance and from pilots to portfolio-wide impact.

In today’s climate, AI isn’t a bet. It’s a lever. And with the right execution partner, it can become a multiplier across your investment horizon.