What’s happening in artificial intelligence in the year ahead? Look for modeling at the edge, new attention to data governance, and continued talent wars, among key AI trends.
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Artificial intelligence: Everybody’s doing it.
Few are doing it well, however. In fact, nine out of ten companies have made some investment in AI, but 70 percent said they have seen minimal or no impact from AI thus far, according to the 2019 MIT SMR-BCG Artificial Intelligence Global Executive Study and Research Report.
Looking ahead to 2020, CIOs will need to better assess the value of their AI bets and prove that ROI to the business, says Kara Longo Korte, director of product management at TetraVX. That’s the headline for Forrester’s AI prognostications as well: “We believe 2020 will be the year when companies become laser-focused on AI value, leap out of experimentation mode, and ground themselves in reality to accelerate adoption,” Forrester analysts write.
Artificial intelligence (AI) trends for 2020
It looks to be an active year ahead on the AI front, with a number of relevant trends unfolding that IT leaders should follow:
1. IT leaders will get real about measuring AI impact
Here’s a sobering stat: Fewer than two out of five companies reported business gains from AI in the past three years, according to the MIT AI survey. That will need to change in the new year, given the significant investment organizations are continuing to make in AI capabilities.
One way to achieve this is to change the way we measure results. Think reporting against things like ease of use, improved processes, and customer satisfaction. “CIOs will also need to continue to put more of their budgets against understanding how AI can benefit their organizations and implement solutions that provide real ROI,” says Jean-François Gagné, CEO and co-founder of software provider Element AI, “or risk falling behind competitors.”
2. Operationalization will be the name of the game
AI has the potential to become the new operating system for the enterprise. “Over the last decade, organizations have been picking up AI know-how and started working with the technology, but successfully putting models into production has remained a challenge,” Gagné says. “This year will be a tipping point for the infrastructure needed to support effective deployments, providing integrated learning environments and data ecosystems that support adaptive decision making by AI.”
3. Data governance will get sexy