AI has moved from an interesting initiative to a standing board topic. CMOs are increasingly asked, directly, what marketing is doing with AI, what it is costing, and what it is producing. A one-off enthusiastic update is no longer sufficient. Boards want a consistent answer they can track over time.
Open Future Forum's CMO AI Leverage research and our broader CEO AI Leverage research both point to the same gap: executives are confident AI matters, and far less confident they can explain its return in terms a board will accept.
What are we spending on marketing AI?
Start with total AI-related spending across tools, licenses, vendors and internal build cost. Compare that spending to budget and to the prior period. A number without context, such as “we spent $400,000 on AI tools,” is not useful on its own. The board needs to know whether that is more or less than planned, and what it bought.
Where is AI actually changing marketing work?
Name the specific workflows where AI is genuinely changing how work gets done: content production, campaign analysis, personalization, sales enablement, customer research. Vague statements such as “AI is being used across the team” are not informative. Specific workflow examples are.
What productivity has been created?
Where time savings have been measured, report them with a baseline: what a workflow took before, what it takes now, and how many people or how much volume that applies to. Avoid presenting productivity gains as financial results. They are an input to financial results, not the same thing.
See how CMOs should measure AI ROI for the distinction between productivity and return in more depth.
Where is the economic return?
This is usually the hardest question and the one boards care about most. Connect AI activity to cost avoided, revenue influenced or capacity redeployed, measured against a comparable baseline rather than asserted as a percentage improvement.
Where a clean revenue number is not yet available, say so directly and describe what is being done to get one. “We do not have a clean attribution number yet; here is our plan to build one over the next two quarters” is a stronger answer than a confident figure that cannot survive scrutiny.
Is AI changing the marketing organization?
Report on hiring plans, agency spending and team structure. If AI has allowed the company to avoid planned hires, reduce agency scope or restructure how work gets done, say so specifically. See how AI is changing marketing team structure and headcount for the underlying dynamics driving this.
Is AI changing agency spending?
Report agency and outside-production spending by scope category, not as a single line. Execution-heavy scope is more likely to shift in-house; strategic and creative-direction scope is more likely to remain with outside partners. A board benefits from seeing which category is actually changing.
Is AI improving customer acquisition?
Where AI is used in acquisition, such as personalization, targeting or creative testing, report performance against a comparable baseline: conversion rate, cost per acquisition, or revenue per visitor before and after. Avoid crediting AI for acquisition results that are more plausibly explained by other changes, such as pricing, seasonality or product changes.
What customer and brand risks should the CMO surface?
Boards increasingly expect CMOs to proactively raise risk, not wait to be asked. Relevant risks include:
- Brand and reputational risk from AI-generated content that is inaccurate, off-brand or poorly reviewed
- Data privacy and customer data handling in AI tools, particularly personalization
- Disclosure and labeling obligations for AI-generated or AI-assisted content, where applicable
- Dependency risk from concentrating critical workflows in a small number of vendors
See the general counsel's role in AI governance for how legal and marketing should coordinate on these risks.
Should the board know which AI vendors marketing uses?
Increasingly, yes, at least at a summary level. Boards are asking about vendor concentration, data-sharing terms and contract exposure, particularly for tools that touch customer data or produce public-facing content. A brief vendor summary, updated periodically, is more useful than raising it only when something goes wrong.
What should the board actually see?
A consistent scorecard, repeated each quarter, is more useful to a board than a fresh narrative each time. A practical structure:
| Category | What to report |
|---|---|
| Investment | Total AI spending versus budget and prior period |
| Deployment | Which specific workflows are using AI, and how broadly |
| Productivity | Measured time or capacity change, with baselines |
| Economics | Cost avoided, revenue influenced or capacity redeployed |
| Risk | Brand, data, disclosure and vendor-concentration exposure |
| Next decision | What the company needs to decide or invest in next |
Using the same six categories every quarter lets a board see trend rather than a new story each time, which is what actually builds confidence in the CMO's judgment.
What should CMOs avoid reporting?
A few patterns undermine credibility with a board:
- Vague productivity claims without a stated baseline
- Revenue attributed to AI without a comparable control
- Tool adoption counts presented as business results
- Enthusiasm substituted for evidence
- A new framework or metric introduced every quarter, making trend impossible to see
Boards notice when numbers do not hold up under a second question. It is better to report less and have it be defensible than to report more and have it collapse under scrutiny.
How often should CMOs report AI progress?
Quarterly, aligned with existing board cadence, is generally sufficient for most companies. More frequent updates are reasonable during a major deployment or when a significant risk has emerged. What matters more than frequency is consistency: using the same scorecard each time so the board can track change rather than absorb a new structure every meeting.
What questions should CEOs ask CMOs about AI?
A CEO preparing for this conversation can use the same structure in reverse:
- What are we spending, and how does that compare to plan?
- Where is AI actually changing how marketing work gets done?
- What have we measured, and what is the baseline?
- Where is the economic return, and where are we still uncertain?
- What has changed in the organization, hiring plan or agency spending?
- What is the next decision we need to make?
A CMO who can answer all six clearly, including the ones without a fully satisfying answer yet, is demonstrating exactly the kind of judgment a board is trying to evaluate.
The CMO's job is translation
Boards do not need to understand every AI tool marketing uses. They need to understand what changed, what it cost, what it returned and what risk it introduced. The CMO's job in this conversation is translation: turning marketing activity into terms a board can evaluate and trust over time.
Last updated: September 28, 2026
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Open Future Forum publishes original research examining enterprise AI from different executive perspectives, including the CMO AI Leverage Report, CFO AI Leverage Report, CEO AI Leverage Report, CISO AI Leverage Report and broader executive AI research. Individual research findings should be read alongside the methodology and sample described in the underlying Open Future Forum reports.
To go deeper:
- Read how CMOs should measure AI ROI
- See how AI is changing marketing team structure and headcount
- Explore the CEO AI Leverage Report
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CMOs compare notes on board reporting, AI risk and executive alignment off the record at Open Future Forum's private gatherings.