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Wealth Beat News > Small Business > Use Cases And Best Practices For Using AI Tools As An Investor
Small Business

Use Cases And Best Practices For Using AI Tools As An Investor

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Last updated: 2023/08/08 at 4:48 PM
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Leen Kawas | Entrepreneur, Inventor, Innovator and Leader | Managing General Partner at Propel Bio Partners.

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Use Cases For AI In The Investment IndustryBest Practices For Leveraging AI As An Investor

While companies of all sizes across various industries adapt their processes to make room for innovative artificial intelligence (AI), the financial and investment industry is catching up and leveraging AI tools to enhance their operations and improve their performance. I’m seeing that the financial industry and investment firms can and are implementing various AI tools to help boost their productivity, error margins and overall efficiency.

Being the managing general partner of a global equity investment firm focused on life science companies, I have always been interested in the application of AI in the life science industry. I believe there is a significant opportunity to streamline and optimize drug discovery, development, data analysis, product launch, post-market analysis and patient experience. There are significant additional areas that AI and machine learning could be applied to as well, such as electronic patient records, intellectual property strategies and searches and more.

This is an industry that is data-rich, and as an investor with significant insights into science and operations, I can see value in using AI tools to streamline aspects of the research done at an investment firm. It could help with tracking news; researching the competition; comparing clinical trial results; and supporting predictive models to identify the probability of success for a specific catalyst, development milestone or product performance. AI can also help support portfolio construction, performance and real-time decision-making and adjustment, thus enabling portfolio managers to react quickly to internal and external information.

Use Cases For AI In The Investment Industry

1. Elevating investment searches: Each investment brings a potential risk that must be vetted thoroughly. Investors might use AI to assist in the vetting process by providing background information. Access to the background of the business and its competitors in an efficient way can enable informed decisions with a faster turnaround period. AI tools can help streamline the analysis of a potential investment’s returns, sales and profitability as well.

2. Industry analysis and trend forecasting: Investors closely monitor trends across various industries, as macro and micro changes can impact the different companies in their portfolios. Traditionally, this means that teams or individuals must manually keep their proverbial “eye on the pulse” across many industries, a nearly impossible task in arenas that experience frequent change and innovation. Using AI to gather relevant data points, highlight new studies and analyze trends across various industries can provide a unique advantage to an investment firm.

3. Enhancing due diligence efficiency: Most firms have to comb through a large number of potential investment opportunities, but if a firm has a clear investment mandate or thesis, it can use AI tools to sieve through a large number of opportunities and identify the best fit. Various AI-enabled software technologies can scan legal documents, financial statements and pitch decks. AI can also help complete the vetting process and identify companies that fit the fund’s strategy. In addition, I’ve seen some software that can pinpoint opportunities that might not have significant materials; it does so by using pattern recognition to match the firm’s interests and historical investment trends to that of the startups in question.

4. Improving fundraising opportunities: Fund managers often dedicate significant time to identify potential investors. AI can assist in creating individual investor profiles and identifying fundraising opportunities. By providing the AI algorithm with pertinent information about an upcoming funding round, fund managers can receive a targeted list of potential investors. This streamlining provides the fund manager with more time to create genuine connections and foster long-term relationships with investors.

Best Practices For Leveraging AI As An Investor

While AI-integrated tools continue to grow, I’ve found there are two notable applications that seem to be gaining traction in the world of venture capital. First, machine learning algorithms are used by firms due to their ability to learn and analyze a large data set efficiently. By repeatedly using the algorithm and honing in on specifics, users actually make the machine learning model “smarter,” thus rendering more accurate predictions and analyses over time. Secondly, a natural language algorithm is used to analyze a candidate’s corporate language and forward-facing presentations. Based on key learnings, the algorithm then presents full details of the company’s landscape and relevant information.

While it has been around for a while, the accessibility to AI tools and the potential of integrating them widely is new. Unless you are an investor with a background in AI, you will likely not have clarity on where to start or how to use AI tools. If you have never used AI, one thing to consider is looking at tasks that are lower risk but still take a significant portion of your time. Identify software and tools that can help you streamline these tasks. Make sure to track the performance of these tools to give you confidence that you can rely on them long term.

I also recommend exploring workshops that give a good basic understanding of AI and how to use it effectively. Then, if you are looking to integrate it further into your operations, you can consider hiring an AI and data scientist to support building purpose-built models specifically to fulfill unique aspects of your investment thesis. Start with generic tools, and then advance to tailored ones. This might help improve your firm’s performance and ultimately differentiate your products as you scale your business. Multidisciplinary talent is hard to find, and working with AI and data scientists might be challenging, but realizing ways to communicate the unique aspect of your industry and learning the basic concepts of AI will help build a strong collaborative team with successful unique products.

AI might not be the industry or area you are investing in, but incorporating tools in your day-to-day could help you stay relevant in this new era of investing. Especially considering that a lot of companies are incorporating AI into their services, having a basic understanding could not only help you grow your firm but also support your ability to evaluate new investment opportunities.

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News August 8, 2023 August 8, 2023
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