The Reason Most Companies Are Failing At AI Implementation

Those that are failing at deriving value treat it as a plug and play tool rather than a disruptive force that requires rethinking operations, staffing and strategy. JL

Jonathan Vanian reports in Fortune:

Seven out of ten companies report little to no impact from their A.I. projects so far. 40% of the surveyed companies that have made “significant investments” in A.I. have yet to report any business gains.There is a clear difference in the A.I. strategies between the “winners” and “losers."  Companies that are getting some value from their investments view A.I. as a way to upend and change current business practices likes sales, rather than simply buying an A.I. tool from a vendor. Also, at the most successful companies, business leaders oversee A.I. initiatives.
Most companies that say they're using artificial intelligence have yet to gain any value from their A.I. investments.
A survey from MIT Sloan Management Review and Boston Consulting Group found that companies that view A.I. as merely a “technology thing,” akin to a product rather than a business overhaul, fail to gain financial results. The survey’s authors defined the “value” of an A.I. project as lifting sales, reducing costs, or creating a new product.
The survey, based on responses from nearly 2,500 executives, found that seven out of ten companies report little to no impact from their A.I. projects so far. Overall, 40% of the surveyed companies that have made “significant investments” in A.I. have yet to report any business gains.
There is a clear difference in the A.I. strategies between the “winners” and “losers,” according to Boston Consulting Group managing director Shervin Khodabandeh. For instance, companies that are getting some value from their investments view A.I. as a way to upend and change current business practices likes sales, rather than simply buying an A.I. tool from a vendor, he said.
Also, at the most successful companies, business leaders oversee A.I. initiatives. These executives, who control budgeting and resources, then build a group of data scientists and key personnel from departments like sales or marketing to oversee the A.I. project to completion.
This process is markedly different than the traditional technology approach at most businesses, in which CIOs decide which data-crunching projects to pursue. The downside to this CIO-driven tactic, Khodabandeh said, is that the A.I. projects become isolated and neglected by the overall executive team.
The report confirms the findings of other recent surveys about A.I. and business that show companies struggle with their data-crunching initiatives. A KPMG survey earlier this year found that most executives believe it will take many years before their A.I. projects create a “significant return on investment.”
Beyond the latest survey, Khodabandeh said companies that are successful in using A.I. often create their own mini-IT departments, built specifically for A.I. projects. Doing so allows the companies to brainstorm a specific business process they want to improve, like forecasting which products to sell, and then letting their data scientists pick and choose the A.I. technologies to do the job.
“He or she starts with something like, ‘I want my marketer to do their business differently,’” Khodabandeh said about how business-side executives should approach A.I.. “They don’t say, ‘I need reinforcement learning.’”