AI will drive business value via decision support, human augmentation

Gartner paints a nice hybrid AI approach where humans and machines work together through 2030 to drive business value.

Enterprise organizations plan to double their AI and ML projects within a year Over half of organizations already have at least one AI or ML project in place, Gartner says. Read more: https://zd.net/2LHKZmD

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Artificial intelligence will drive worker productivity in the years ahead primarily through decision support as humans everywhere get a crutch when it is time to make a call, according to a Gartner estimate.

Gartner estimates that artificial intelligence augmentation will create $2.9 trillion in business value and 6.2 billion hours of worker productivity in 2021.

The general idea from Gartner is that augmented intelligence won't take over human tasks, but improve learning, decision making, and experiences. This combination of human and AI know-how will drive productivity for enterprises.

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By 2030, decision support and augmentation will surpass all other AI initiatives in terms of business value and represent 44% of the market. Smart products will be 13% of business value with decision automation at 19% and agents at 24%.

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Why would decision support and augmentation drive so much business value? Here are a few thoughts:

  1. For starters, decision support and augmentation are the least controversial in the AI food chain. If you're using AI to augment decisions, improve data and quality, the customer experience improves and drives revenue without automating humans. That nice balance means AI doesn't draw the political fire that automation would.
  2. Decision support and augmentation can democratize data, and that improves corporations too.
  3. Humans are more comfortable with the hybrid approach to AI.

However, it may be worth looking at the big picture in 2030 and the No. 2 and No. 3 business value generators in AI. Agents will drive a lot of business value and likely replace humans to some degree. And decision automation will ultimately scale and mean machines will make more calls.

Bottom line: While 2030 may have a nice human-AI balance to it, the decades beyond that may be more zero-sum.

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