Agentic AI vs Generative AI: What Event Planners Have to Know | InEvent

Most occasion groups already use generative AI. You ask, it writes. Agentic AI is the following step, and the distinction between the 2 is just not intelligence. It is permission. A generative software fingers you a draft. An agentic software takes an motion.

That adjustments the planner’s job. The ability is not writing a great immediate. It is deciding what a machine might do in your behalf, and that, in our view, is the actual AI resolution occasion groups face. Most “which AI tool is best” debates skip it.

This piece attracts on the InEvent Open House of October 8, 2026, the place Katie McIntyre, Director of Technical Architecture at Opus Agency, and Wendy Porter, Founder and Chief Event Strategist at Wendy Porter Events, defined how they use each sorts of AI in actual occasion work.

What is the distinction between agentic AI and generative AI?

Generative AI creates content material if you immediate it, then waits on your subsequent instruction. Agentic AI takes a aim, decides its personal steps and carries them out, usually inside different software program, with out checking in at every step. One provides you drafts to approve. The different provides you actions you must belief.

Katie McIntyre put the distinction merely on the Open House. Generative AI “is responding to your prompts. It’s asking you what you want and then doing its best to match that.” Agentic AI “can ingest a request, and then it is empowered to do its own thing with that.” The clue, she stated, is within the title: it has company. For a deeper technical comparability, see IBM’s explainer on agentic AI vs. generative AI.

That final row is the entire story. A nasty draft prices you a couple of minutes of modifying. A nasty motion can attain attendees, sponsors or your information earlier than anybody seems to be. So the transfer from generative to agentic is just not primarily a expertise improve. It is a call about belief.

Agentic AI vs generative AI examples in occasion planning

The clearest strategy to see the distinction is to line up actual duties, from pure drafting to full motion. All 5 beneath got here up on the Open House.

1. Polishing your writing (generative). Wendy Porter educated as a math main and doesn’t see herself as a pure author. “But I know what I want to say,” she stated. She provides ChatGPT her factors and will get again tighter copy that also appears like her. Nothing occurs till she approves it. That is generative AI at its greatest.
2. Loading a thousand choices (agentic, low stakes). Katie used to kind each selection right into a platform’s dropdown menu by hand. Now, via MCPs (Model Context Protocol connections that allow an AI software work inside different software program), she will be able to hand over an inventory and say, “here is an import list, please add these.” In her phrases, it’s “literally put thing A into place B.” The AI is performing, not drafting, however there isn’t a judgment concerned.
3. Pulling particulars out of fifty locations (agentic, medium stakes). Event particulars arrive from in every single place: the present proprietor’s prospectus, shopper emails, vendor messages. Today, Wendy stated, her workforce has to “toggle around, you know, 50 places” to assemble the total image. She needs agentic AI to scan these sources and drop the important thing information into one mission plan. Here the agent is selecting what counts as vital, so an individual must test what it pulled.
4. Picking the chief visitor listing (agentic, excessive stakes). For unique govt applications, Katie described feeding partly anonymized CRM information to AI and asking “who’s actually active, who’s actually given buying signals,” fairly than who has the grandest title. It replaces sales-team lobbying with proof. It additionally decides who will get a seat, which is why the ultimate listing ought to nonetheless be human-approved.
5. Choosing classes for attendees (agentic, another person’s stakes). Katie described a future by which an attendee’s AI works as a “contextual wallet.” It is aware of their preferences, scans the session catalog, picks the very best classes and books them. The agent now acts for another person, and its selections have an effect on audio system and sponsors who by no means agreed to its guidelines.

Notice the sample. The expertise barely adjustments from instance 2 to instance 5. What adjustments is how a lot judgment the AI workouts, and whose pursuits journey on it.

What can an AI agent do for an occasion workforce?

An AI agent for occasion administration can deal with any process the place the steps are clear and a mistake is reasonable to catch. Our rule: delegate by the choice, not by the duty. Ask what judgment the job requires and who pays if the agent will get it fallacious.

That provides three ranges of belief:

1. No choices: let the agent act. Imports, information entry, copying dates right into a plan, reformatting a schedule. Katie loves these jobs for AI exactly as a result of they’re “the thing that doesn’t need my human curiosity.”
2. Decisions with inner stakes: let the agent suggest, then approve. Shortlisting VIP company, proposing a schedule, filling a finances. The agent does the legwork; an individual indicators off. Wendy’s personal check exhibits why. She gave AI her finances template and a shopper’s numbers, and it “didn’t actually do as well as I had hoped.” Recommendation mode caught that. Action mode wouldn’t have.
3. Decisions that have an effect on different individuals: set the foundations and audit the outcomes. Anything that decides what attendees see or which sponsors get publicity. Here the agent’s guidelines matter greater than any single output, so individuals write the foundations and overview the patterns.

There is a prerequisite underneath all three ranges. “I don’t want to have the AI conversation with you if we haven’t already had the data conversation,” Katie stated. That applies doubly to brokers. A generative software given messy information writes one unhealthy paragraph. An agent given messy information acts on it, time and again, at pace.

Where ought to a human keep within the loop?

A human ought to keep within the loop wherever an agent’s selections form another person’s expertise, cash or entry. For occasion groups, which means attendee personalization, sponsor publicity and something that filters what individuals see.

Katie’s contextual-wallet instance is the place this will get actual. An agent that picks your classes appears like a useful new door into the occasion. But, she requested, “at what point does it stop being a door and start being a gatekeeper at the door?” If the agent learns that you just skip sponsored content material, it could cease displaying you any. The attendee by no means determined that. The sponsor by no means agreed to it. And the organizer might by no means discover.

This is an important open query in occasion expertise, and we predict distributors, InEvent included, owe planners clear solutions. Big exhibits are already there: BizBash’s Dreamforce 2026 report exhibits how Salesforce put autonomous AI brokers in entrance of attendees. Before you turn on any agentic characteristic, ask:

• What can it change with out my approval?
• Can I see a log of each motion it took, and undo them?
• What information can it learn, and the way is attendee information anonymized?
• What is it allowed to filter out, and who set these guidelines?

Wendy’s rule covers the remainder: “anything it spits out, it needs human oversight and review.” Katie went additional. She requested us to maintain some friction on goal, as a result of “friction is how we learn.” Remove it from chores like information entry. Keep it in discovery and dialog, the place the human worth of an occasion lives.

The backside line

Generative AI made occasion groups sooner writers. Agentic AI could make them sooner operators, however provided that they resolve, intentionally, what it could do alone. Start with the no-decision jobs, maintain approval on the remainder, and deal with any agent that acts for attendees or sponsors as a coverage query, not a characteristic toggle. For how planners are utilizing AI daily, learn our recap of the Open House: AI for occasion planning, narrative vs. actuality.

Frequently requested questions

1. What is the principle distinction between agentic AI and generative AI?

Generative AI creates content material in response to a immediate and waits for you. Agentic AI takes a aim, plans its personal steps and acts on them, usually inside different software program. The sensible distinction is that generative AI produces drafts, whereas agentic AI produces actions.

2. What are examples of agentic AI vs generative AI in occasion planning?

Writing a session description or sharpening an e-mail is generative. Importing an inventory of choices into an occasion platform, pulling particulars from many emails into one mission plan, or shortlisting govt company from CRM information is agentic, as a result of the AI acts fairly than simply drafts.

3. Is agentic AI secure to make use of for occasions?

It is secure for duties with no judgment concerned and clear information. For choices that have an effect on attendees or sponsors, maintain an individual approving the output, test the agent’s motion log, and agree on information and privateness guidelines with shoppers first.

About the Author / Adedoyin

Adedoyin is a Content Campaign Manager with 3 years of expertise in main international campaigns and creating focused content material that drives engagement and achieves outcomes, demonstrating confirmed experience within the occasion trade.

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