Discussions: Mike Bushman on the Finest Use Cases for Events with Generative AI

As requested, RainFocus CTO Mike Bushman is returning for another round of assisting marketing and events teams in understanding the most recent developments in generative AI!

In our most recent discussion, we covered important topics like openness, trust, and the arrival of multiple large corporations. We’re now delving further into the most interesting use cases to far. Additionally, you will discover how RainFocus goes about adding possible new generative AI capabilities to the platform.

What are the primary generative AI use cases for events that you are currently seeing from clients?

We see clients adopting generative AI to write emails and session content, as well as to automatically take notes during meetings, as these models’ natural language capabilities have improved. They can also be used to extract valuable information from unstructured data. AI is being used, for instance, in surveys for word clouds, summaries, sentiment analysis, and classification.

Our customers’ primary priority is always assisting guests in finding the appropriate material at events. Here, generative AI can be used to propose cohorts of sessions, session tagging, and classification. These can be used to enhance and supplement the session catalog’s current filters.

Additionally, we have used machine learning and more conventional, rather than generative, AI to offer tailored suggestions for at least four major events this year. Attendees’ hobbies, pastimes, and groups influence this customisation.

According to our most recent event content survey, event teams most frequently used generative AI for relatively easy tasks like content creation and transcription. As technology advances and people’ trust grows, do you see a shift toward increasingly complex tasks?

Session scheduling is another intriguing use case that we have already seen, and it may entail some quite complex algorithms. A list of sessions can be automatically suggested and scheduled for the participant. This list may be curated or the recommendation engine’s AI-personalized list.

Many people are searching for prompt responses to their frequently asked event management issues on the data exploration side. “How many people have registered this week?” is one of the questions they ask. or “What is the number of authorized speakers who have uploaded their bios?” Generative AI can quickly locate the reports that address these queries and then recommend related reports that might be useful.

Using natural language to automatically generate reports is another way to achieve true data exploration. Our metadata layer, which considers responsibilities and data access rights, may be used to accomplish this safely. Basically, anyone may utilize our report builder or ask questions to obtain useful information.