Insights from a session at one of ConferenceDirect’s exclusive client events earlier this year on AI adoption in the meetings and events industry

If you needed a single image to capture where we are with artificial intelligence, consider this: In just five cities — Phoenix, Los Angeles, San Francisco, Atlanta and Austin — roughly 2 million people a month are climbing into a driverless Waymo car. No driver. No steering wheel in use. Two million rides a month — and that number is climbing. As Frank Leonard, strategic business advisor with 42Chat, said at ConferenceDirect’s inaugural The Meeting Summit held in New Orleans earlier this year, “If you’re not sure if AI is here, that’s a good example to say, ‘Oh my gosh, it’s here.’”

For those of us in the meetings and events world, that moment of recognition is arriving fast. This session brought together hoteliers, meeting planners, agency professionals and event technology experts to share how they’re using AI right now — not in theory, not in a future roadmap, but today. The conversation was honest, practical and, at times, surprising. Here’s some of the insights they shared.

The “Upskill or Fall Behind” Moment

The session opened with an analogy that landed with the audience: AI today is like email in the 1990s — only moving faster. Back then, learning email felt urgent and transformative. Today, AI is that, amplified.

Enterprise leaders are definitely feeling that pressure. One hospitality executive described conversations with a corporate client responsible for 500 employees. The old dynamic — an employee coming to management saying, “I’m doing the work of two people, we need to hire,” is being replaced with a new expectation: How much are you using AI, and can you do the work of five or 10 people?

That’s not a hypothetical future. It’s a present-tense conversation happening in corporate offices right now. And the data backs it up: According to a recent DataCamp study, AI-literate employees are expected to become up to 20% more productive, and organizations with mature AI upskilling programs are nearly twice as likely to report significant positive ROI on their AI investments. Nowadays, upskilling isn’t optional for anyone, much less meeting professionals.

Enterprise AI vs. Individual AI: Two Different Games

One of the clearest frameworks to emerge from the session was the distinction between how large organizations use AI versus how individuals use it.

On the enterprise side, the goals are ROI, scalability and cross-departmental efficiency. Companies are spending millions on AI infrastructure and they want compliance, meaning near-100% daily usage from employees. Several large corporations are now actively monitoring AI adoption by staff, not to penalize but to protect their investment. If your company has deployed Microsoft Copilot or a similar platform, there’s a good chance someone is tracking whether you’re using it.

On the individual side, the goals are more immediate: productivity, creativity, content generation and efficiency. Most meeting professionals in the room were using tools like ChatGPT, Microsoft Copilot, Google Gemini or Claude — often for research, writing and summarization. Retail AI (Siri, Alexa) and creative tools (Adobe, Canva) are also part of the mix, whether people consciously label them as “AI” or not.

This gap matters because individual users often have to self-direct their adoption, while enterprise deployments come with training, compliance expectations and investment pressures. Understanding which world you’re operating in helps clarify what’s expected — and what’s possible.

What Meeting Planners Are Actually Doing with AI

The richest part of the session was a breakout roundtable discussion where attendees shared with others at their table specific ways they and their clients are using AI. Here’s a sampling of what came up:

Contract review and risk analysis. Several hoteliers described using Copilot to analyze customer contracts and addendums — not to replace their legal team, but to get a plain-English read on risk areas and identify places to propose alternative language. For professionals who aren’t attorneys but are expected to navigate complex agreements, this use case is a genuine game-changer.

Meeting notes and CRM data entry. One attendee described how their organization uses AI-powered note-taking tools during client meetings. A team leader joins calls, starts the recorder, and the resulting transcript and summary get edited collaboratively and uploaded to account tracking systems. What used to be manual data entry is now largely automated. The broader observation from the session: Before COVID, almost no one recorded meetings; today, almost every meeting is recorded. In five years, the norm has flipped entirely.

Data analytics and media performance. The COO of a legal professional association described using AI to run data analytics on media performance — understanding trends and usage patterns that would have taken weeks of manual spreadsheet work to surface. It’s also helped the team with budget drafting and copy approval workflows.

Contract comparison. One creative use case: Uploading two versions of a contract into Copilot to surface differences that might otherwise require painstaking manual red-lining. The tool can call out edits and flag areas for discussion.

Rewriting for tone. Multiple attendees mentioned using AI to rewrite emails or messages that might come across too bluntly — getting the point across with more professional or diplomatic language. A small but time-saving use case that’s become almost reflexive for some.

Event themes, taglines and creative. One meeting planner described using AI to generate event themes for a major tech company — and then, in a move that got a knowing laugh from the audience, using AI again to figure out how to sell those themes to senior leadership. Planners are using it for the first pass on copy, with human editors reviewing and refining rather than generating from scratch.

Session abstracts and call-for-papers review. For large conferences — especially in the medical and academic world with hundreds or thousands of paper submissions — AI is beginning to handle the initial review and filtering work, applying consistent criteria at scale.

Customized AI “voice of God” announcements. One attendee described an upcoming event for 300 people where AI-generated audio will replicate the voice of a well-known sports figure — customized to the event’s theme — to introduce speakers. Encore is reportedly offering similar capabilities now.

The Attendee Experience: Where AI Is Heading

The second half of the session focused on the attendee side: How AI is being used (and could be used) to personalize and improve the event experience?

Personalized content recommendations. The idea of Netflix-style content recommendations for events — where AI learns what’s relevant to each attendee and surfaces the sessions, people and exhibitors most likely to matter — is now a reality, not a wish-list item. Machine learning has been doing this in consumer technology for years, and now it’s making its way into event platforms. According to a 2025 meetings industry report, AI tools have opened up possibilities for “personalized experiences, enhanced networking opportunities, and improved analytics” for event professionals.

AI-powered matchmaking. Several attendees described a near-future (and in some cases already-present) capability: AI that takes an attendees’ stated goals, matches them against other attendees’ goals, and proactively sets up meetings — even reaching out on their behalf to the people they haven’t connected with yet. The parallel drawn was to how medical residency-matching works, only automated and in real-time. One industry analysis found that Clarion Events achieved a 44% increase in in-person meetings through AI matchmaking.

Facial recognition and booth analytics. For exhibitors, the frontier is measurable engagement: knowing not just that someone passed your booth, but how long they stood there, who they were (with consent frameworks), and what was said. Some technology is already tracking booth dwell time by demographic. Integrations with CRM systems — so that booth conversations automatically populate contact records — are in active development.

Seamless registration. One attendee articulated a “lazy but smart” vision: An attendee could just show up to a conference where AI has pre-populated their registration and loaded their preferences from existing data sources and loaded their preferences, so all the attendee has to do is confirm or adjust. The friction of filling out forms — for an audience that has already given all this information a dozen times — essentially disappears.

Accessibility. One of the most compelling moments in the session came from an attendee who noted that AI apps are now enabling people with visual impairments to navigate arrivals, hotels and event venues independently. Her uncle, who lost his eyesight completely, now travels again — on his own — because of this technology. It’s a reminder that the same tools driving efficiency gains for planners are expanding access and independence for people who were previously excluded.

Real-time transcription tools. Tools like Otter.ai and Wordly came up repeatedly. The ability to transcribe in real time, generate summaries and search through transcripts by topic has become a baseline expectation for many attendees. Several people noted they’re already using these for one-on-one meetings, and the wish is to have the same capability for all their interactions at an event — automatically collated and actionable when they get home.

Text-based communication. The session also touched on how AI-powered chatbots (such as 42Chat, which was represented in the room and powers ConferenceDirect’s Brianna chatbot) have evolved beyond logistics answers (“What time does the session start?”) into revenue-generating tools — reaching out to exhibitors about booth renewals or attendees about next year’s registration at precisely the right moment, via text channels with 98% open rates.

The Elephant in the Room: Data, Privacy and Compliance

Not everything about AI adoption is frictionless. A few important tension points surfaced:

The COO of the intellectual property attorneys’ association noted that her membership — attorneys who work in IP law — actively objects to being recorded in meetings. For that group, the AI-powered meeting transcription that everyone else is celebrating is a non-starter. The lesson: Know your audience, and have a clear disclosure and consent policy before you start recording or deploying facial recognition or voice capture.

On the enterprise side, compliance expectations are running ahead of individual comfort levels in some organizations. The message from leadership is increasingly, “We’ve invested heavily in AI tools, we expect you to use them daily, and we’re monitoring adoption.” That’s motivating for some; anxiety-inducing for others. The answer, consistently, is training and demystification — helping people understand what the tools actually do rather than leaving them to imagine the worst.

Time to Take Action

Participants walked out of this session with some actionable messages:

Start using AI if you haven’t. The window for “I’ll wait and see” has closed. The tools are good enough, accessible enough and expected enough that professional competitiveness now depends on at least baseline fluency. Pick one tool — Copilot, ChatGPT, Claude or Gemini, for example — and start using it for tasks you already do, such as drafting emails, summarizing documents, doing research or reviewing contracts.

Understand your organization’s expectations. If you work for a large company or association, there’s likely an official AI platform and an expectation that you use it. Find out what it is, take advantage of any training offered, and make sure you’re not the person in the room who doesn’t know how to use it.

Think beyond the obvious use cases. The most interesting examples from this session weren’t the obvious ones (write this email, summarize this document). They were the creative applications: Using AI to analyze what’s between two contracts, to generate event themes and then figure out how to pitch them, and to personalize the attendee experience in ways that weren’t financially feasible before.

Don’t ignore the attendee side. If you’re a planner, your attendees are developing expectations shaped by their experiences as consumers. Netflix knows what they want to watch. Spotify knows what they want to hear. They’re going to start expecting that a conference platform knows who they should meet.

Embrace the good. AI is going to produce problems, such as misuse, privacy violations and errors. It’s also going to produce things like enabling a sight-disabled man to travel independently again. As session presenter Frank Leonard with 42Chat put it, “There’s going to be some plenty of good things that come out of it, too.”