Despite considerable talk and industry attention, the reality is that meaningful artificial intelligence (AI) deployments are just beginning to take place, according to Gartner. The research firm’s 2018 CIO Agenda Survey found that just four percent of CIOs said their organization has implemented AI, however another 46 percent said their company has developed plans to do so.
“Despite huge levels of interest in AI technologies, current implementations remain at quite low levels,” says Whit Andrews, research vice president and distinguished analyst at Gartner. “However, there is potential for strong growth as CIOs begin piloting AI programs through a combination of buy, build and outsource efforts.”
As is generally the case with emerging technologies, early adopters face many obstacles to the progress of AI in their organizations. Gartner analysts have identified four lessons that have emerged from these early AI projects.
The first lesson is to aim low at first rather than falling into the trap of primarily seeking hard outcomes with AI projects, such as direct financial gains, says Andrews. In general, it’s best to start AI projects with a small scope and aim for “soft” outcomes, such as process improvements, customer satisfaction or financial benchmarking, he continues.
Expect AI projects to produce, at best, lessons that will help with subsequent, larger experiments, pilots and implementations. What’s more, in some organizations, a financial target will be a requirement to start the project.
“In this situation, set the target as low as possible,” says Andrews. “Think of targets in the thousands or tens of thousands of dollars, understand what you’re trying to accomplish on a small scale, and only then pursue more-dramatic benefits.”
Next, companies should focus on augmenting people rather than replacing them with AI. Big technological advances are often historically associated with a reduction in staff headcount. Nonetheless, while reducing labor costs is attractive to business executives, it’s likely to create resistance from employees whose jobs appear to be at risk.
“We advise clients that the most transformational benefits of AI in the near term will arise from using it to enable employees to pursue higher-value activities,” says Andrews. “Leave behind notions of vast teams of infinitely duplicable ‘smart agents’ able to execute tasks just like humans. It will be far more productive to engage with workers on the front line. Get them excited and engaged with the idea that AI-powered decision support can enhance and elevate the work they do.”
Another key lesson is for companies to plan for knowledge transfer. Gartner’s survey found that most organizations aren’t well-prepared for implementing AI. Specifically, they lack internal skills in data science and plan to rely to a high degree on external providers to fill the gap. Indeed, 53 percent of organizations in the CIO survey rated their own ability to mine and exploit data as “limited”—the lowest level.
“Data is the fuel for AI, so organizations need to prepare now to store and manage even larger amounts of data for AI initiatives,” says Jim Hare, research vice president at Gartner. “Relying mostly on external suppliers for these skills isn’t an ideal long-term solution. Therefore, ensure that early AI projects help transfer knowledge from external experts to your employees, and build up your organization’s in-house capabilities before moving on to large-scale projects.”
Finally, AI projects will often involve software or systems from external service providers, so it’s important that some insight into how decisions are reached is built into any service agreement, Gartner recommends. Although it may not always be possible to explain all the details of an advanced analytical model, such as a deep neural network, it’s important to at least offer some kind of visualization of the potential choices, says Andrews. In fact, in situations where decisions are subject to regulation and auditing, it may be a legal requirement to provide this kind of transparency, he says.
What are your thoughts on use of AI? Does your company have plans to implement AI?