Statistics, data mining, data science, machine learning, and AI – no matter what you call what you do, all ultimately have the same goal of turning data into insights and improved decision-making.  Proponents suggest that removing the human element from the equation can result in more efficient and transparent outcomes, but what happens when the models or training data are incomplete, poorly documented, flawed, or even unlawful?

Companies whose valuation relies heavily on intellectual property should ensure that their software, algorithms, and data are compliant and well-documented. Non-compliance and IP uncertainty pave a path to lost deal value, lawsuits, regulatory fines, or even collapse of the company.