As I mentioned recently, early October in Santa Clara, CA at the AI & Big Data Expo World Series, I had the opportunity to capture interesting insights from SMEs and business leaders around #ai adoption and AI challenges. Find here some takeaways I want to share about "Building Enterprise AI Excellence" (more capsules to come about other topics and presenters during the #aiandbigdataexpo). My take on this intervention by Daniel Wu (head of AI & ML Commercial Banking at #jpmorganchase) is how relevant it is for business leaders to gain a perspective on AI/ML adoption with a holistic lens. Everyone working in high-tech (and also other verticals!) has been exposed somehow to the positive benefits that emergent tech like AI can bring thanks to extracting value from the increasing #computing power we now have, solutions automation, making #unstructureddata useful, faster #decisionmaking, and so on (too many benefits to mention here!). However, adopting new tech as AI has many aspects (beyond the business problem it solves). To be really prepared to move forward with #aiadoption, any organization needs to consider AI as a total new aspect of the business, encompassing the elements described in the framework presented here. According to Daniel Wu, every year enterprises are investing more money in adopting AI (as expected). However, a proper framework and solutions to face challenges brought by such adoption, are needed to prepare organizations in this transformation. The Framework to drive this process, should consider five different angles: Data - considering its quality, cleansing process, accessibility and #datasilos within organizations. Compute - Managing security, #privacycompliance, cloud migration, and carbon footprint, among other challenges. Talent - Navigating through talent shortage, lack of #diversity and corporate AI literacy. Operation - supporting scalable models with dedicated teams to manage AI-related processes. Governance (this one being my favorite!) - where lack of ethical knowledge and #regulations, as well as absence of AI boards withing orgs, are creating exponential risks for consumers and companies adopting AI-based solutions.