Imagine receiving a phone call about a promising deal proposition and, before the conversation concludes, instantly accessing data-driven investment insights — complete with ROI calculations and risk assessments. Or picture opening a dashboard that processes thousands of market signals in real-time to identify the top investment opportunities for your fund across multiple sectors and subsectors. These scenarios, once considered beyond reach, are now becoming a reality as generative AI reshapes the investment decision-making ecosystem.
These enhanced and easily accessible AI capabilities come at an opportune time. The investment landscape is more competitive than ever, with sovereign wealth funds, private equities, and principal investors navigating capital-heavy markets with limited high-quality deals. Recent economic and regional megatrends have led to an abundance of funds and dry powder but fewer opportunities, making the “sure bet” a far more elusive proposition.
Many sovereign wealth funds also grapple with inefficiencies, particularly when it comes to using human capital effectively. As a result, investment professionals are often consumed by non-core, low-value activities such as carrying out research, processing documents, analyzing data, and managing processes. Generative AI can address this by automating routine tasks, allowing professionals to focus on strategic decisions and value creation.
But where is AI best placed to help sovereign wealth funds create that value for the long term? How can it drive efficiencies within both funds themselves and their portfolio companies? Further, given its transformative effect across all types of organizations and institutions, should funds prioritize AI as an asset class in its own right?
We will explore these questions, confirming that AI is indeed the future for sovereign wealth funds.
Leading funds are already riding the wave
For funds not yet using AI for operational efficiency and competitive advantage, the time to act is now, as several leading funds are already implementing it.
Singapore’s GIC has begun using generative AI tools to produce investment report drafts, support internal audits, and assist with due diligence for private equity investments. Temasek, also in Singapore, has made AI a core part of its operations, helping portfolio companies innovate and enhance digital consumer engagement.
Additionally, Norway’s Norges Bank Investment Management (NBIM) has leveraged AI to boost productivity by 10 percent compared to last year.
How AI is transforming funds
These are just a few examples. However, AI can significantly improve efficiencies across the entire sovereign wealth fund life cycle:
- Deal sourcing
AI scans markets to identify investment opportunities across sectors, processing real-time data from sources, such as financial news and social media, to uncover trends and undervalued assets. - Due diligence
AI automates the analysis of financial statements, legal documents, and compliance reports. Natural language processing extracts crucial information from vast unstructured data, reducing due diligence from weeks to days and minimizing errors. - Value creation
AI optimizes portfolio company operations, streamlining supply chains by reducing waste and improving quality. It can anticipate equipment failures, forecast demand, maintain optimal inventory levels, and lower costs. AI also analyzes customer data, helping to design personalized marketing strategies that boost engagement and revenue growth across portfolio companies. - Exit
AI streamlines pitchbook and prospectus creation for IPOs and divestitures, automating data compilation and enhancing accuracy. Its analytical capabilities also assist in identifying and assessing high-potential investors, ensuring profitable exits. - Back-office functions
AI benefits compliance monitoring and risk management, automatically tracking regulatory changes and generating reports. Machine learning models detect anomalies, allowing proactive risk mitigation. AI also flags fraud, market instability, and credit risks for timely intervention.
Funds can also use generative AI for a wide range of content and communication-led activities, such as designing marketing collateral, using chatbots in employee training, improving the quality and speed of code generation, testing the customer experience (for example, using the fund’s communication channels), and ensuring technical quality control.
In a nutshell, there is no shortage of potential AI applications for sovereign wealth funds to consider. In fact, the problem is often choosing where to start and knowing how to prioritize the roadmap in a way that captures quick wins and sets the organization up to generate long-term value.
When it comes to quick wins, there are three key steps to follow, in our experience:
- Identify areas where AI can capture the highest value by assessing current process inefficiencies.
- Focus on quick wins, like automating routine data tasks and accelerating analysis.
- Prioritize high-value use cases and quick wins, developing a roadmap with pilot projects to demonstrate AI’s value before scaling.
To ensure long-term success, funds should focus on key principles:
- Set up an in-house AI platform that is scalable, secure, and integrated with existing systems.
- Identify AI champions across the business to drive adoption and align projects with strategic objectives.
- Hire AI talent and upskill employees to foster a culture of continuous learning.
- Measure success by establishing KPIs that track operational efficiency, investment performance, and risk management.
Where to go from here?
As AI reshapes the financial landscape, sovereign wealth funds can unlock significant value. This transformation isn’t about reducing headcount but about merging AI’s capabilities with human expertise.
Funds that integrate AI with human judgment, ethical considerations, and strategic vision will achieve faster, more significant gains, navigating the complexities of investment and converting “dry powder” into lasting value.
Javier Herrera is a partner in Kearney’s Middle East & Africa Transactions & Transformation Practice. Martin Pavlica serves as a principal in the same practice, while Akshay Goel is a manager in Kearney’s Middle East & Africa Digital & Analytics Practice.
