Strategy
Peter Micciche
Peter Micciche • July 30, 2026
By Peter Micciche, CEO, CertainTL;DR (the short answer)
You don’t have to be fully AI-ready to get value from AI this quarter.
Readiness is a ladder, not a gate.
The cleanest input an agentic system can act on is already being produced at the events you run: first-party, declared answers from verified buyers who chose to give you their time.
The move is to stop waiting for the whole stack.
Pick the one rung that closes your most expensive gap.
Climb it with data you already own.
Your AI budget is approved.
Your program is probably still waiting on a readiness that never quite arrives.
You’re not alone in that.
Revenue teams are funding orchestration layers and autonomous agents at a pace that would have surprised most of us two years ago.
A great many of those same programs are stuck behind a condition that keeps drifting into the next quarter.
The data has to be cleaned.
The team has to be trained.
The work meant to improve results sits in a queue.
Here’s the part that changes the math. The data an agentic stack needs to do something useful with this quarter is not sitting inside a future migration. A meaningful share of it is already being produced inside the events you run right now. Prospects who chose to give you dedicated time produce that meaningful share.
Do you have to be AI-ready before you can put AI to work?
No.
Readiness is not a gate you pass through all at once.
Treating readiness as a gate is what keeps AI programs stuck in planning.
The teams making real progress pick one source of clean, high-intent data.
The teams making real progress put that data to work this quarter.
Everyone else waits for the full rollout to be finished.
The scale of the commitment isn’t in question. Gartner’s 2026 research shows chief marketing officers allocating an average of 15.3% of their budgets to AI. The same research shows 70% calling the goal of becoming an AI leader critical to the organization.
The figure that causes headaches in the C-suite comes from the same research. Only 30% describe their AI capabilities as mature. That number gets read as a reason to second-guess the AI budget. Read the number the other way. Only 30% describing AI capabilities as mature is a normal starting condition. Only 30% describing AI capabilities as mature is not a disqualification. The teams pulling ahead treat it that way. Those teams clean, high-intent data source. Those teams put the cleaned data source to work while everyone else is still planning the full rollout.
Why are events the best first-party data source for an AI stack?
Events produce first-party, behavioral data from a verified buyer.
The verified buyer chose to spend real time with you.
This data is close to a perfect description of what an agentic system is built to act on.
You generate this data every time you open the doors.
Unlike third-party intent or cookie data, events produce a data source that needs no cleaning before your systems can use it.
Set events against the data most teams are waiting to repair. Third-party intent is softening as the models behind it lose resolution. Cookie-based identity keeps eroding under privacy changes that show no sign of reversing. Enrichment everyone buys from the same few providers produces outreach that converges on the same accounts. That outreach converges on the same messages because the underlying inputs are identical.
Against that backdrop, the answer a buyer gives at check-in is a signal. The pattern of three colleagues from one account arriving within minutes of each other is a signal. These signals need zero preparation.
The event professionals running these programs execute them extraordinarily well. The gap is in the direction they were handed. Most event programs were built to run logistics. Event logistics reduces event intelligence to a registration record and an attendance figure. Event logistics reaches the revenue team days later. That delay happens after the moment that produced the data has cooled.
Gartner finds that 77% of B2B buyers call their most recent purchase complex or difficult. A decision that hard turns on every clean signal a seller can get. The event produces one such clean signal. The event produces that clean signal mostly unused.
What are the four rungs of event AI readiness?
Event AI readiness climbs four rungs.
The rungs are logistics, capture, delivery, and orchestration.
Most programs stand on logistics.
Event logistics runs the event well.
Event logistics produces a list that reaches sales days later.
Each rung above logistics turns more of what the event already produces into intelligence your revenue systems can act on.
You’re rewarded for every step you take.
The first rung is logistics
The first rung is logistics.
The event runs well.
Registration is flawless.
A list lands in a spreadsheet.
Follow-up reaches sales some days later.
None of that signals a weak team.
It signals the rung where the event produces a debrief and not pipeline.
The second rung is capture
The second rung is capture.
Registration gets read at the account level instead of as a roster.
Asking a few structured questions at check-in turns the arrival into a record your systems and your reps can use.
The third rung is delivery
The third rung is delivery.
The signals reach the CRM and the account owner’s phone within seconds.
The signals reach those destinations instead of sitting in an export.
This timing allows the team to act while the buyer is still at the event.
The fourth rung is orchestration
The fourth rung is orchestration.
The signals trigger insight and action.
The pattern repeats across the whole event portfolio.
AI manages sorting at scale.
AI enables answering which formats and regions produce qualified pipeline.
You don’t have to reach the top to be rewarded for the climb. A team that does nothing this quarter beyond reading its registration data at the account level has already moved up a rung. That team will walk into its next event knowing which accounts sent a buying committee. That is a concrete gain. That gain is produced with data the team already owned. Which rung are you standing on right now?
How does event data protect your marketing budget?
Event data protects your budget by letting you describe events in the terms a budget review respects.
Those terms are cost per qualified opportunity, sourced pipeline, and revenue.
Those terms replace attendance counts.
When profits fall short, the channels that survive the cut are the ones that can show their contribution to business results. A program that climbs even two rungs can do this.
There’s a second cost to waiting. The second cost surfaces in the budget review. The Spring 2026 CMO Survey from Deloitte, Duke, and the AMA found that marketing gets cut 45% of the time profits fall short.
Events have struggled in that conversation for a long time. The same readiness reason described above applies. The intelligence that would let a CMO show cost per qualified opportunity by event type never reached the systems where the case gets made. That lack caused the defense to come down to attendance counts and anecdotes.
Climb even two rungs. Divide event spend by the opportunities it sourced instead of the registration count. That shift keeps the budget intact.
Where to start before the quarter ends
Stop waiting for the entire stack.
Choose one move you can make with the data you’ve already collected.
Pick the rung that closes your most expensive gap. If follow-up is slow, route event signals into the systems your team works in. Route event signals into those systems so signals arrive in hours instead of days. If the budget is hard to defend, consolidate your event data. Start measuring cost per qualified opportunity. If your reps walk into events without context, read registration at the account level. Give reps a brief before the doors open.
This capture and delivery work is the same as the badge table in what buying signals you can capture at event check-in. Run one of those moves. Measure the result against a single metric that matters.
None of this asks you to be AI-ready in the usual sense of the phrase. This approach asks you to see the cleanest first-party signal you’ve already produced at your events. This approach asks you to treat readiness as a ladder you can start climbing today. This approach does not require waiting.
The full version of this argument, with seven plays you can run this quarter and the metric that measures success, is in the Event Signal Playbook, free and ungated. It is the first of two parts. The first part shows the plays. The second part shows how to run those plays without stitching five tools together.
The agents your competitors are buying will keep improving. The agents your competitors are buying will keep resembling one another. The signal your events produce is the one input none of them can buy. How much longer will you wait to use it?
Frequently asked questions
Do you have to be AI-ready before you can put AI to work?
No.
Readiness is not a gate you pass through all at once.
Gartner finds only 30% of organizations describe their AI capabilities as mature.
Only 30% describing AI capabilities as mature is a normal starting condition rather than a disqualification.
The teams making progress pick one source of clean, high-intent data.
The teams making progress put that data to work this quarter.
Everyone else waits for the full rollout.
Why are events the best first-party data source for an AI stack?
Events produce first-party, behavioral data from a verified buyer.
The verified buyer chose to spend time with you.
This buyer data is close to a perfect description of what an agentic system is built to act on.
Unlike third-party intent or cookie-based identity, a buyer’s answer at check-in and the pattern of three colleagues arriving together need no cleaning. No cleaning is required before your systems can use those signals.
What are the four rungs of event AI readiness?
Logistics, capture, delivery, and orchestration.
Logistics runs the event and produces a list.
Capture reads registration at the account level and asks structured questions at check-in.
Delivery routes those signals into the CRM in seconds.
Orchestration repeats the pattern across the whole event portfolio.
Orchestration enables AI to sort the signals at scale.
How does event data protect your marketing budget?
The Spring 2026 CMO Survey from Deloitte, Duke, and the AMA found that marketing gets cut 45% of the time profits fall short.
The channels that survive describe their contribution in business results.
A program that climbs even two rungs can divide its spend by the opportunities it sourced instead of a registration count.
That spend division keeps the budget intact.
Author note
Peter Micciche is CEO of Certain, the AI-powered Event Intelligence platform for enterprise B2B companies.
Connect with Peter on LinkedIn or visit certain.com to learn more about turning events into revenue.