By Jose Ribau, Senior Advisor and Anaqi Afendi, Analyst, Deloitte Canada.
As Canadian private equity firms navigate a rapidly evolving landscape, artificial intelligence (AI) and digital transformation have emerged as core drivers of portfolio optimization. Analysis of project work across numerous industry sectors spotlighted five practical levers for value creation using technology and AI: talent development, revenue growth, margin expansion, product differentiation, and asset protection. This article distills those insights, offering actionable strategies for general partners (GPs) seeking to maximize returns and resilience in their portfolio companies.
1. Talent: Building AI-Ready Teams
The foundation of any successful AI program is talent. PE firms that routinely assess CEO and management team readiness using objective tools—psychometric tests, leadership assessments, and digital/AI skills inventories—are often better positioned when it comes time to bring forward a deal for investment committee sign-off. Embedding digital and AI talent within management teams accelerates adoption and reduces execution risk, ensuring that new technologies are not just implemented but embraced at every level as part of the future roadmap of value creation.
Key Takeaway: Structured change management and visible leadership commitment are critical. CEO/CFO sponsorship drives alignment, while ongoing education and reskilling prepare organizations for the future of work. Only 22% of organizations feel they are highly prepared to address talent issues related to GenAI adoption, highlighting a significant opportunity for proactive investment in people (Deloitte State of AI 2024, Q1 Report.
2. Revenue Growth: Predictive Analytics and Transformation
While adoption at the portfolio company level varies based on several factors, AI-powered predictive analytics are transforming how some of these firms prioritize leads and optimize pricing. Traditional consumer brands are adopting direct-to-consumer platforms, while nimble fintechs leverage new marketing enablers to optimize sales. For example, a B2B distribution company implemented Salesforce with AI-enabled lead scoring, boosting sales productivity by 15% while also reducing the sales cycle dramatically. Similarly, a PE-backed apparel company launched a direct-to-consumer channel using advanced digital tools and achieved 30% YoY online sales growth. In another example, a mid-sized neo bank upgraded their marketing tech stack and realized a 25% increase in website conversion within 3 weeks of implementation.
Key Takeaway: Even long standing solutions like predictive lead scoring can make a big difference and have become inexpensive with increased competition in this space. Despite being a proven capability however, most portfolio companies are still at a relatively early stage in their data science and AI adoption, as noted in a recent report by Private Equity International
Source: Private Equity International | PEI | Global Private Equity News & Analysis
3. Margin Expansion: Automation and Optimization
Margin expansion is increasingly driven by intelligent automation. Process automation and Generative AI capabilities are known to streamline manual tasks across finance, HR, and customer service operations with newly found capacity being used by employees to focus on higher-stakes work. With the adoption of AgenticAI solutions and machine learning companies are also better able to perform demand forecasting and inventory management at scale. A global mining company used GenAI to forecast demand while optimizing logistics costs and reducing CO₂ emissions by 20%. Siemens is a well documented example of automation potential. The multinational technology company automated its AP function globally to extract data from over 1 million invoices, reducing manual effort by 60% and processing time from days to hours. On top of time savings, Siemens also realized a 40% reduction in processing costs. These margin-focused initiatives carry an in-year ROI payback while also enhancing the company’s operations making them more efficient and robust over the longer term.
Key Takeaway: Unlocking value through automation requires robust data governance and cyber controls to protect enterprise value and investor trust. Agile pilot-to-scale approaches with clear KPIs (ROI in 12–18 months) prove impact within the typical PE hold period and help provide resilience within the P&L if sales momentum slows. Source: Creating Value through Technology.
4. Differentiation: Data Monetization and New Business Models
Portfolio companies are leveraging large customer datasets to create new subscription or analytics products, moving legacy infrastructure to the cloud for scalability, and capturing cross-sell opportunities through predictive insights. A global logistics provider turned shipping route data into a subscription SaaS product, creating a new revenue stream. Specialty manufacturers migrating ERP to the cloud have realized significant IT spend reductions and real-time visibility.
Example: At the 2025 Super Return conference on a panel focused on Technology as a Value Creation lever, Aurelius shared that one of their portfolio companies – SkyChefs – used AI sensors to optimize inflight menus, improving meal profitability and reducing costs by 25%. At the same time, this new use of data allowed the service provider to link their value to improved customer satisfaction, thereby gaining a valuable competitive edge for contract discussions at the next renewal (Source: Super Return).
Key Takeaway: Knowing where to start can be the biggest challenge. Learning from proven use cases is a great way to kick start the design thinking process that ultimately leads to customized value creation. Deloitte AI Doissier: 80 AI Use Cases.
5. Asset Protection: Cybersecurity and Risk Management
The cyber landscape is evolving, with AI making sensitive data and financial processes more vulnerable. Legacy systems and outdated partners can become exit risks if proactive risk management is delayed. Network segmentation and robust cybersecurity protocols have protected companies from malware spread, safeguarding value and reputation. Publicly traded firms have suffered average stock declines of 5% when data breaches are disclosed (Infosecurity Magazine). A recent report by the Canadian Cybersecurity Network advises that emerging technologies such as Generative AI help increase defensive measures but also enable sophisticated attacks like deepfake-based fraud and identity theft. ITDR (Identity Threat Detection and Response) has emerged as a critical strategy to combat these threats, addressing identity vulnerabilities in cloud and hybrid environments. The State of Cyber Security in Canada, 2025.
Key Takeaway: Early integration of tech diligence separates hype from reality and aligns AI initiatives with the deal thesis. Structured risk management frameworks, including data governance and explainability, are essential as global regulators increase scrutiny
Practical Considerations and Risks
While the promise of AI is substantial, PE firms must navigate risks such as technology spend without adoption, underestimated change management, cybersecurity vulnerabilities, underinvestment in talent, timing mismatches, and overestimating AI capabilities. Human oversight remains critical to counter risks of inaccuracy, bias, IP violation, and privacy concerns. Only a quarter of organizations feel highly prepared to address governance and risk issues related to GenAI (Deloitte State of AI 2024).
Conclusion
AI and digital transformation are no longer optional for private equity value creation—they are essential levers for growth, efficiency, differentiation, and risk management. By investing in talent, embracing predictive analytics, automating operations, monetizing data, and safeguarding assets, GPs can unlock new levels of portfolio performance. As competition intensifies and the bar for value rises, those who act decisively will lead the next wave of PE innovation.
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Leveraging real-world examples and industry data, this article offers a practical roadmap for private equity leaders to unlock portfolio potential with AI. For further discussion or to access Deloitte’s latest research, reach out to our team or follow us on LinkedIn. For more insights on portfolio optimization and AI-driven value creation, connect with Deloitte Canada’s Private Equity practice.
