In an era of economic volatility, traditional portfolios of equities and bonds often fall short in delivering desired returns or hedging risks. Enter alternative assets—a diverse array of investment opportunities spanning private equity, real estate, cryptocurrencies, renewable energy projects, and collectibles. Once the exclusive domain of institutional investors and high-net-worth individuals, alternative assets are increasingly accessible to a broader investor base, thanks to technological advancements and evolving market dynamics. AI is emerging as a key catalyst, reshaping how these investments are created, evaluated, managed, and traded.
AI Is transforming alternative assets
The heterogeneity and opacity of alternative investments pose challenges in evaluation, liquidity, and risk management. Generative and agentic AI are proving to be transformative forces, offering novel capabilities that significantly enhance decision-making, operational efficiency, and market exploration.
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1. Enhanced due diligence and research: Generative AI, known for generating insights from vast amounts of structured and unstructured data, has a profound impact on data analysis and investment strategy development. By processing datasets such as financial records, market trends, and social sentiment, generative AI uncovers patterns that traditional methods might miss.
These capabilities are especially powerful in private and alternative asset markets, where data sources are often limited or incomplete. For example, generative AI systems can evaluate thousands of private companies simultaneously, identifying potential acquisition targets before they appear on traditional radar screens. In real estate, AI analyses foot traffic patterns, demographic shifts, and local economic indicators to identify opportunities. Similarly, in art and collectibles, it revolutionises pricing by analysing auction results, market trends, and artistic characteristics. AI can simulate market scenarios, generate synthetic data for stress-testing portfolios, and craft detailed investment forecasts. Generative AI also excels in producing natural language summaries and visualisations of complex financial information, simplifying data-driven decision-making for investors. For instance, a leading wealth management firm employs generative AI-based assistants to help wealth managers craft tailored strategies.
2. Investment process: Agentic AI, with its autonomy and advanced decision-making capabilities, acts as an intelligent agent within the investment process. These systems can autonomously monitor markets, identify opportunities, and execute trades or transactions based on predefined goals. In hedge funds and cryptocurrency trading, agentic AI dynamically adapts to market fluctuations, reacting faster than human analysts. One leading bank, for example, uses agentic AI to conduct due diligence, monitor fraud, and manage risks by tracking and responding to various signals.
3. Enabling creation of alternative asset classes: While traditional alternative assets like private equity and real estate remain important, new categories are emerging, often enabled by AI. Cryptocurrencies, for instance, have evolved beyond basic digital currencies to include AI-governed decentralised autonomous organisations (DAOs), sophisticated smart contract-based financial instruments, and tokenised real-world assets. These developments fundamentally shift how digital assets are perceived and utilised.
4. ESG in alternative assets: AI is also enhancing the focus on environmental, social, and governance (ESG) factors in alternative investments. By evaluating ESG metrics and providing quantifiable impact measurements, AI ensures investments align with sustainability goals. For instance, a leading European bank leverages generative AI to analyse ESG reports and streamline compliance processes for alternative asset classes.
5. Investor awareness and democratisation: Generative and agentic AI are democratising alternative investments by reducing entry barriers. Generative AI creates educational tools and content to guide smaller investors, while agentic AI provides personalised investment management. As alternative assets become more accessible to retail investors, personalisation becomes critical. Agentic AI-driven platforms tailor investment strategies to individual risk tolerance, financial goals, and market outlooks. Robo-advisors powered by agentic AI are helping novice investors explore alternative assets, broadening the investor base.
The road ahead
However, challenges persist. The adoption of AI in alternative assets must address concerns around data privacy, transparency, algorithmic bias, and ethical considerations. Regulatory frameworks also need to evolve to keep pace with technological innovation, ensuring investor protection without stifling growth. Establishing responsible AI guardrails and governance is imperative for organisations leveraging AI in alternative asset management. The future of alternative assets is undeniably intertwined with AI, heralding a new era of innovation in asset management.
Sachin Kamat, VP & Head of Capital Markets, Financial Services at Infosys
