Artificial intelligence is fast becoming a business imperative. Whether it’s to improve efficiency, find new business opportunities, or keep up with — or get ahead of — the competition, companies across all industries are exploring the business benefits of AI, with AI adoption tripling in the past year alone.
For some companies, that means building AI systems from scratch. But finding the right talent is difficult and expensive, and, at 85 percent, AI projects have a high likelihood of failure, according to Gartner. Even when a project works, a commercial vendor might soon come out with something better, at a lower cost, with regular upgrades, more integrations, and a more intuitive UI. Or, your DIY AI sweat equity might be rendered superfluous when the new AI capability you’re working on is included as a free feature or upgrade to a platform your company already uses.
Using a commercial product, on the other hand, can facilitate rapid experimentation with many different AI technologies, and minimal investment. And to succeed with AI, volume is important, says Rob Thomas, IBM’s general manager of IBM Data and Watson AI.
“I encourage clients to do 100 AI pilots,” Thomas says. “Not one, not two, but 100. Half of them won’t work, but the half that work can really pay off.”