10 Things Your Artificial Intelligence Initiative Needs to Succeed - InformationWeek

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4/20/2021
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Lisa Morgan
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10 Things Your Artificial Intelligence Initiative Needs to Succeed

In the race to implement AI, some companies may overlook important details that can mean the difference between success and failure.
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Credit: Gorodenkoff via Adobe Stock
Credit: Gorodenkoff via Adobe Stock

The rush is on to implement in a battle for competitive advantage. However, in the haste to implement, some organizations are stumbling because their initiative lacks a solid foundation.

"People want to solve problems with AI just because it's AI and not because it's the best solution," said Scott Zoldi, chief analytics officer at analytics decisioning platform provider FICO. "It has to be soup to nuts. How are we going to develop AI from a governed perspective of having a governance process that talks about the data, the success criteria and the risks from both a project perspective and an ethical perspective?"

Some AI initiatives falter because the thinking that went into them was inadequate. For example: 

  • The AI initiative is created separately from the business strategy so it fails to make a strategic impact.
  • The success criteria are overly broad because they fail to include a success metric (E.g., "We want to be more competitive" as opposed to "We want to reduce fraud by 15% while reducing the number of false positives by 30%.")
  • The change management aspect wasn't considered so the initiative faces resistance.

"Shared capabilities or shared data across business units is becoming more important than the autonomy of individual units," said Marco Iansiti, David Sarnoff professor of business administration at Harvard Business School, who heads the technology and operations management unit and chairs the Digital Initiative. "This causes all kinds of difficulties in traditional organizations because all of a sudden, you have a person who runs investment banking that has never shared anything with the person who runs wealth management. And all of a sudden, they are both interested in leveraging some of the same algorithms and some of the same components. They have to standardize because before they didn't have to."

The use of AI has become such a strategic issue that CEOs are getting involved in defining what their company's AI strategy would look like.

"Earlier, we were seeing it was the CIO, CTO and some CXOs, but now the leading CEOs realize that this is going to redefine the future of their industry and the future of their own company," said Arnab Chakraborty, global managing director, applied intelligence North America lead at global consulting company Accenture. "They're looking at this as a reinvention of their business in the context of where things are headed with AI."

Some of the common missteps can be avoided or minimized by thinking through the initiative in a holistic manner and involving those in the value stream who can help think through the various aspects -- opportunities, risks, potential impacts, success factors, data requirements, compliance issues, governance, etc. Other success factors follow.

Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include ... View Full Bio

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