The hype around AI in events is loud. But beneath the noise, something genuinely transformative is happening. A new generation of AI, one that does not just generate content but takes autonomous action, is starting to reshape how commercial events are planned, sold, and delivered.
That was the central message of Grip's recent webinar, Supercharged: How Agentic AI Will Shape the Events Industry, where three of the most hands-on practitioners in this space came together to share what they are actually building, deploying, and measuring.
The panelists were Asghar Maqsood, Group Digital and AI Director at Terrapinn; Max Gabriel, Co-Founder and CEO of Markus AI and former President at Informa; and Maanas Mediratta, Co-Founder and CEO of Bridged, an event growth platform used by over 2,000 events globally. The session was hosted by Hew Leith, SVP of Marketing at Grip.
What followed was a working playbook for commercial event organizers who want to understand what agentic AI is, where to apply it, how to measure it, and how to avoid being left behind by competitors and sponsors who are already moving.
Agentic AI refers to AI systems that can perceive their environment, make decisions, take action, and learn from the results, all with minimal human intervention. Unlike a standard chatbot or a generative AI tool that responds to a single prompt, an agentic system can execute multi-step tasks autonomously, coordinate with other agents, and adapt based on what happens next.
Maanas Mediratta introduced the SPAR framework to explain this clearly. SPAR stands for Sense, Plan, Act, and React. An AI agent senses its environment by reading data signals such as email opens, CRM records, website behavior, and intent signals. It plans by determining which tools to use, which systems to query, and what sequence of actions to take. It acts by executing those steps, processing information, triggering workflows, and even activating other agents. And it reacts by learning from previous outcomes and adjusting its approach over time.
This is the difference between asking ChatGPT a question and deploying an autonomous agent that can nurture an attendee from first touch to confirmed registration without a human needing to intervene at every step.
For commercial event organizers, the implications are significant. Agentic AI does not just help your team work faster. It enables an entirely different operating model, one where repetitive, high-volume tasks like attendee outreach, lead qualification, meeting scheduling, and post-event follow-up can be handled by always-on systems that run 24 hours a day, across every event in your portfolio.
As Maanas put it during the webinar, the industry is moving from a system of record to a system of action. Tools that previously stored data are now capable of engaging audiences, updating records, and creating personalized experiences autonomously. That shift is already underway.
Maanas identified four developments in agentic AI infrastructure that every event leader should understand.
The first is multi-agent orchestration. This is where multiple agents work together, giving each other feedback, verifying outputs, and coordinating tasks. Rather than one monolithic AI, you have a team of specialized agents, each handling a different part of the event lifecycle.
The second is tool usage. Agents are no longer limited to generating text. They can connect to your calendar, send emails, query databases, update CRM records, and trigger downstream systems. They act on data rather than simply describing it.
The third is persistent memory. This was historically a major limitation of AI systems, but it is now being solved. Agents can retain context about individual attendees, specific events, and organizational preferences, which means interactions become more relevant over time rather than starting from scratch each session.
The fourth is voice and multimodal capabilities. Agents can now speak, listen, and process multiple types of input. This matters for events because it opens up entirely new engagement channels, from voice-based onboarding calls to real-time session recommendations.
One of the strongest themes across all three panelists was that agentic AI should augment your best people, not replace them.
Maanas framed it as creating AI-native employees within your event team. The goal is to use AI to bring people closer to data, to augment their ability to process RFPs, create content, and manage relationships, and to extend their reach so that follow-up happens outside of working hours without anyone staying late.
Asghar Maqsood from Terrapinn has taken this philosophy and operationalized it. At Terrapinn, AI agents are named, onboarded, trained on relevant data, and given clear objectives and KPIs, just like human employees. Agents named Reggie, Colin, and Tom are assigned specific tasks across the organization.
And just like human employees, they undergo quarterly performance reviews. If an agent is not meeting its objectives, it gets decommissioned. As Asghar explained, there have been cases where agents were doing interesting things but not hitting their core KPI, so Terrapinn decided to retire them and redirect resources toward agents that were delivering measurable results.
That discipline matters. It prevents the common trap of deploying AI for its own sake and ensures every agent is tied to a business outcome.
The most striking results shared during the webinar came from Terrapinn's deployment of AI agents for attendee acquisition via WhatsApp.
The process is straightforward but powerful. Terrapinn reaches out to previous attendees via WhatsApp, thanks them for attending last year, and asks whether they are interested in returning. If they are, they can register in a few taps without ever leaving the WhatsApp conversation. Behind the scenes, AI handles the conversation, answers questions about the agenda, sponsors, logistics, and even off-topic queries, and processes the registration automatically with no human intervention required.
The results speak for themselves. On some events, Terrapinn has acquired over 4,000 registrations through this single channel. On certain shows, WhatsApp and AI account for 15 per cent of total registrations. Across the portfolio, the average is 5 to 6 per cent of registrations coming through this route, and it is still growing.
What makes this especially valuable is that it represents a genuinely new acquisition channel. Traditional email is slowing down. Open rates are declining. WhatsApp, combined with AI-powered conversational registration, is opening a direct line to attendees that feels personal, is frictionless, and operates at a scale that would be impossible to manage manually.
Terrapinn runs over 90 events. Once the WhatsApp agent proved itself in a pilot, it was rolled out across the portfolio. That is the power of the agent model: prove it once, then scale it everywhere.
Max Gabriel from Markus AI shared a different but equally compelling use case focused on post-registration attendee onboarding.
After someone registers for an event, Markus AI contacts them two to three weeks before the event and conducts a one-on-one voice interview. The agent welcomes them, confirms their registration details, and asks a simple but powerful question: what are the top three things you want to get out of this event?
The team experimented with three formats. Video-based interviews were a disaster as the technology was not ready and people did not want to engage that way. Text-based chat was acceptable but suffered from low completion rates because attendees did not want to type out more information. Voice-based conversations were the breakthrough. Markus AI is seeing 60 to 70 per cent of attendees complete the interview voluntarily, with no training or incentive required.
The data this generates is transformational. For the first time, organizers can see written goals for every attendee at scale. They can understand why 4,000 people are coming to their event, not just that they registered. That intelligence feeds directly into matchmaking tools like Grip to improve meeting quality, into sponsor packages to demonstrate buyer intent, and into future programming decisions.
Max described people becoming genuinely reflective during these conversations, pausing mid-interview to say they had not actually thought about their goals before. That depth of engagement is something a registration form will never capture.
Post-event, the agent circles back and gives each attendee a snapshot: here is what you said you wanted to achieve, and here is what you actually did at the event. That closed loop creates a measurable value story that organizers can share with sponsors and use to drive rebooking.
Max introduced a mental model for categorizing AI agents that every event organizer should understand. He calls it Inside, Middle, and Edge.
Agents on the inside are the ones you deploy within your own organization to improve internal processes. Sales SDR agents, marketing automation agents, content creation agents, and registration acquisition agents like those Terrapinn is using all fall into this category. These are the lowest-risk, highest-learning-value experiments to run because they improve your value chain while building organizational muscle in working with AI.
Max's advice to the audience was direct: do this faster. Experiment even if experiments fail. Do not deploy too much capital, but continue running pilots because the value of your internal team learning how to work with agents is strategically critical.
Agents in the middle are where things get more strategic. These are agents that sit between you and your customer, potentially reshaping the discovery and engagement layer. Think of an agent that becomes the way attendees discover relevant sessions, exhibitors, or meetings, not through a traditional app or website, but through a conversational interface that understands their intent.
This is also where disintermediation risk lives. If you do not build agents in the middle, someone else might. Max pointed to Harvey AI in the legal industry as an example of a company inserting itself between data publishers and end users by building a more intelligent discovery layer.
Agents on the edge are the personal assistants that hyperscalers like Apple, Google, and Amazon are racing to build. These are the AI systems that live on the user's phone and help them navigate their entire digital life. Event organizers cannot compete here, but they need to be aware of it. If a sponsor's procurement agent is scanning the market for the best events to attend, your event data and your agents need to be visible to that system. The events that are structured, data-rich, and agent-accessible will be the ones that surface in those results.
One of the most urgent points raised during the webinar was the speed at which sponsors and exhibitors are building their own AI agents.
Max was blunt about this. Every one of your sponsors has access to the same AI tools you do. They are not sitting around waiting. Large companies are already investing in agents that calculate ROI across their event portfolio, determine which events to attend, and plan their engagement strategy autonomously.
That means sponsors are starting to ask different questions. Instead of visiting 25 event websites and renewing based on habit, they are building agents that evaluate which events deliver the best return and recommend where to allocate budget.
If your event data is not structured, your outcomes are not measurable, and your digital presence is not agent-readable, you risk being invisible to the systems that are increasingly making these decisions.
The implication for organizers is clear. You need to own the AI layer around your event before someone else does. That means building agents that add value across the attendee and sponsor journey, not waiting for a third party to insert themselves in the middle.
Asghar reinforced this with what he called the death of hope-based networking. The old model of putting people in a room and hoping they connect is ending. AI enables organizers to understand intent before the event, facilitate targeted connections during it, and measure the value of those connections afterward. That is a fundamentally more valuable proposition for sponsors, and the organizers who deliver it will have a significant competitive advantage. For more on this, see Grip's AI-powered matchmaking in action.
Despite the urgency around AI adoption, the panel was unanimously optimistic about the future of in-person events.
Maanas cited investor Mark Cuban's characterization of events as a sunrise industry. The logic is compelling. As AI makes digital channels like email and LinkedIn increasingly noisy and untrustworthy, the value of genuine, face-to-face connection goes up. More marketing spend will flow toward in-person events because they offer something no digital channel can replicate: verified human interaction.
The numbers support this. Conservative estimates suggest the events industry will double in the next decade. More bullish projections suggest it could triple. Asghar confirmed that Terrapinn is seeing attendance figures rise, not fall, as AI becomes more prevalent.
But growth creates its own challenge. If the industry doubles, organizers need scalable infrastructure and playbooks to launch events in new geographies and new verticals efficiently. That is exactly where agentic AI becomes transformational. It provides the operational leverage to scale without proportionally scaling headcount.
The organizers who build that infrastructure now will be the ones best positioned to capture the growth. Those who wait will find themselves trying to scale with manual processes while competitors move faster with fewer people.
The panelists were asked what an organizer who is doing nothing with agentic AI today should do in the next 90 days. Their advice was practical and consistent.
First, form a small team. You do not need a large AI department. You need a few curious, committed people who are willing to experiment.
Second, pick one event. Do not try to roll out AI across your entire portfolio at once. Choose a single event where you can test a specific hypothesis, whether that is improving registration conversion, enriching attendee intent data, or automating sponsor follow-up.
Third, partner rather than build from scratch. There are companies like Bridged, Markus AI, and Grip that have already built the infrastructure. You do not need to reinvent the wheel. Many offer flexible commitments with no long-term lock-in, so you can walk away if the experiment does not deliver.
Fourth, define a clear KPI before you start. Asghar was emphatic about this. Every agent at Terrapinn has a specific objective it needs to hit. If it does not hit it, it gets reviewed and potentially decommissioned. That discipline prevents AI experimentation from becoming an unfocused cost center.
Fifth, accept that some experiments will fail. Terrapinn made over 1,000 AI-powered phone calls to acquire attendees and generated only 12 registrations. That experiment failed by any measure. But the learning it produced informed the next experiment, which succeeded. Failure is part of the process.
And sixth, move quickly. As Asghar put it, in the AI world, 90 days is a long time. The tools are evolving fast, the competitive landscape is shifting, and the organizers who start experimenting now will have a compounding advantage over those who wait.
Watch the full discussion with Asghar Maqsood, Max Gabriel, and Maanas Mediratta for deeper insights, live demos, and audience Q&A.
See how Grip's AI-powered platform helps commercial event organizers drive better attendee connections, deliver measurable sponsor ROI, and scale their events portfolio. Book a free demo today.
Agentic AI refers to AI systems that can autonomously sense data, plan actions, execute tasks, and learn from results with minimal human oversight. In the events industry, this means AI agents that can handle multi-step workflows like attendee acquisition, personalized outreach, meeting scheduling, and post-event follow-up, operating around the clock across an entire event portfolio.
Generative AI tools like ChatGPT respond to individual prompts and produce content on demand. Agentic AI goes further by taking autonomous action across multiple systems. An agentic system can read your CRM data, send a personalized WhatsApp message to a past attendee, process their registration response, and update your database, all without a human needing to intervene at each step.
Terrapinn has acquired over 4,000 registrations through WhatsApp-based AI agents on some events, with AI-driven channels contributing up to 15 per cent of total registrations. Markus AI is seeing 60 to 70 per cent of attendees voluntarily complete voice-based pre-event interviews, generating intent data that organizers have never had access to before. Bridged reports that events using their platform have seen sponsor renewal rates double and the number of touchpoints needed to convert attendees cut significantly.
SPAR stands for Sense, Plan, Act, and React. It describes the four capabilities of an agentic AI system. Sensing means reading data signals like email opens, CRM records, and website behavior. Planning means determining which tools and systems to use. Acting means executing workflows and triggering processes. Reacting means learning from outcomes and adapting future behavior. The framework was introduced during the webinar by Maanas Mediratta of Bridged.
No. Every panelist agreed that AI agents should augment human teams, not replace them. The goal is to create AI-native employees who are brought closer to data, can operate at greater scale, and are freed from repetitive tasks to focus on strategy, relationships, and creative work. Terrapinn names its agents, onboards them with training data, and reviews their performance quarterly, treating them as extensions of the team rather than replacements.
Start small. Form a focused team, pick one event, define a clear KPI, and partner with an AI platform rather than building from scratch. Run a pilot, measure the results, and scale only what works. The panelists recommended a 90-day sprint to test a single use case, such as AI-powered registration acquisition or pre-event attendee onboarding, and to accept that some experiments will fail while generating valuable learning.
The biggest risk is disruption. Sponsors and exhibitors are already building AI agents that evaluate event ROI and recommend where to allocate budget. If your event is not structured, measurable, and digitally accessible to these systems, you risk being bypassed. As Maanas summarized during the webinar: AI is not going to replace you, but someone who is using AI better than you might.
