Startups 3 Methods for Investors Assessing AI Readiness of Portfolio Companies • businessroundups.org Ana LopezDecember 7, 20220208 views Richard Potter Contributor Richard Potter is co-founder and CEO of Peakwhich provides the platform, applications and services that enable companies to harness the potential of AI to increase revenue, increase profits and increase efficiency. We are in the grasp of a fourth industrial revolution: the intelligence age. The next decade will be marked by advances in artificial intelligence (AI) and machine learning (ML) that will fundamentally change the way businesses operate. With real-time data at hand and more automated decision-making, the processes and rhythms we now take for granted will become obsolete. From quarterly board meetings to approval processes, AI will revolutionize the way we conceptualize, execute and report on business activities. This technology will change the way the world works. The vast majority of leaders tell us that AI/ML will play a major or moderate role in achieving their business goals over the next five years. For investors, assessing a portfolio company’s AI readiness is now just as important as scrutinizing the books. The ability to deploy this technology and derive meaningful value from it indicates longevity, profitability and a competitive advantage. Peak’s Decision Intelligence Maturity Index evaluated 3,000 decision makers and 3,000 junior employees from companies in the US, UK and India to assess their readiness for AI across a number of key maturity indicators. The research revealed similarities between the companies best placed to succeed with AI adoption. Companies with the highest AI maturity are also invariably those communicating their aspirations to team members at every level – not just leadership. Here’s what investors should watch out for in the intelligence age: How are data teams structured? AI is a transformative technology, so it cannot be implemented by technical teams alone. To succeed, companies need commercial insight into what an AI application needs to deliver for each function, as well as end-user agreement. As such, how companies structure data teams has a major impact on their AI readiness. Our research found that those with the highest AI maturity tend to work with a decentralized data team. In the US (30%) and UK (25%), it is common to rely on one central data or business intelligence team. This means that advanced data functionality and knowledge are housed within a single department and support for functional teams should be directed through that central team. By contrast, in India, where organizations routinely showed the highest AI maturity, the majority (33%) of companies have a dedicated data professional embedded in every department.