Accelerate your AI/ML initiatives and deliver business value quickly by implementing practical and innovative approaches


Critical success factor for enterprise level AI adoption and sponsorship is the ability to rapidly deploy AI technologies, solve use cases quickly, and deliver iterative business value to stakeholders. In this session, we will discuss the challenges of AI adoption, share some pragmatic approaches that enterprises can adopt to accelerate their AI / ML initiatives and deliver quick and iterative business value. Examples of some approaches would include leveraging pre-integrated AI frameworks and automation techniques such as AutoML, along with ready-to-use industry-specific AI solutions. The faster and more incremental the delivery of business value through AI, the higher the likelihood of successful adoption and implementation of AI within enterprises.


Shan is a data analytics, AI, and management consulting practitioner with over 20 years of experience in solving complex business problems for clients through innovative technology solutions. Shan joined Fujitsu in 2017 to grow and lead the data analytics business at Fujitsu North America. In his current role as the Head of AI offerings, Shan is responsible for shaping the AI go-to-market strategy, and product offerings, and for promoting AI adoption amongst Fujitsu’s clients. Shan has published thought leadership articles/whitepapers for the Fujitsu Global blog on technology and industry topics such as AI Enabled Trusted Society, AI and Advanced Analytics, Mobility Industry, and Smart Cities. Shan lives in Dallas, Texas, and is an avid NBA fan and motorcyclist.

Open Data Science




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