Strategy
Peter Micciche
July 30, 2026
By Peter Micciche, CEO, Certain
TL;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.
The input is 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.
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 the data is already being produced inside the events you run right now.
Prospects produce the data by choosing to give dedicated time.
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 like a gate keeps AI programs stuck in planning.
The teams making real progress pick one source of clean, high-intent data.
The teams put that data to work this quarter.
The teams put the data to work while 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 research also 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 figure the other way.
It’s a normal starting condition, not a disqualification.
The teams pulling ahead treat the figure as a normal starting condition.
The teams choose one clean, high-intent data source.
The teams put the data 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 who chose to spend real time with you.
That data is close to a perfect description of what an agentic system is built to act on.
You generate the data every time you open the doors.
Unlike third-party intent or cookie data, the data needs no cleaning before your systems can use it.
Set that 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.
The enrichment everyone buys from the same few providers produces outreach that converges on the same accounts with the same messages.
The convergence happens because the underlying inputs are identical.
Against that backdrop, events produce signals that need zero preparation.
The answer a buyer gives at check-in is a signal that needs zero preparation.
The pattern of three colleagues from one account arriving within minutes of each other is a signal that needs 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.
The logistics focus reduces intelligence the event produces.
The reduction turns the intelligence into a registration record and an attendance figure.
The revenue team receives the registration and attendance after the moment the event produced them 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 a clean signal that mostly goes unused.
What are the four rungs of event AI readiness?
Event AI readiness climbs four rungs: logistics, capture, delivery, and orchestration.
Most programs stand on the first rung.
The event runs well on the first rung.
A list reaches sales days later on the first rung.
Each rung above 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 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’s simply the rung where the event produces a debrief and not pipeline.
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.
Delivery routes those signals to the CRM and the account owner’s phone within seconds rather than sitting in an export.
The routing lets the team act while the buyer is still at the event.
The fourth rung is orchestration.
Orchestration triggers insight and action.
The pattern repeats across the whole event portfolio.
AI manages the sorting at scale.
Orchestration enables answering which formats and regions produce qualified pipeline.
You don’t have to reach the top.
A team that does nothing this quarter beyond reading its registration data at the account level has already moved up a rung.
The team walks into its next event knowing which accounts sent a buying committee.
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.
The alternative is 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 protect the budget.
There’s a second cost to the waiting.
The budget review surfaces the second cost.
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 readiness reason comes from the same readiness described above.
The intelligence that would let a CMO show cost per qualified opportunity by event type never reached the systems where the case gets made.
The defense came 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.
The routing makes 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 is the same capture and delivery work I laid out for the badge table.
Run the move described in: what buying signals you can capture at event check-in.
Measure the move against a single metric that matters.
None of this asks you to be AI-ready in the usual sense.
It asks you to see the cleanest first-party signal you’ve already produced at your events.
It asks you to treat readiness as a ladder you can start climbing today.
You can start climbing without waiting.
The full version of this argument
The full version includes seven plays you can run this quarter.
The full version includes the metric that measures success.
The full version is in the Event Signal Playbook.
The playbook is free and ungated.
It is the first of two parts.
The first part shows the plays.
The second part shows how to run them without stitching five tools together.
The agents your competitors are buying will keep improving.
Competitors’ agents will keep resembling one another.
The signal your events produce is the one input none of them can buy.
The question becomes how much longer you will 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.
That starting condition is normal rather than a disqualification.
The teams making progress pick one source of clean, high-intent data.
The teams put the 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 who chose to spend time with you.
That 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 needs no cleaning.
The pattern of three colleagues arriving together needs no cleaning.
Your systems can use the signals without cleaning.
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 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 approach keeps the budget intact.
Byline
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.