Managing risks from poor-quality AI is too important to leave purely to technical specialists. An organization-wide perspective is needed. As the adoption of artificial intelligence (AI) continues at pace across industries, there is increasing awareness of the risks it can pose. Recent high-profile examples have highlighted the risk of unjust bias regarding race and gender, such as those found in some law enforcement or recruitment algorithms. Other examples have highlighted the reputational risk from poorly communicated AI use cases, such as an online insurer's recent claims of using facial emotion recognition to detect fraud.

Bharani Kumar is an Alumnus of premier institutions like IIT & ISB with 15 years professional experience and worked in various MNCs such as HSBC, ITC, Infosys, Deloitte in various capacities such as Data Scientist, Project Manager, Service Delivery Manager, Process Consultant, Delivery Head etc. He has trained over 1500 professionals across the globe on Business Analytics, Agile, PMP, Lean Six Sigma, Business analytics and the likes. He has 8 years of extensive experience in corporate, open house and online training. He is a thorough implementer with abilities in Business Analytics and Agile projects. He worked in Delivery management focusing on maximizing business value articulation.

Even though my work often mystified you, you and Dad have been my biggest fans throughout my over 25-year data management career. Not surprising, as you were both dental professionals, not data professionals! But as you started hearing about data in the media more and more, your interest piqued to better understand it. I've thoroughly enjoyed writing my letters to you over the past few years covering a range of topics including Data management, Metadata, and Data Governance, as well as several industry trends like Big Data, the Internet of Things, Cloud computing and my last letter discussing Digital Transformation. I know you've heard the term AI before.