Research

Transform.AI brought together enterprise and startup CEOs, economists, technologists, venture capitalists, and journalists. We discussed the myths and realities of the economic impact of AI, enterprise applications of AI, the ethical questions surrounding AI, and the state of what’s possible in the field. Here is part three of the highlights.

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Yes, Artificial Intelligence Is Analytics

By Bill Franks, Sep 14, 2017

There seems to be some confusion as to exactly what artificial intelligence (AI) is, and how the discipline of AI should be categorized. Is AI a form of analytics or is it a totally new discipline that is distinct from analytics? I firmly believe that AI is more closely related to predictive analytics and data science than to any other discipline. One might even argue that AI is the next generation of predictive analytics. Additionally, AI is often utilized in situations where it is necessary to operationalize the analytics process. So, in that sense, AI is also often pushing the envelope of prescriptive, operationalized analytics. It would be a mistake to say that AI is not a form of analytics.

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Transform.AI brought together enterprise and startup CEOs, economists, technologists, venture capitalists, and journalists. We discussed the myths and realities of the economic impact of AI, enterprise applications of AI, the ethical questions surrounding AI, and the state of what’s possible in the field. Here is part two of the highlights.

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Transform.AI brought together enterprise and startup CEOs, economists, technologists, venture capitalists, and journalists. We discussed the myths and realities of the economic impact of AI, enterprise applications of AI, the ethical questions surrounding AI, and the state of what’s possible in the field. Here are some highlights.

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Sarmila Basu’s team of data scientists is using machine learning and modeling to save Microsoft millions of dollars on heating, cooling, and other facilities maintenance costs.

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“The real issue is that every business is now a tech business – whether it wants to be or not – and that means not just new skills and experiences, but a new outlook on opportunity and strategy.” This quote is from a recent Forbes analysis of the different business models companies can deploy and how each one is performing in the new digital world.

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A Revolution in Analytical Technology

By Thomas H. Davenport, Aug 22, 2017

It’s been 10 years since Jeanne Harris and I published our book, Competing on Analytics, and we’ve just finished updating it for early-fall (2017) re-publication. We realized during this process that there have been a lot of changes in the world of analytics.

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Digital Systems Maturity Model

By Geoffrey Moore, Aug 17, 2017

Every so often a phrase emerges from the Word Cloud to achieve capital importance, the sort of thing that authors and pundits can dine out on years to come (well, we do have to eat too, you know). At present that phrase is digital transformation.

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When it comes to creating a more data-and-analytics-driven workforce, many companies make the mistake of conflating analytics training with data adoption. While training is indeed critical, having an adoption plan in place is even more essential.

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The analysis of Internet of Things (IoT) data is quickly becoming a mainstream activity. For this blog, I’m going to focus on a few unique challenges that you’ll most likely encounter as you move to take IoT data into the AoT realm.

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