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July 17, 2024
PI Global Investments
Alternative Investments

Mapping the AI Path for Alternative Investment Managers

Alternative investment managers recognize the potential of AI and have spent 2023 experimenting with the multiple tools available. Unfortunately, while everyone has 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, what is the future of AI for alternative investment managers? Next year 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.  

Meeting fund managers where they work 

To ensure success on their AI journey in 2024, alts will look to plug into platforms that meet them where they work and offer pre-built connections to the data stores and applications they already use daily. That includes CRMs, research systems like DealCloud
and Dynamo, market data providers like Pitchbook, collaboration tools, messaging applications and local drives and data rooms. And during a chaotic time for AI providers like OpenAI, it will also be critical that they 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.  

Putting the AI in AIM 

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 really put the AI in AIM, 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

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. 

Identifying the right initial use cases 

In 2024, it will be imperative that firms 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.

At a minimum, look for AI solutions that can help your 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. 

The future of alts simplified 

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 fear, uncertainty or doubt 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 still 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.

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