Gartner estimates only about 130 of the thousands of agentic AI vendors are real. Your marketing automation platform vendor just announced “agents.” Which camp are they in? This buyer’s checklist for marketing automation platforms adding agentic features gives you the questions to ask before renewal, so you pay for autonomy you can verify and not for a rebrand.
Agent washing is the default, not the exception
Every major suite now ships something called an agent. Some are genuine. Many are the same drag-and-drop workflow with a chat box on top.
Gartner’s June 2025 prediction is blunt. Gartner expects over 40% of agentic AI projects to be canceled by the end of 2027, citing escalating costs, unclear business value or inadequate risk controls. The same release says vendors contribute to the hype through “agent washing,” which means rebranding assistants, RPA and chatbots without substantial agentic capability.
Gartner’s warning is not that agents fail. It is that buyers fund them without a defined outcome, a cost ceiling or a risk control, and then cancel.
The market is not shrinking, though. The market is not shrinking, though, and Gartner projects that 33% of enterprise software applications will include agentic AI by 2028. You will be sold agents whether you want them or not. The job is to decide which ones earn a place in your stack.
What “agentic” should mean in a demo
Scripted automation follows a path you drew. An agent chooses its own path toward a goal you set. That distinction is the whole test.
Ask the vendor to run three things live, on your data, not a sandbox:
- Goal in, plan out. Give it an objective (re-engage lapsed trial users) and watch it propose segments, channels and sequencing without a prebuilt journey.
- Mid-flight adaptation. Change a condition, such as a suppression list update, and see whether the agent revises its plan or simply fails.
- Visible reasoning. You should be able to read why it took each action, in plain language, in a log you can export.
If the demo only works when the presenter clicks through a template, you have bought automation with a new label. That may still be useful. It should not be priced like an agent.
The 2027 buyer’s checklist
Use this as a scoring sheet. Anything the vendor cannot answer in writing is a zero.
1. Pricing: who carries the risk?
Agent pricing is moving fast, and it is the clearest signal of vendor confidence. HubSpot moved two Breeze agents to outcome-based pricing effective April 14, 2026. Per MarTech’s coverage of the change, the Customer Agent moved from $1.00 per conversation to $0.50 per resolved conversation, and the Prospecting Agent moved to $1 per lead for outreach. HubSpot says, as reported by MarTech, that the Customer Agent resolves 65% of conversations, a vendor figure you should test against your own tickets.
That model shifts risk toward the seller. Still, outcome pricing hides a trap: who defines “resolved” or “qualified”? Get the definition in the contract. Then ask these questions of every vendor:
- Is billing per action, per outcome or per seat?
- Is there a hard monthly spend cap that stops the agent, not just an alert?
- Do retries, failed runs and test runs count toward your bill?
2. Guardrails and approval gates
Would you let a new hire send to your entire database on day one? Of course not. Agents deserve the same onboarding.
Look for tiered autonomy. At the lowest level, the agent drafts and a human approves. At the next, it acts inside limits (audience size, frequency, discount ceiling). Full autonomy should be opt-in, per use case. Confirm you can set rules on send volume, offer value, brand voice and excluded segments, and that a single switch pauses every agent at once.
Ask what happens when the agent is uncertain. The right answer is escalation to a person. The wrong answer is a confident guess.
3. Data access, quality and ownership
An agent is only as good as the data it can reach. If your CRM has duplicate contacts and stale consent flags, the agent will scale those errors faster than any human could.
Before purchase, audit three things. First, which objects and fields the agent can read and write. Second, whether it respects consent and suppression in real time. Third, who owns the prompts, outputs and learned configurations if you leave. The same exit-term logic we cover in our guide to data ownership and exit terms applies here. If your lead qualification depends on the model, read how to pressure-test AI lead scoring accuracy as well.
4. Compliance and disclosure
When an agent writes and sends on your behalf, the legal exposure is still yours. That includes claims in copy, endorsement language and any content that touches creators or testimonials.
Ask whether the platform checks outbound content for required disclosures, and whether it keeps a record of what was sent and why. For campaigns involving creators, pair the suite with tooling that audits posts, such as the options in our review of disclosure verification tools. If agents will draft or negotiate creator terms, check the usage rights exposure before anything gets automated.
5. Measurement: can you prove the agent did it?
Vendors love to report “agent-influenced revenue.” Treat that phrase with suspicion. Influence is not lift.
Insist on a holdout. Run the agent against a control group that receives your standard workflow, then compare conversion, unsubscribe rate and cost per outcome. If the platform cannot support holdouts natively, you will need to build them with your analytics stack. Our incrementality testing breakdown shows what a credible design looks like.
Log the human hours saved too. Gartner’s own advice is to pursue agents only where they deliver clear value or ROI, so baseline your current time and cost per task before you switch anything on.
6. Integration and lock-in
Gartner notes that integrating agents into legacy systems can be technically complex and disruptive to workflows. Budget for that. Ask for the list of native connectors, the API limits that apply to agent calls, and whether agents built in the suite can run against tools outside it.
Then ask the uncomfortable question. If you cancel, what do you keep? Exportable logs, configurations and training data are worth negotiating now, while you still have leverage.
How to run the evaluation without a six-month pilot
Shortlist two vendors. Pick one bounded use case with a measurable outcome, such as lead follow-up or lapsed-customer win-back. Run a four to six week test with a spend cap, a human approval gate and a holdout group.
Score each vendor on the six areas above, weighting pricing risk and guardrails highest. Anything below a passing score on guardrails is disqualifying, regardless of how good the demo felt.
FAQs
What is the difference between marketing automation and agentic marketing automation?
Traditional automation executes a path you define: if a contact does X, send Y. Agentic features take a goal, decide the steps, act across channels and adjust based on results. In practice, many products sit in between, so test with a live scenario rather than relying on the label.
How do I spot agent washing?
Ask for a live demo on your data with a goal-based prompt, not a template. Request exportable reasoning logs and a description of what the agent does when it cannot complete a task. Gartner defines agent washing as rebranding assistants, RPA and chatbots without substantial agentic capabilities, so vendors that cannot show autonomous planning are likely in that group.
Should I choose outcome-based or usage-based pricing?
Outcome-based pricing lowers your risk if the outcome is defined tightly and is hard to game. Usage-based pricing can work for high-volume, low-risk tasks, but it needs a hard spend cap. Whichever you choose, get the definition of a billable event in the contract.
How much autonomy should I give an agent at first?
Start with draft-and-approve. Move to bounded autonomy once the agent has a track record against a holdout group, and keep limits on audience size, frequency and offer value. Reserve full autonomy for low-risk, reversible actions.
Who is liable when an agent sends non-compliant content?
Your brand is. Treat agent output like content from any employee or contractor, with review, disclosure checks and records of what was sent. Ask vendors what audit trails they provide.
How long should an agentic pilot run?
Four to six weeks is usually enough for a single bounded use case with a control group. Longer pilots tend to drift into open-ended experiments, the pattern Gartner links to canceled projects.
This week, pick one workflow, write the outcome and spend cap into a one-page scorecard, and send the six checklist areas to your top two vendors for written answers before any further demos.
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