For COOs, CIOs, heads of due diligence, and platform leaders at RIAs, asset managers, broker-dealers, custodians, and fund administrators, the ability to monitor these complex assets in real time is no longer a luxury—it’s a necessity. Teams of AI agents, working collaboratively as intelligent, autonomous systems, are revolutionizing how firms navigate this opaque and dynamic market. These teams of AI agents offer a rare opportunity to achieve smarter investing and deeper risk awareness without relying on third parties or increased costs.
In April and May 2025, global markets faced significant turbulence, from tariff-driven trade disruptions to emerging risks in private markets. Politics aside, these challenges, coupled with evolving regulatory demands, highlight the transformative potential of teams of AI agents. By analyzing fund managers, monitoring exposures, automating due diligence, and enhancing transparency, these systems empower investment leaders to stay ahead in uncertain times. This blog explores how teams of AI agents are reshaping alternative asset monitoring and why now is a pivotal moment for modernization.
Traditional due diligence in alternative investments is a time-consuming, labor-intensive process, often requiring weeks to evaluate fund managers, strategies, and risks. Teams of AI agents are transforming this by working together to process vast datasets—financial statements, market trends, and unstructured sources like news and social media—in real time. Unlike standalone AI tools, these collaborative systems distribute tasks across specialized agents, with some extracting data, others analyzing patterns, and others generating insights, delivering unparalleled speed and accuracy.
A January 2025 Romina Day report noted,
"AI Agent powered systems now scan social media, news articles, and financial blogs to gauge market sentiment in real-time, critical for financial risk management."
This capability proved vital during April 2025’s market volatility, when U.S. tariff announcements sparked sharp intraday swings and record-breaking trading volumes, as reported by Reuters. Teams of AI agents enabled firms to assess fund managers’ creditworthiness and operational risks swiftly, with tools like those used by JPMorgan Chase cutting research time by 95%, per industry insights. For heads of due diligence, this means moving from periodic, reactive reviews to continuous, proactive monitoring—essential when market shifts, like those in April 2025, can alter risk profiles overnight.
The market turbulence of April and May 2025 underscored the need for real-time oversight of alternative investments. The Financial Times reported that President Trump’s tariff proposals, initially feared to reach 100%, were potentially moderated to 50–60% after lobbying, yet they still clouded economic forecasts and slowed growth. Just yesterday we saw some regional tariffs reduced to 30% after weekend discussion.
The IMF’s April 2025 Global Financial Stability Report further highlighted risks in private markets, warning that
“Highly leveraged financial institutions and their nexus with banking systems could amplify volatility. These events exposed vulnerabilities in private credit and illiquid assets, where traditional monitoring often lags.”
Teams of AI agents address this by providing dynamic, coordinated oversight. Each agent focuses on specific data streams—market feeds, enterprise systems, or geopolitical signals—while collaborating to deliver a unified view of exposures across strategies. This approach flags correlations or risks, such as those noted in the IMF’s October 2024 report:
“AI models could generate portfolios across different asset classes, geographic regions, and trading venues, creating correlations and interconnectedness that are not relevant at the current juncture.”
For CIOs and platform leaders, this translates to real-time insights into liquidity risks or leverage spikes. During April’s tariff-driven swings, firms using AI agent teams adjusted strategies rapidly, minimizing losses. As BlackRock’s COO Rob Goldstein stated in December 2024, AI’s ability to
“Automate processes and improve data handling” is critical for agility, and collaborative AI teams amplify this advantage..
Private markets face growing geopolitical and regulatory risks, amplified by recent events. In April 2025, the Wall Street Journal reported that Trump’s tariff recalibration created “deep uncertainty” for investors, prompting capital shifts away from U.S. markets. The IMF’s April 2025 report echoed this, noting that “geopolitical risk events… can trigger financial market volatility,” especially in emerging markets with limited fiscal buffers. Meanwhile, regulatory scrutiny of AI in finance is intensifying, with the SEC and GDPR emphasizing explainability and transparency, per 2025 regulatory updates.
Teams of AI agents excel in this environment by integrating diverse data—trade policies, capital flows, and regulatory changes—into cohesive risk analyses. Specialized agents assess how tariffs might impact a private equity fund’s supply chain or a real estate portfolio’s financing costs, while others ensure compliance with regulatory demands.
Imagine a hedge fund manager, Priya, who tracks a portfolio of private equity investments in renewable energy. A sudden tariff hike on solar panel imports from China hits the news. Within hours, supply chain costs spike, affecting her portfolio companies’ valuations. In the past, Priya might have spent days gathering data, consulting analysts, and recalibrating models. Now, teams of AI agents handle this in real-time, pulling data from global markets, news feeds, and supply chain logs to deliver instant insights. Given the nature of the asset class, perhaps a position readjustment is not necessary, but the data collected is vital to adjust in real time her potential outlook, communicate intelligently with her LP’s and understand where to focus her energy on next steps.
A February 2025 World Economic Forum report highlighted AI’s ability to “flag emerging industries or undervalued assets” by analyzing geopolitical risks and market sentiment. For fund administrators and custodians, AI agent teams automate compliance checks and generate auditable decision trails, reducing manual workloads while enhancing risk visibility.
Traditional due diligence methods, often conducted quarterly or annually, are struggling to keep up with the fast-paced nature of today’s trade environment. These fixed review cycles leave significant monitoring gaps, making it easy for unexpected risks to slip through the cracks. For example, a sudden tariff increase that drives up input costs might go unnoticed until the next scheduled review - far too late to mitigate the impact or adjust an allocation strategy.
"We want to free the lawyer from mundane, routine tasks, so that they can focus on what matters - strategy, advice, and judgment. This has become the mantra for my team." - David Wakeling, Global Head of Markets Innovation Group (MIG) and AI Advisory Practice, A&O Shearman
These challenges make it clear that businesses need more dynamic and integrated approaches to risk detection.
As trade regulations evolve at a breakneck pace, the ability to reassess risks swiftly is no longer optional - it’s essential. Delays in risk analysis, particularly during critical periods like earnings seasons, can hinder strategic decision-making. This highlights the growing need for automated, rapid risk assessment tools.
The limitations of traditional due diligence are especially glaring in situations that demand quick scenario testing and impact analysis. When trade policies shift, businesses must act fast to understand how these changes could affect investments across different sectors and regions. Relying on outdated methods for such complex and time-sensitive tasks only adds to the challenge.
Unlike standalone AI models, teams of AI agents work collaboratively, each specializing in a task—data collection, sentiment analysis, predictive modeling, or risk assessment. This division of labor mimics human teams. Yet, it operates at a scale and speed humans can’t match. For instance, one agent might scan X posts for real-time market sentiment, while another cross-references trade data to predict tariff impacts.
The convergence of market volatility, geopolitical shifts, and regulatory pressures in 2025 marks a turning point for investment management. Teams of AI agents are strategic enablers, allowing firms to modernize without increasing headcount. By automating due diligence, enabling real-time monitoring, and enhancing risk analysis, these systems empower allocators and asset managers to navigate complexity with confidence.
As AI technology advances, its applications in alternative asset monitoring will expand. We are already seeing AI agents integrate with blockchain for enhanced data security and with IoT devices for real-time supply chain tracking. The future promises even deeper integration, with AI agents potentially predicting market shifts before they occur, based on patterns imperceptible to human analysts.
The benefits are transformative: faster decisions, deeper risk awareness, and improved transparency. As the IMF noted in April 2025, “financial institutions and their oversight bodies should allocate sufficient resources to identify, quantify, and manage [geopolitical] risks.” Teams of AI agents make this scalable, turning complex data into actionable insights. For executives at RIAs, asset managers, broker-dealers, custodians, and fund administrators, the imperative is clear: adopt collaborative AI systems to unlock smarter investing. Platforms like Romina Day are pioneering this shift, leveraging teams of AI agents to deliver real-time monitoring and due diligence capabilities that redefine alternative asset management. As the industry evolves, those embracing these tools will lead the future of investing.
In today’s fast-changing trade policy environment, investment teams need to be able to break down information quickly. A single policy announcement can ripple through markets, significantly affecting alternative assets in mere hours. The ability to understand the environment and adapt swiftly is what separates top performers from the rest, and these actions help maintain relationships with clients and LP’s.
To navigate this, firms must rely on systems designed to shrink the time between spotting risks and implementing strategies to address them. This urgency highlights the growing role of technology in maintaining a competitive edge.
To keep pace with these demands, many firms are embracing AI-powered tools. Modern due diligence now relies on advanced technology capable of processing massive amounts of data in record time. For example, what once took six hours of earnings call analysis per week can now be completed in under a minute - saving 108 hours every quarter.
Here are some of the key features driving this efficiency:
In 2025, regulatory scrutiny of alternative investments is intensifying, with bodies like the SEC and GDPR emphasizing transparency and explainability, as noted in recent SEC guidelines. AI agent teams streamline compliance by continuously monitoring regulatory updates and integrating them into risk and due diligence processes. Specialized agents analyze fund manager data and portfolio exposures to ensure adherence to standards, while others generate auditable decision trails for compliance reporting. For example, during April 2025’s market volatility, firms using AI agent teams quickly aligned with new SEC disclosure rules, reducing compliance risks. Platforms like Romina Day leverage these systems to deliver real-time, transparent reporting, enabling COOs and compliance officers to navigate regulatory complexity with confidence and efficiency
AI agents are reshaping how due diligence is conducted for alternative asset investments, especially in the face of shifting trade policies. With automated monitoring, AI can keep a constant eye on regulatory updates, policy shifts, and regional developments that might influence portfolios. This means investors are always up-to-date, without needing to manually sift through endless updates.
Another game-changer is AI's ability to deliver risk summarization. By quickly analyzing the potential impact of new trade policies on key operating assumptions, AI eliminates the need for time-intensive manual evaluations. This allows investment teams to make faster, data-backed decisions. The result? Teams can respond swiftly to changing market conditions, maintaining both flexibility and confidence in their strategies.
In 2025, transparency in alternative investments is critical amid rising regulatory scrutiny and market volatility, as highlighted by the IMF’s April 2025 Global Financial Stability Report, which emphasized managing geopolitical risks. Teams of AI agents enhance transparency by continuously analyzing fund manager data, market trends, and regulatory changes in real time.
These systems integrate diverse datasets—such as tariff impacts or private market exposures—and generate auditable decision trails, ensuring compliance with SEC and GDPR standards. For CIOs and Research teams, this means clearer insights into risks and performance without added headcount. Platforms like Romina Day leverage AI teams to deliver transparent, actionable reporting, empowering firms to navigate uncertainty confidently..
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