AI and machine learning due diligence (+ checklist download)

You may be considering making an investment in a startup (your “target”) that claims to use machine learning/AI and would like an impartial assessment of their technology along a practical checklist, or involved in planning a corporate merger. We can perform an evaluation of a company’s technology stack. This should be done in tandem with a traditional due diligence exercise. You can download our AI due diligence checklist.

We have performed a number of AI technical due diligence exercises in different industries. You can read our AI due diligence case studies.

Some of the points we will look at in our technology/machine learning due diligence checklist include:

• is the product a real product and capable of being sold as is, or just a demo?
• how viable and scalable is the technology long term?
• where will the data for the AI come from? If from users, then does the product suffer from the cold start problem?
• can the product scale in the real world?
• how reproducible is the product?
• how sustainable are the development workflows?
• are code and models documented and under version control?
• are the target’s founders’ credentials and experience valid and as claimed?
• is there any crucial employee, or exceptionally talented employee on whom the target business depends?
• is the team well-balanced with complementary experience, or have the founders recruited individuals with the same profile?
• how is the product’s performance measured (see posts on evaluating generative models or healthcare applications)?
• is sensitive data sent to third party generative AI providers such as GPT? Is the start-up a thin wrapper around a well-known GenAI offering?

• how robust is the target organisation’s structure? Does the company have a low bus factor?
• How is the organisation’s approach to data science project management?
• how is the technology licensed?
• how will costs scale as the operation scales?
• if we are talking about a healthcare or medical device, is the product likely to need licensing?
• how reproducible is the technology, irrespective of patents and legal protection?
• what are the future risks from a technology perspective?
• is there any risk of reputational damage from the technology?

Once you’ve downloaded the AI/technology due diligence checklist you can read more about how technical due diligence can help you, and how Fast Data Science conducts technical due diligence on AI companies.