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Measuring ROI for AI investments? Put on your venture capitalist hat

 

Think RD, develop projects in parallel

Interest in AI abounds, but actual deployments of the technology are still relatively few. In a recent Forrester Research survey, 58% of business and technology professionals said they’re researching AI, but only 12% said they are currently using AI systems.

Mike Gualtieri, ForresterMike Gualtieri

The limited use of the technology provides an opening for CIOs to create competitive advantage and even carve out new revenue streams. “Until artificial intelligence in applications becomes the norm, you have an opportunity to get out in front of the trend and use AI to facilitate more efficient business processes and, of course, better, more individualized customer experiences,” Mike Gualtieri, an analyst at Forrester Research, wrote in “Artificial Intelligence: What’s Possible For Enterprises in 2017.”

And AI projects don’t have to require a lot of talent or a lot of money. “Cloud companies — Amazon, Google, Microsoft, IBM, HP [Hewlett Packard Enterprise] and their cloud — they have what’s called pretrained models,” Gualtieri said in an interview with SearchCIO. “So, they have AI sort of baked into the APIs already.”

But AI investments do hinge on data models that have to be tuned, and that tuning takes time and often requires additional and/or different data to get a result, Gualtieri said. “You may see a business benefit, but it’s not until you actually work with the data and use the algorithms that you’ll know if it will work.”

A more realistic way to look at AI investments, according to Gualtieri, is to see them as research and development (RD) projects. “When you’re doing this stuff, you have to think like a venture capitalist,” he said. “Venture capitalists will invest in 10, 12 companies. They believe they’re all going to be successful, but statistically, they know that only two or three are going to be fabulously successful.”

By treating AI technologies as RD efforts — including those AI investments with relatively proven technology — CIOs will have the time to experiment and the space to develop multiple projects in parallel, which Gualtieri said is key. “Otherwise, if it’s sequential, if you just have this one idea and you spend three months and it doesn’t work, well, now, you need to find the next idea, which can put you behind the eight ball,” he said.

Indeed, Gualtieri said bigger companies are making use of their innovation labs, which are funded for the express purpose to experiment without proving an ROI, to oversee and pursue their AI investments.

AI investment advice

CIOs may want to turn their attention to Amazon Lex as a point of entry for AI investments. The Amazon service, powered by the same conversational engine as the company’s Alexa bot, introduced a chatbot interface API last fall. The service makes building an application on the Amazon Echo platform fairly straightforward for application developers and designers, according to Mike Gualtieri, an analyst at Forrester Research. “Amazon has created an API that lets companies create an experience that’s specific to their business domain,” he said. It’s not good for everything, he warned, but no AI experience is needed.

 

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