There are plenty of Artificial Intelligence efforts underway — the global AI adoption rate grew steadily and now is 35%, a four-point increase from the year before, a recent IBM study shows. It’s clear, as shown in the study, that there are tangible benefits — half of organizations are seeing benefits from using AI to automate IT, business or network processes, including cost savings and efficiencies (54%), improvements in IT or network performance (53%), and better experiences for customers (48%).
But bringing in AI means changes for the organization, and the systems and processes that have defined the way business is done. Selling AI as a new way requires some degree of finesse and business sense.
The following are recommendations provided by industry experts who work day to day to advocate greater AI adoption:
Think and understand the problem to be addressed before bringing in the technology. “Instead of coming in and asking for a blank check to tackle numerous vague goals, identify a single problem and outline a clear strategy around how AI will solve it,” says Sagar Shah, client partner at Fractal Analytics. “Highlight the quick wins that can be achieved in the first 12 weeks of the project. This provides clear parameters for skeptics to compare against and judge results.”
It’s a matter of taking more time to understand what problem needs AI applied to it. “The single biggest inhibitor to AI success is relying on unscientific assumptions and broad goals, versus taking the time to frame the exact problems they are trying to solve,” Shah says. “Simply put, the more time a company spends with a problem ahead of time, the better AI product adoption will be.”
Set realistic expectations. “Set realistic expectations of what AI can accomplish,” says Alex Saric, smart procurement expert and CMO at Ivalua. “It can be a powerful aid, but algorithms still have a long way to go. Setting realistic near-term goals and working to improve over time is important. Leaders must sell AI in a way that explains it as helping simplify work, and enabling employees to focus and become more engaged and productive, rather than displace them.” Often, people assume AI means automatic innovation, versus “really understanding what it means for them and how it will be applied every day,” Shah agrees. “At times, a more traditional approach may be more effective than one powered by AI, so buyers must seriously look into the details.”
Get talent on board, but don’t try to build everything yourself. While AI is seen as a labor saver, the skills gap remains the biggest barrier to AI adoption, another recent IBM study shows. “The talent gap is significant, particularly when considering state-of-the-art algorithm development in AI,” says Flavio Villanustre, senior vice president and global chief information security officer for LexisNexis Risk Solutions.
