The uptake of artificial intelligence in business has been sluggish. However nearly half of the CIOs surveyed by Gartner said they have plans to implement the technology and those that already had shared some key AI lessons.
“Despite huge levels of interest in AI technologies, current implementations remain at quite low levels,” said 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.”
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Gartner outlined four lessons that have emerged from AI pioneers in their report, Lessons From Early AI Projects.
1. Aim Low at First
Don’t expect AI to deliver step changes overnight. According to Gartner analysts, early experimental AI will likely reveal insights to inform larger pilot programs and not much more.
“Don’t fall into the trap of primarily seeking hard outcomes, such as direct financial gains, with AI projects,” said 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.”
If a financial goal must be attached to early AI projects, try to keep the target as low as possible, Andrews said.
2. Focus on Augmenting People, Not Replacing Them
Despite concerns, AI is not all about reducing labour costs and organisations who approach the technology in this manner stand to miss out real gains. Instead, early AI projects should focus on enabling employees to pursue higher value activities.
“Leave behind notions of vast teams of infinitely duplicable ‘smart agents’ able to execute tasks just like humans,” said Andrews. “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 every day.”
3. Plan for Knowledge Transfer
A dearth of talent in data analytics talent means most organisations aren’t able to run AI programs completely in-house and must rely on partners. However, Gartner analysts recommend organisations begin collecting and storing data now, with an eye for future AI programs.
“Relying mostly on external suppliers for these skills is not an ideal long-term solution,” said Jim Hare, research vice president at Gartner.
“Therefore, ensure that early AI projects help transfer knowledge from external experts to your employees, and build up your organisation’s in-house capabilities before moving on to large-scale projects.”
4. Choose Transparent AI Solutions
Executives should also push for transparency in AI partnerships, including pushing for provisions in any service agreement. It is not enough for AI to work, the organisations must also understand why it works, Gartner analysts said.
Further, AI decisions can also be subject to regulation and auditing, meaning transparency becomes a legal issue.