Forrester published a blog post this week that is worth reading carefully. The argument, made by Principal Analyst Conrad Mills, is that the bottleneck in AI adoption for events has shifted. It is no longer a question of whether the technology is good enough. The tools exist. The use cases are proven. The problem, Forrester argues, is leadership.
I shared the piece with the Event Tech Founders Forum, a group of 200 event technology founders I run, and asked a direct question: are your customers coming to you with a clear AI strategy, or are they still asking you to tell them what is possible?
The responses came quickly, and they painted a picture that goes considerably further than the Forrester analysis. What is happening out there is not just a strategy gap. It is a governance crisis dressed up as a technology question.
The Gap Between Policy and Strategy
Dahlia El Gazzar, founder of DAHLIA+Agency, was direct about what she sees on the ground. “Many clients do not have a clear AI strategy,” she said. “They have AI policies that they put together from ChatGPT or Claude.”
The distinction matters enormously. A policy is a set of rules about what staff can and cannot do with AI tools. A strategy is a considered view of where AI can create value, how it should be resourced, governed, and measured, and what success looks like. One is defensive. The other is directional.
“The events teams and marketing teams are not abiding by the policies because they were usually written by someone in IT who does not know the real pressures of managing events.” — Dahlia El Gazzar, DAHLIA+Agency
The result is predictable. Staff revert to using personal LLM accounts, bypassing whatever official tool the organisation mandated. The policy exists on paper. The behaviour it was designed to govern carries on regardless, just outside the firewall.
El Gazzar has been working to address this directly, educating leadership on why they need an AI strategy, governance structures, and continued staff education as a package. Not a product decision. A cultural and organisational one.
This aligns squarely with Forrester’s data. Their research shows that 63% of event leaders identify data quality and structure as a significant challenge. That number makes more sense when you understand the context: if teams are operating fragmented AI workflows across personal accounts, the data hygiene that underpins any serious AI capability is never going to exist.
Vendors Are Doing the Strategy Work Their Clients Should Be Doing
Tom Gavazzi from Woom described a pattern that will be familiar to anyone selling into the events market right now. “People usually come with questions about what AI can do, typically focused on solving one or two specific problems,” he said. “Then it becomes our role to provide a kind of education and show them everything they can do with AI: what the possibilities are, what the costs look like, what the ROI and benefits can be.”
Read that back. A technology vendor is having to construct the strategic vision their client should have arrived with. This is not a criticism of vendors. Many are doing this extraordinarily well. But it points to a structural problem in how organisations are approaching AI adoption.
If the vendor is defining the strategy, the client is outsourcing one of the most consequential decisions they face. They end up with a solution shaped by what the vendor sells, rather than a solution shaped by what the business actually needs.
Tom also made a point that deserves its own conversation: event organisers need to be clear about what they want to use AI for and through which channels, because the use cases for internal efficiency and for external audience communication are fundamentally different. “The organiser needs to know which problem they want to solve first,” he said, “and based on that, the appropriate AI capabilities can then be structured to address the specific challenges they face.”
That framing is useful. AI for operational efficiency — scheduling, content repurposing, brief generation, data analysis — requires a different set of tools, integrations, and governance than AI deployed in the attendee experience. Conflating them produces neither well.
Two Types of AI Adoption That Organisations Are Confusing
Adam Price, who works with HubSpot in a growth architecture capacity, made a distinction that I think is underappreciated in most discussions about AI strategy. “It is definitely important to distinguish between deploying AI tools as part of your offering versus using AI tools internally,” he said. “Two very different internal processes.”
This is a point that applies to event technology vendors and event organisers alike. For a vendor, building AI into the product is a product decision with implications for engineering, data privacy, liability, and customer expectation. Using AI internally to speed up marketing, support, or operations is an entirely separate matter with its own governance requirements.
For an event organiser, the equivalent distinction is between AI that touches the attendee experience directly, think personalised session recommendations, AI-generated networking prompts, real-time translation, and AI that works behind the scenes to make the team more efficient. Both are valuable. Both carry different risk profiles. And both require different conversations with leadership.
The organisations getting this right are the ones that have separated these two conversations rather than running them together as a single “AI strategy” discussion.
The Agentic Question Nobody Is Ready For
The most forward-looking contribution to the conversation came again from Tom, who introduced the concept of AI agents as the next layer of complexity. He shared a reference to Infobip’s AgentOS platform, which positions AI agents as orchestrators of both internal and external communications, and posed a question that I suspect most event marketers have not seriously considered yet.
“How do you envision a specific event appearing directly in a personal AI agent and having it complete the ticket purchase on behalf of the attendee? What new knowledge in marketing and sales will you need to have?” — Tom Gavazzi, Woom
This is not a hypothetical for 2030. The infrastructure Tom is describing exists today. AI agents that can browse, evaluate, and transact on behalf of users are already in deployment in other sectors. The question for events is not whether this will happen but how soon, and whether organisers will be positioned to reach an audience that increasingly delegates discovery and purchase decisions to AI systems acting on their behalf.
If an attendee’s AI agent is filtering and selecting events based on parameters the attendee has set, the entire model of event marketing changes. Search engine optimisation gives way to something closer to AI discoverability. The metrics that matter shift. The data you need to expose, structure, and publish about your event becomes a different set entirely.
This is a leadership question. It is not something a technology team can answer on its own.
What Forrester Gets Right, and Where It Stops Short
Forrester’s data provides a useful structural frame. Their finding that 60% of organisations report flat or declining event budgets while 71% expect costs to increase captures the pressure that makes this conversation urgent. The squeeze is real, and it is not easing.
Their point that two-thirds of B2B buyers are now Gen Z or Millennials, and that more than half of marketers find building interactive experiences difficult, reflects an audience expectation gap that is widening faster than most teams can respond.
Where the Forrester framing is perhaps too clean is in its suggestion that the solution is for leaders to step up and define their AI vision. That is true, but it assumes that leaders have the context to do so. What the conversation in our founders group revealed is that the problem is more embedded than that.
Leaders are receiving AI strategy advice from IT departments that do not understand event operations. They are being sold AI visions by vendors whose commercial interest shapes the scope of that vision. Their teams are already using AI tools informally, generating data and workflows that exist entirely outside governance structures. The strategy gap is real, but it sits inside a larger deficit of cross-functional understanding.
The event technology vendors who are thriving in this environment are not just the ones with the best product. They are the ones that have recognised their role has expanded. They are now educators, strategists, and translators between what AI can do and what an event business actually needs. That is a different commercial proposition from selling software.
The Question Worth Asking
If you are an event organiser reading this, the question is not which AI tools you are using. It is whether the decisions about those tools are being made by people who understand the full commercial, operational, and audience context of what you are trying to achieve.
If you are an event technology vendor, the question is whether you are genuinely helping clients build that understanding, or whether you are filling the strategy gap in a way that serves your roadmap more than their business.
Forrester is right that this has become a leadership issue. What the founders in our group made clear is that it has also become an industry literacy issue. And those are not the same problem.
Responses quoted in this article were shared by participants in the Event Tech Founders Forum, a private group of event technology founders. Quotes have been lightly edited for clarity and length.
Source: Forrester, Why An AI Event Strategy Is Becoming A Leadership Issue, Not A Technology One, March 2026.
