Real-world challenges of using AI in the enterprise

Abstract: Recent advances in the field of AI has been exciting and the resultant hype has been great. However, most enterprises have yet to substantively harness their data to positively affect their bottom lines. In this talk, we discuss some of the underlying technological and cultural reasons as well as approaches for success.  From a technological perspective, there are a multitude of legacy systems with different formats and data models that must be merged. We discuss some approaches for managing this landscape using ad-hoc query methods. In addition, while technological and analytical challenges abound, having a high degree of cultural sensitivity, empathy for the end-user, and design-orientation are key to success. We discuss a few high profile examples of technologically advanced AI products that 
have failed to gain traction.
 
Bio: Afsheen Afshar is the Chief Artificial Intelligence Officer for Cerberus. He is a seasoned business leader and deeply technical professional with hands-on knowledge across the entire data and analytics value chain in multiple industries. His experience spans business management, rapid organizational growth, design and creation of industrial-scale data and analytics infrastructure, bleeding-edge artificial intelligence algorithm design, product design and creation, and large-scale value generation.
 
Professional History:
• Chief Artificial Intelligence Officer and Senior Managing Director, Cerberus
• Chief Data Science Officer and Managing Director, JPMorgan, Corporate and Investment Bank
• Managing Director, Goldman Sachs
 
Accomplishments:
• Creating and leading first artificial intelligence function from scratch for one of the world’s leading investment firms
• Advising, assisting, and serving as a senior resource to Cerberus’s affiliates, portfolio companies, and investments worldwide
• Created, grew, and led multiple industrial-strength data science and engineering functions at two of the world’s largest and most prestigious investment banks. One of the first to do so.
• Created one of the first scalable and flexible data and analytics platforms that could be used by technical as well as non-technical professionals alike
 


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