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AI, verification and impacts on commercial due diligence 


May 12, 2023
AI, verification and impacts on commercial due diligence 

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Ever since the launch of ChatGPT in late 2022, AI has grabbed the attention of people and businesses around the world. This technology was previously understood as highly promising but a topic for the future. Today, it has loudly announced itself, catching businesses off-guard as they mobilize to make sense of its exciting potential to automate processes and supercharge efficiencies. 

One important aspect to examine is where investors are currently focusing their attention. This latest wave of AI has focused early attention on those startups and businesses already using AI in their products and services (loosely termed AI adopters). Other factors to consider are whether investors are pausing their investments and causing illiquidity in the market. In this, investors consider likely consequences and disruptions across industries and update their commercial and technical due diligence approaches as they look to side-step hazards and seize opportunities.

New approach to content platforms

For example, since the arrival of large language models (LLMs) such as GPT and its chatbot variant ChatGPT and text-to-image models such as Midjourney, investors have reconsidered their approach to business models involving content platforms. Given the ability of LLMs to function at incredible speed, digesting vast amounts of information (either ‘contained’ from internal data stores or straight from the internet) to produce detailed summaries and insights, as well as process visual inputs, it comes as no surprise that investors would anticipate significant disruption for stock image marketplaces or more complex content types such as website builders. 

Inevitably, this disruption to established business models translates into opportunity for some, as innovative models develop to replace them and challenger enterprises overcome or are integrated into incumbents. In the short term, there may be a few ‘winners’ in the AI-adopter space. However, it’s sensible to expect that these product offerings will likely be overtaken by the Googles and Microsofts of this world, with outliers being bought and integrated into larger businesses in the medium term. Ultimately, this will be a fascinating time to watch these innovators racing to establish market dominance, delivering these cutting-edge solutions. 


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Due diligence critical

Looking beyond AI companies to businesses more generally, the starting point for any AI approach should be the same. The AI genie is not going back in the bottle, and there will almost certainly be potential for it to fast-track slower, inefficient or manual processes wherever possible to optimize costs and free up employees to do more interesting and engaging work. This is where it becomes important for investors to ensure their due diligence efforts can protect against any damaging impacts as they assess AI’s ability to disrupt, deliver improvements and transform business value. 

For digital experts, accurate and reliable information is essential for making informed business decisions. There is a wealth of potential data sources for AI to choose from, such as specific financial data in the case of BloombergGPT, or the internet itself.

However, when it comes to AI-generated content, platforms often lack an immediate ‘in-built’ method to verify the information being presented, as the algorithm doesn’t always provide sources at the time of generation. A more damaging habit of AI is its ability to deliver plausible citations that are completely fabricated or ‘hallucinated’. This presents a major challenge as businesses need total trust in the data they are working with. 

Verifiable sources and context critical

Without verifiable sources, businesses and individuals who rely on AI-produced content for decision-making purposes may inadvertently make choices based on inaccurate or unreliable information. This can have serious consequences, ranging from missed opportunities to financial losses and reputational or legal damages.

It’s equally important to consider the context where the AI is being applied. For example, more regulated industries such as healthcare, limit the degree of automation possible without human oversight. Likewise, individuals may reject AI handling sensitive information in one area of their life while having no qualms about trusting AI in another — such as planning a holiday or buying a new outfit.

To avoid these risks, it is essential for businesses to carefully evaluate the sources of any AI-generated content they use in their work. Leaders must partner with AI developers who use LLMs that have shown the highest degree of transparency in their citation selection and reasoning processes. They should also invest internally to insert human review stages to verify the accuracy of any AI-generated content before presenting it to clients. With this in place, firms can help take confidence that the information they provide is accurate, reliable and trustworthy. 

Lack of clear ownership a concern

The lack of clear ownership rights over AI-generated content is another area for attention. It can be unclear who owns the intellectual property rights to AI-generated content, leading to disputes over control. It will be vital to pay close attention to eventual legal rulings, especially for multinational companies, which may have to account for varying rulings for different regions. 

Another potential misstep for businesses using AI is the importance of ensuring that any sensitive or confidential company information remains internal and is not simply fed back into the AI model provider. Here it can be vital to introduce internal policies around the correct use of AI, such as anonymizing all data before processing or even using locally deployed models.

While every industry is considering the shape of its future once AI is properly integrated, some will inevitably be shaped more than others — for example, those deploying narrow and deep expertise, such as legal agencies and law firms. As they anticipate likely impacts from AI’s democratization of knowledge, they may be spurred sooner rather than later to invest and build out their capabilities and knowledge building. 

Toni Stork is CEO and partner at OMMAX.


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