10 Things Your Artificial Intelligence Initiative Needs to Succeed


In the race to implement AI, some corporations could overlook essential particulars that may imply the distinction between success and failure.

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Credit: Gorodenkoff via Adobe Stock

Credit: Gorodenkoff through Adobe Stock

The rush is on to implement in a battle for aggressive benefit. However, within the haste to implement, some organizations are stumbling as a result of their initiative lacks a strong basis.

“People want to solve problems with AI just because it’s AI and not because it’s the best solution,” stated Scott Zoldi, chief analytics officer at analytics decisioning platform supplier 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 as a result of the pondering that went into them was insufficient. For instance: 

  • The AI initiative is created individually from the enterprise technique so it fails to make a strategic affect.
  • The success standards are overly broad as a result of they fail to embrace a hit 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 administration side wasn’t thought-about so the initiative faces resistance.

“Shared capabilities or shared data across business units is becoming more important than the autonomy of individual units,” stated Marco Iansiti, David Sarnoff professor of enterprise administration at Harvard Business School, who heads the expertise and operations administration 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 turn into such a strategic challenge that CEOs are getting concerned in defining what their firm’s AI technique would appear to be.

“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,” stated Arnab Chakraborty, international managing director, utilized intelligence North America lead at international consulting firm 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 frequent missteps could be averted or minimized by pondering by the initiative in a holistic method and involving these within the worth stream who may also help assume by the assorted points — alternatives, dangers, potential impacts, success components, information necessities, compliance points, governance, and many others. Other success components observe.

Lisa Morgan is a contract author who covers massive information and BI for InformationWeek. She has contributed articles, experiences, and different kinds of content material to varied publications and websites starting from SD Times to the Economist Intelligent Unit. Frequent areas of protection embrace … View Full Bio

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