The Power of Artificial Intelligence and Machine Learning

in Business Valuations

The advent of ChatGPT and its other AI apps has come to the forefront. This is potentially disruptive technology that will raise uncomfortable issues, but also open the door to innovation and new industries. AI will impact how business valuations are performed and the role of accredited professionals. This article discusses how AI and machine learning could impact the business valuation profession.

Is knowledge power? Artificial intelligence (AI) refers to using computers, IT systems, and technologies and their abilities to perform tasks that naturally require human intelligence, i.e., simulated cognitive, critical thinking, and reasoning capabilities. How does the machine have the capacity and capability to reason? The answer is relatively intuitive. The answer lies in the massive amounts of data (good data). In finance, cash might have been thought of as king; however, in the rapidly evolving world of AI and machine learning (ML), it is data. AI systems can find potential solutions to complex problems and assist in the decision-making process by analyzing enormous amounts of information, recognizing patterns, making predictions, and adjusting those predictions based on the changing circumstances using progressive learning algorithms, ML systems, deep learning, neural networks, cognitive computing, natural language processing, and various other statistical models.

The origin and roots of AI date back to 1950 when a British mathematician, Alan Turing, published a paper titled “Computing Machinery and Intelligence.” In this work, Turing explored whether machines are capable of reasoning and exhibiting similar cognitive abilities compared to humans. Turing is often considered the father of modern computer science and AI. In 1956, the term “artificial intelligence” was coined at the Dartmouth Conference. Since then, the field of AI has experienced tumultuous ups and downs.

The early 1980s experienced notable movement and fascination with AI from the science community; however, this interest faded away in late 1987 through the early 1990s. Consumer-facing AI innovations entered the market in the 2000s, including the early Roomba robot (2002). Around 2006, user experience (UX) algorithms gained momentum in such companies as Twitter, Netflix, and Facebook. Since 2010, mass commercialization permeated everyone’s daily lives with the invention of virtual assistants (such as Siri, Alexa, etc.), fraud detection systems, healthcare diagnostics, chatbots, quant funds, etc.

The power of AI in the context of business valuations can be significant, and it can provide valuable insights and efficiencies. First, AI can facilitate data processing and analysis processes, including historical financial statements analysis, trend forecasting, and market and industry research. This capability can be useful in assisting valuation professionals in assessing the subject company’s current position and future growth prospects. Second, computer systems, algorithms, and data-driven modeling can enhance the valuation analysis by identifying risk factors and incorporating them into the intricately calibrated valuation modeling.

However, although AI-powered solutions may enable valuation professionals to make better decisions and improve risk management and assessment techniques, AI should not replace the expertise and sound judgment of valuation professionals. Human interpretation, experience, and qualitative assessments are still crucial in understanding the nuances and context of a business’s value. Valuation professionals will need to adapt to and leverage AI technologies as valuable tools to enhance their expertise and provide more accurate and insightful valuations.

Valuing AI-Powered Businesses

The application of AI-powered innovations has been utilized in almost every industry. For example, AI has been used in manufacturing and logistics industries to optimize supply chain management, determine predictive maintenance requirements, standardize quality control measures, and forecast demand. For these types of firms, AI-powered automation potentially increases operational efficiency and reduces costs. In retail and e-commerce, AI can enable personalized product recommendations, customer sentiment analysis, inventory management, and chatbot assistance. AI-driven insights and automation are used to enhance customer experiences and drive sales growth.

As AI ecosystems continue to permeate across a wide range of industries, from healthcare and construction to customer-centric service and dining establishments, it is essential to consider factors that can either contribute to or detract from the company’s core value attributes.

Intellectual Property (IP) Considerations

Given how abundant resources are available at the disposal of many firms, ML, along with proprietary algorithms, is geared to solve specific and oftentimes complex programs that can significantly contribute to the company’s value. Evaluating how unique the company’s IP is and how well it is protected, whether by patents, copyrights, or trade secrets, may serve as a value driver and a barrier to entry to potential competitors. For example, if the company’s AI ecosystem is based on proprietary or exclusive datasets, it will have a greater competitive advantage than its peer group. In the financial services sector, AI can play a vital role in developing and deploying automated trading algorithms or applications to detect fraud or perform risk assessments.

IT Systems and Technology Considerations

Any AI-powered business must have adequate technology infrastructure to support and potentially scale its environment. A valuation professional should assess the company’s ability and capability to maintain its AI-based systems and applications; especially when it comes to storing, analyzing, and protecting (securing) large amounts of data. Additional considerations include computation power capacity and the company’s cloud infrastructure to handle complex and intricate algorithms and processes.

Market and Growth Potential Considerations

Although nearly every industry can benefit from AI-based applications by solving specific problems within each niche, the extent to which AI can be successful in any given industry depends on the type of technology or solution being offered and the scalability of the AI technology itself. Markets and industry sectors that are high-growth and in high demand would benefit significantly from AI-based solutions. For example, AI has great potential to revolutionize the healthcare and life sciences sectors by enabling precision and personalized medicine, drug discovery, and medical diagnosis. AI-powered solutions have the potential to improve patient outcomes, enhance patient monitoring, reduce costs, and drive advancements in healthcare delivery, treatment efficacy, and operational efficiency.

Valuation Notes

When it comes to quantifying an indication of value, the nature of the business will dictate the most appropriate valuation method to use. Valuing AI-powered companies can present unique challenges due to the rapidly evolving nature of AI technologies and the uncertain market condition and adaptation. From a valuation methodology perspective, a discounted cash flow business (DCF) can be used to value an AI-powered business. However, the assumptions and projections made during the valuation process need to be carefully considered and supported by relevant data and market research. When valuing an AI-powered business using the DCF method, a practitioner typically would follow these steps:

1. Forecast Cash Flows: company management (and/or in collaboration with a valuation professional) will estimate the future cash flows that the AI-powered business is expected to generate over a specific period, usually five to ten years. These cash flows should account for the revenues, expenses, working capital, and investments related to AI technology and its impact on overall business performance.
2. Determine the Discount Rate: when estimating the required rate of return, a weighted average cost of capital (WACC) can be used. The WACC is a financial metric used to calculate a company’s average cost of capital. It represents the blended cost of both debt and equity financing based on their respective weights in the company’s capital structure. For an AI-powered business, the risk considerations may include factors related to technology, competition, regulatory landscape, and market acceptance of AI solutions.
3. Calculate the Terminal Value: At the end of the forecast period, estimate the business’s value beyond that period. This is often done using a terminal value calculation, such as the perpetuity growth method or exit multiple, which assumes the business will continue generating cash flows into perpetuity or be sold at a certain earnings multiple.
4. Discount and Sum Cash Flows: Apply the discount rate to each projected cash flow and the terminal value to find their present values. Sum up all the present values of the cash flows to obtain the business’s enterprise value.

Although valuing an AI-powered business may seem like unchartered territory, it is simply not the case. AI-powered enterprises have been around for a long time. If your name or your company’s name has been entered into a customer relationship management (CRM) system, or you visited a doctor who uses electronic medical records (EMR), your information and data have been accumulating in some database that drives and powers an AI ecosystem.

Nowhere has the use of AI been more prominent than in the investment and hedge fund industries. Companies such as Black Rock, Vanguard, Bridgewater Associates, and many others use AI and ML to analyze vast amounts of data, generate investment insights, formulate investment strategies, and manage risk. Companies such as Wealthfront and Betterment are well-known robo-advisers that use AI algorithms to offer automated and personalized investment advice to retail investors. While not exclusively an AI-powered company, Robinhood’s platform incorporates AI to optimize trade execution and provide personalized recommendations to its users.

Given the widespread prominence of AI-based tools and technologies in a wide range of industries, the valuation professional can look for industry guidance and comparable companies to benchmark and gain insights that can be applied to their valuation assignment. Industry and sector analysis can assist the valuation professional in determining the appropriate value drivers for the companies operating in the same or similar industry, help to support growth rate assumptions, and assess the reasonableness of the discount rate.

As the landscape of AI-powered companies continues to evolve, new companies and market leaders will emerge. The rise of AI-powered businesses brings unique characteristics that make them fascinating from both a business and valuation perspective. AI-powered businesses are at the forefront of technological innovation. They leverage advanced algorithms, ML, and data analytics to create cutting-edge solutions that can revolutionize industries and business processes. From a business valuation perspective, rather than being taken aback by the uncertainty of the AI landscape, valuation professionals should embrace it and approach it with a structured, rigorous analysis applied to any business valuation or litigation engagement.

“In the world of AI-powered businesses, uncertainty is the canvas upon which innovation paints its masterpiece. Embrace the ever-evolving landscape, adapt your brush of valuation methodologies, and collaborate with the colors of technology to unveil the true beauty of tomorrow’s transformative ventures.”

I would like to thank Murali Minnah of Nambri Technologies LLC (www.nambri.com) for sharing his knowledge and insights that contributed to this article.

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Nataliya Kalava, CVA, ABV, MAFF, is an expert in the fields of business valuation and finance, with about 15 years of experience. As the founder and managing director of American Valuations, she has led and contributed to numerous valuations for diverse purposes, including gift and estate tax planning, management planning, M&A transactions, SBA valuations, financial reporting, and litigation support.

Ms. Kalava’s passion lies in helping business owners navigate ownership transitions, guiding them through challenges, and uncovering opportunities for growth. Her expertise is honed through a rich career journey, having worked with renowned organizations such as Equinix Inc., Humana Inc., BDO LLP, Sigma Valuation Consulting Inc., and PwC.

Beyond her leadership at American Valuations, she actively contributes to various ventures. She serves as the Chief Financial Officer at Tampa PainMD. Additionally, she is the co-founder and managing member of NAMBRI Technologies LLC.

Ms. Kalava’s dedication to her profession extends to education and community engagement. She has been an Adjunct Finance faculty member at the University of Tampa, imparting her knowledge to undergraduate students on corporate finance and investment. Furthermore, she organizes Continuing Legal Education (CLE) courses on business valuation topics accredited by the Florida Bar.

Ms. Kalava can be contacted at (813) 999-1144 or by e-mail to nataliya@amervalue.com

Murali Minnah is a managing member and co-founder of Nambri Technologies LLC. He leads the product development department at Nambri and brings deep expertise in enterprise software and commercialization. With academic backgrounds in Finance and Technology, he is interested in rapidly accelerating operational effectiveness and productivity by applying scalable, secure, and high-precision software solutions leveraging AI and ML.