By Raj Bakhru, CEO and Co-founder of BlueFlame AI
Alternative investment managers recognize the potential of AI and have spent the past year experimenting with the multiple tools available. But while many have seen the power of ChatGPT and personal tools, most have struggled with how to make this usable in their work lives. In many cases there have not been clearly enough defined objectives, pre-identified use cases or coherent strategies in the initial implementation phase. Coupled with many fear-based assumptions, this has led to an underutilization of AI in the industry and a failure to tap into its true potential.
As we move into 2024, the future of AI for alternative investment managers is bright. We’ll see a sharp uptick in AI deployments and a shift towards ‘productionizing’ AI, with a strategic focus on where AI can deliver the most benefit. That includes areas such as how to enhance portfolio research, refine risk management strategies and automate routine but crucial tasks such as DDQ and RFP responses. Private equity firms will harness the content search capabilities for better diligence and research. Private credit will use it for aggregation of covenants from credit agreements. Hedge funds will leverage it to aggregate sell-side reports – and plenty more examples. The focus for alts will be on understanding how they can obtain the highest ROI on integrating AI into their day-to-day activities and existing workflows to complement and elevate human decision-making – not replace it – thereby supercharging their ability to make more informed, data-driven decisions.
Supercharge your analysts
Alts will look to plug into platforms that meet them where they work in 2024 and offer pre-built connections to the data stores and applications they already use daily. That includes CRMs, research systems, market data providers, collaboration tools, messaging applications and local drives and data rooms. And during a chaotic time for some AI providers, it will also be critical that alts leverage solutions that are Large Language Model (LLM) and provider agnostic and can build on top of existing OpenAI, Copilot and/or other Big Tech solutions.
It’s vital that AI solutions for our industry go beyond mere automation to actually simplify everyday activities. If your AI platform can natively connect with the systems you’re already working in, there’s no fundamental change to how your team performs its work – only upside.
Drive maximum ROI
Any AI solution must strike an optimal balance between cost, benefit, complexity, ease of use and functionality. If a firm has an overload of AI software that is incorrectly deployed and/or teams that are not properly trained, the challenges could quickly negate the benefits and heighten the risk of data loss or security breaches. To drive maximum ROI, firms must also embrace effective change management and staff training to drive smooth integration and maximum value, and ensure any deployment is done in a secure and compliant way. As regulators will likely soon weigh in on this space, firms must ensure they have the right strategy and solutions in place to leverage AI’s strengths while meeting client and regulatory expectations on security, privacy, and compliance.
It’s just as important that alts have reliable, high-quality data to drive critical investment decision-making, fundraising and investor relations activities, especially when the data they use is augmented by
AI. While many smaller or mid-size firms may not have the resources for full-time data scientists and developers, it’s imperative that they be able to enhance their data sources and undertake rigorous data cleansing to ensure the dependability of AI-supported decisions.
Choose your starting point
In 2024, firms must deploy AI solutions that are tailored for the alternatives space. From deal diligence to investment research, portfolio value creation to fundraising, it’s critical to ensure your AI provider knows how to make this technology work for this industry.
Firms should start by selecting and an AI solution that can help their team:
· Connect with systems like Pitchbook to provide details including team summaries, deal histories, files, news headlines, and more.
· Accelerate the review of PDFs and unstructured content, such as earnings transcripts, expert network calls, sell-side research, 10-Ks/10-Qs, market research reports, board decks and news.
· Aggregate views across dozens of documents at a time, extract key data points and put them into tables or create time-series of views.
· Prepare for LP meetings by looking up contact biographies from selected market data sources and by looking across internal emails, calendar invites, files and CRM activity.
· Draft initial responses to DDQs/RFPs or create draft emails with proposals.
· Connect to your research management system (RMS) to review historical notes, summarize views, and post notes and commentary.
· Quickly pull deal data, past deal history and save updates and tasks after meetings with targets within your Deal Management Systems (DMS)
· Interact with your CRM using natural language prompts to pull select data, mass email prospects, add interaction details and update statuses
· And more.
Powering the future
The potential of AI for our space is immense but that doesn’t mean properly deploying AI within your firm has to be overwhelming or introduce any type of FUD about the outcome. When fund managers have the right AI solution that simplifies everyday activities and properly integrates into existing workflows, they will derive significant time savings and efficiency gains from it. There are many more use cases to be defined and strategies to be implemented across the sector – and we will continue to see new, innovative ways AI can support alts managers. Those that ensure they have the right solution in place to enhance crucial tasks and meet future regulatory requirements will set themselves clearly on the path to AI success in 2024.
