Generative artificial intelligence (AI) bots such as Microsoft Copilot, Google Gemini and ChatGPT are making inroads in meeting and event planning at an ever-increasing pace. But can these AI bots be useful for incentive planning as well? That’s something the Incentive Research Foundation recently explored in a series of focus groups with suppliers, third parties and program owners.

While many expressed some concerns about data privacy, especially when it comes to proprietary information and personally identifiable information (PII), that can be controlled by using private generative AI models such as Spark, as well as putting usage policies in place. Others said they just hadn’t yet had the time to work with an AI, while others expressed concern about losing human connections and critical thinking.

But most of the participants agreed that, like it or not, AI is here to stay — and it should be. The benefits of increased efficiency make it well worth any perceived risks, just like any other new technology.

Here are 14 of the many ways they said they are using AI for their incentive travel programs.

• To suggest an appropriate incentive trip destination based on your attendee profile, past destinations and budget.

• To answer attendee questions. Instead of having your coordinator field thousands of emailed questions — the answers to which are, of course, in the registration materials that apparently no one reads — you can use AI to provide the answers.

• To identify the best way to motivate and reward a specific group using data from past programs, sales and product data. AI also can help analyze past attendee data and recommend ways to adjust programs to better meet the company’s diversity, equity and inclusion (DEI) objectives.

• To identify which incentives spur the most revenue-affecting results from incentive participants, and which are lower performing.

• For third parties, to land new business by using AI to learn about specific organizations and market niches, a prospect’s key competitors, the regulatory environment in which the prospect works, and other relevant factors to get a competitive edge. Third parties also said they were using AI to generate program communications and writing session descriptions.

• To come up with rough first drafts of communications such as program rules, updates, website content and launches — with the caveat that these are just first drafts and a human needs to get involved before anything goes public.

• To brainstorm ideas for themes.

• To find some “wow” activity options for specific destinations — as well as reasons why certain activities aren’t a great option for a specific group. Just be sure to check that the AI didn’t “hallucinate” or make up some options that don’t exist, which does happen. Some said they were using AI to create itineraries for programs that are too small to be worth engaging a third party to manage.

• To predict winner pools/size/scope using aggregated program data or redacted PII.

• To generate a recommended budget for the program using expected results and the number of participants, and/or use historical spend and profit targets to recommend ways to improve ROI.

• To generate a list of rewards based on audience profile data, such as demographics, psychographics and salary ranges.

• To optimize education session times based on the audience profile.

• To recommend personal room gift ideas based on attendee preference data (if you collect information on favorite foods and beverages, allergies, hobbies, etc.).

• To develop a better understanding of participants, including the difference between past winners and first timers when it comes to generational factors and what motivates each, based on historical data.

But that’s just the tip of the incentive iceberg when it comes to using generative AI. As long as you’re cognizant about protecting confidential data and PII, the potential uses of AI for incentive planning are as varied as the programs you plan.