Use of AI for Incentive Planning Evolves, But Some Are Still Hesitant
Photo Credit: Unsplash / Luisa Brimble
Skift Take
Incentive planners’ use of AI is changing from making their jobs more efficient to customizing programs and analyzing their impact on sales. Still, some refuse to try it.
Incentive planners are increasingly embracing AI: According to one Incentive Research Foundation (IRF) study, 63% of respondents said they already use it or plan to.
Skift Meetings’ recent Rethinking Rewards report revealed the most common use among incentive planners was as a shortcut for tasks that are not a core competency, such as drafting communications or helping with data analysis.
They are also using ChatGPT, or other similar generative AI tools, for brainstorming themes and writing session descriptions.
It also has been helpful for improving program flow: Planners can share itineraries with AI and ask it to optimize the education session times based on the audience profile, or ask it to review the program and make recommended changes based on best practices and research.
Download the Rethinking Rewards report here.
Other emerging uses include:
- Suggesting an incentive location based on attendee profile, past destinations, and budget
- Reviewing the agenda for any DE&I concerns
- For planners who gather attendee preference data, recommending a personal room gift within a certain price range.
Next-Level Applications
Companies at the front of the curve are turning to AI to analyze employee engagement and performance data, which can be used to create personalized incentive programs tailored to specific demographics, behaviors, and preferences.
One10, a performance improvement provider, has leveraged ‘explainable AI’ to analyze sales and product data, and to guide clients as to which incentives most impacted revenue and which were lower-performing.
Bob Miller, president and CEO of One10, believes this level of expertise will lead to more companies relying on agencies to plan their incentives. “DIY incentive departments and small boutiques are not going to be as effective.”
Late Adapters Concerned About Privacy
Among those who have yet to try AI, most hesitation stems from privacy concerns.
One way to manage some of the privacy concerns is to use a private version of AI, which helps protect copyrighted materials and blocks data sharing.
Another roadblock is time. Respondents to the IRF survey reported finding it hard to take the time to experiment with tools like ChatGPT. Others expressed concern that using AI would interfere with human connections and critical thinking.
Incentive planners who are still hesitant to use AI come from multiple age and demographic groups. “The assumption that younger generations would be quicker to adopt this technology seems to be incorrect relative to the incentives industry,” the IRF report concluded.
