Smart Implementation of AI & Data Analytics in your Business

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Smart Implementation of AI & Data Analytics in your Business

Professor Ikhlaq Siddhu, Chief Scientist and Founding Director of Sutardja Center for Entrepreneurship & Technology of UC Berkley Department of Industrial Engineering & Operations Research, delivered a talk on AI and Data Analytics last May 27, 2021. Despite his busy schedule and the time difference between Manila and California, he agreed to talk. He is always excited to discuss how AI and Data Analytics spurs innovation and positively changes the world. To listen to the new trends and application of AI and Data Analytics in business is inspiring for someone like me who has no technology background. Hence, it is good to know how “data becomes the new oil” as it creates new revenue streams and business models for some if not most companies.

Professor Ikhlaq asked the question: Who will control the future of the automobile? Is it Ford or Google? Of course, the company which has better software and a data science team will control the future. As we know, the core of every business these days, and in the future, is Data and AI. The growing use of Artificial Intelligence and Data Analytics in the business landscape will lead to better predictions, brand awareness and a bigger wallet share. Hence, these companies will become winners at the market place, provided that they can innovate and come up with better use of the data at hand and use AI to monetize said data.

Many of the changes and business transformations today are spurred by AI and data analytics. It is not surprising therefore that business strategies are built around AI and data analytics. The question that comes to mind is, “How many organizations have successfully integrated AI into their business?” A joint research between MIT Sloan Management Review and The Boston Consulting Group illustrates that few organizations understand what’s required to adopt AI. Their study showed that 23% of the organizations they surveyed have adopted the technology beyond the pilot stage. In fact, less than one in five organizations have integrated AI into just some of their processes and offerings. And just one in 20 organizations has integrated AI throughout their organization.

What are the barriers then for the implementation of Data Analytics and AI? The said study identified 2 barriers, namely access to talent, and usable data. AI talents are quite expensive as most, if not all, AI experts are highly paid, not to mention that competition is fierce. What can we do to build the talent pool? Alternative courses of action to address the shortage and access to talents have to be defined.


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