09.01.2026
We Asked a Room of Technology Leaders Where to Start With AI. They Wanted to Talk About People.
6 key takeaways that we heard during lunch
The short version: Digital Intake, the point where information first enters your business, is the easiest and most important first step toward AI enablement. We hosted a lunch to discuss this. The room agreed, then gave us six better reasons for this than the one we walked in with.
Earlier this month we invited a group of senior technology leaders to lunch in Calgary. They came from across industries, each of them responsible for the information their organization depends on.
The premise for the event? AI is only as reliable as the information it can access, and many organizations have not done the foundational work of making their information trustworthy. “Digital Intake”, or standardizing what happens the moment information arrives in the organization, is where that work begins.
Nobody argued with the premise, but twenty minutes into the discussion, when WCD’s Director of Digital Transformation and Innovation, Matt Christensen, opened the floor with what we thought was a technology question asking, “What does the first mile look like in your business,” the answer was not about documents.

The first mile challenge is really around the culture shift and the change management. We talk a lot about AI, but I truly don't think leaders understand what that really means."
And the conversation never really went back. Over the next hour, a table of people who manage information for a living kept returning to the same place. The hard part is not the technology.
What they described, without ever using our language for it, was a very good case for starting at intake.
1. A process that works is not the same as a process that sticks
The best story of the afternoon came early. During COVID, when everyone was sent home, one organization ran a beta of a digital mailroom. Everything was scanned. It worked. Until people came back to the office.

What happened is when we started coming back to the office, the process broke because people got involved. And so, we had to resort back to the way we used to do things. It wasn't a culture shift happening."
The technology did not fail. The business case did not fail. The process reverted the moment the external pressure that created it disappeared, because it had been adopted under duress rather than designed to last.
A workaround survives exactly as long as the crisis that created it. An intake process has ownership, rules, and visibility, which is what lets it hold when the pressure comes off.
KEY TAKEAWAY: If a process only exists because circumstances forced it, expect to lose it. Design digital intake as a standing process, not a workaround.

2. Build momentum by starting where people aren’t threatened
If culture is the constraint, the practical question becomes where you can begin without triggering it. One attendee answered that better than we do in our own materials, then came back to it, unprompted, forty minutes later.

The intake centre or the mailroom is like a gateway drug for AI. I can see it being a non-threatening way for business leaders to introduce AI processes. It's low risk. It's a great way to get the ball rolling. You get the organization consuming it, normalizing it, beginning to use it and leveraging it. Where it goes from there, those are internal decisions."
This is the argument we came to make, put more plainly than we usually put it. Nobody feels endangered by better mail routing. The process work is close to identical to what you would do in a higher-stakes department, the risk is a fraction of it, and you finish with a working example and a real business case instead of a slide deck.
Our CEO, Karen Brookman, made the same point from the other direction. Traditional back-office functions like mailrooms, may seem mundane, but they offer a practical, low-risk opportunity to demonstrate the value of AI-enabled digital intake.
KEY TAKEAWAY: Digital intake is the lowest-threat place in the business to do real process work. The same discipline as a high-stakes department, a fraction of the risk, and a proof point you can carry anywhere else.
3. Everyone has an AI initiative. Far fewer have AI in production.
David VanDerEems, WCD’s Senior Consultant on enterprise transformation, described a CIO conference where the room was asked who had an AI initiative planned for 2026. Effectively every hand went up. Asked who had an AI process actually running in production, he counted perhaps ten or fifteen.
That gap was recognizable to everyone at the table. It is the same energy Karen hears from customers who tell her they have a hundred AI initiatives underway and no idea which one to finish.
What closes the gap is almost never the model. It is the state of the information underneath it, and that state is decided at the point of capture.
KEY TAKEAWAY: Digital Intake isn’t a later step in your AI journey, it is part of the foundation that determines whether AI can succeed.

4. The resistance does not start with the business
The most uncomfortable story of the day is worth sitting with.
One attendee had a ~500-page training document, scanned as a PDF, and wanted to make it useful. They loaded it into their AI platform and asked it to act as a document analyst they could put questions to.
It hallucinated. Repeatedly.

One of the pushbacks that I got from one of my colleagues is that it's hallucinating, you're wasting my time, you're wasting my efforts. Stop using AI."
That pushback did not come from a skeptical business unit. It came from inside their own technical team. So the question they put to the room was if IT resists, what happens when we take it to the broader business? The answer from across the table was blunt and, we think, correct.

People view IT or IT teams as really advanced and technology-embracing people, but they're not. People are people, and they like to stay in their worlds and do what they do."
There is a second lesson buried in that story, and it is the reason we host these conversations. The model did not fail because it was a bad model. It failed because it was handed 500 pages of unstructured scans and asked to be precise. Nobody had ever decided what that document was, what was in it, or how it should be described.
That is not an AI problem. That is an intake problem.
KEY TAKEAWAY: When AI hallucinates on your own documents, the problem almost always arrived before the model did. Fix what happens as the information arrives in your organization and most of the trust problem goes with it.
5. It's difficult to explain an AI decision to a regulator
The sharpest exchange of the afternoon lasted about fifteen seconds.
Someone raised the obvious problem for regulated industries. Regulators audit your decisions. They ask you to show every step of your reasoning. And increasingly, a meaningful part of that reasoning is "the AI surfaced this."
"So, justify that. Explain that."
From across the table, without hesitation:
"And you can't."
Nobody in the room had a better answer. The consensus was only that this is coming, that it may end up being settled in courts, and that most organizations are not ready for the question.

This is what digital intake is built for, and it is the part most easily overlooked. An auditable process, and a documented chain from where a document arrived, to how it was classified, to what was done with it. You are still moving toward AI. You can just show your work.
Karen made the broader observation, and it may have been the smartest thing said all afternoon. Records management already solved this. Information governance has proven processes, and those processes gave people the confidence to say no to bad ideas. AI disrupted all of it and replaced it with experimentation. The answer is not to slow the experimentation down; it is to rebuild the governance underneath it.
KEY TAKEAWAY: Defensibility is coming, and it gets built at intake. A documented chain from arrival, to classification, to action is what lets you show your work later.
6. Use the enthusiasm for AI to get the unglamorous work done
Every other guest treated culture as the obstacle. One had inverted it, and this was the most practical thing we heard all day.
Their organization asked each department to identify a use case where an AI agent could take over a taxing manual process. Departments got excited. Then they discovered that the information feeding those workflows was not standardized, and the agents could not work.

It was this beautiful opportunity to go back and reinforce the necessity for foundations and create some standardization and structure. Because they wanted so badly for these workflows to work, we had their buy-in. We have a captive audience here."
The foundations they went back to build are intake foundations. Consistent capture, agreed metadata, a standard shape for information arriving from a dozen different directions.
Nobody gets excited about that work on its own merits. Everybody wants an AI agent.
Key Takeaway: Use the appetite for the agent to build the intake foundations the agent depends on. Let them chase the agent and let the foundations get built on the way there.
What are we taking from the day?
Besides the honour and privilege of sitting in a room with incredibly smart and collaborative leaders, we went in to talk about information quality and came out with a sharper version of our own argument.
The reason to start with digital intake is not only that it produces cleaner data for AI, though that remains true. It is that digital intake is the one place in the organization where you can do serious process work, build an auditable foundation, and prove the value, without anyone feeling their job is on the table.
Culture is the constraint. Digital intake is the place it bends.



