What it is
Callan Consulting, a B2B technology product-marketing consultancy that also sells an AI enablement service. A follow-on to its 2024 study.
The interviews ran 30 to 60 minutes each with leaders recruited from the consultancy’s network, at companies from under $5M to over $8B in revenue. Two-thirds now report a strong impact on the department, up from a third in 2024, and half say they have significantly overhauled how the function works. Customer-facing content, market research and sales enablement lead the use cases.
Every interviewee is confident AI is delivering value, and none can point to a standard measure that isolates its contribution. Most estimate they do the same work with 20% to 50% fewer people, though none said they let people go. Only four of the eighteen who answered that question had brought AI agents into their marketing. About half had started work on being found by AI answer engines, most of it in the previous six months.
What marketing teams should take from it
- It describes wider use of AI in workflows without an agreed way to isolate what AI contributed, the gap the four chapters measure.
- Its rule for content is worth borrowing: keep foundational assets such as messaging platforms human-written, and use AI with cross-checks for derivative work.
- Expectations rather than mandates drove adoption in these teams, with AI built into goals and objectives, which is close to what finding 04.1 recommends.
- Nineteen interviews describe how peers talk; they do not count how many do what.
Where to start
Read it for the texture of how peers describe the change, then use the “none can isolate the contribution” finding to set a measurement rule before the next budget cycle rather than after.
Ask whether your own effort to be cited by ChatGPT and the other AI answer tools exists at all. Half of these peers had one, most of it under six months old.
Keep in mind
Qualitative, recruited from a consultancy’s own network, with benefit figures that are self-reported estimates.