AI in Marketing: How to Evaluate an Agency’s Workflow

Evaluate an agency’s AI use by examining a real workflow: what goes in, what comes out, who checks it and how mistakes are corrected. A tool list says little about whether the work will meet your requirements. Ask the team to demonstrate one task using approved sample material, explain its limits and show the human decision that follows. This guide provides a practical assessment process, rather than an estimate of industry adoption.

Distinguish Experiments From Routine Delivery

Separate experimentation from routine delivery. A writer trying a drafting assistant, an analyst using a model to summarize reports and a system changing campaign settings have different responsibilities and consequences. Ask which uses are exploratory, which are part of your contract and which can affect a live account. Record the tool, task owner, approved inputs, reviewer and release permissions for each workflow.

The NIST AI Risk Management Framework is a voluntary resource for considering trustworthiness throughout AI use and evaluation. It is a useful starting point for an agency discussion, rather than an agency certification or proof of campaign performance. The buyer checks below are our practical recommendations for that discussion.

Check the Task, Not the Label

• Content: Request the original sources behind factual statements, a record of editorial corrections and a named approver. Check that the final page adds information useful to its audience.
• Reporting: Ask the analyst to reconcile a summary with the underlying table. Distinguish observed results from explanations the model proposed. Missing data should remain missing.
• Creative: Review the brief, supplied assets and intended usage. Require a person to check brand identity, product details and whether the output represents the actual offer.
• Campaign operations: Identify which actions are recommendations and which can execute. Set explicit approvals for budget, targeting, account access and publication changes.

A short demonstration should include a difficult case. For example, give a reporting workflow two sources with different date ranges and ask the team to explain the mismatch. The useful result is an accurate qualification, not a confident but unsupported single number.

What Does Regional Experience Actually Tell You?

Do not infer AI capability from an agency’s city or size. For a regional campaign, ask how the team verifies local terminology, office locations, service areas and customer needs. Request a relevant project example and establish who supplied the local knowledge. Generated local copy should be checked against real sources rather than treated as evidence that a firm operates in a market.

Review Data Handling and Human Oversight

NIST’s Generative AI Profile, published in July 2024, addresses risks specific to generative systems and proposes risk-management actions. Use that resource to structure questions about the application you are buying. It does not establish how many agencies use AI or whether any particular agency delivers better results.

Start with data handling. Ask which client information enters each service, whether that use is authorized, who can access it and what the actual retention and deletion settings are. An agency should explain its specific arrangement rather than assume every account on a product has identical protections. Use approved sample or public material when a demonstration does not need confidential inputs.

Next, inspect the review process. “A human reviews everything” is incomplete without a defined checklist, an accountable role and enough time to perform the check. Ask what happens when a source cannot be verified, an output contains a wrong product fact or a client disputes a recommendation. Agree on how corrections reach both the working file and any published version.

How to Run a Useful Pilot

Choose one bounded task and state its acceptance criteria before work begins. For an article brief, criteria might include correct source links, clearly identified unknowns and coverage of the agreed buyer questions. For a reporting summary, require agreement with the approved date range, metric definitions and underlying calculations. Keep account changes and public publication outside the pilot unless separately authorized.

Compare the proposed workflow with your current process using similar inputs. Record preparation time, generation time, review time, correction time and the final decision. A faster first draft may still take longer to approve. Label the exercise as a pilot; a few examples do not establish a general productivity or revenue claim.

Keep a simple issue log: task, input, problem, reviewer, correction and final disposition. Include rejected outputs. That record helps you decide whether to expand, revise or stop the workflow and makes the assessment less dependent on a polished sales demonstration.

Future Outlook: Build Accountability Into the Agreement

Agree which uses require notification, which need approval and who owns the final deliverable. Revisit the process when the tool, task or data changes. Request an explanation of material workflow changes instead of assuming an initial assessment remains current indefinitely.

Use our agency hiring questions alongside the proposal comparison process. Record the answers in the comparison worksheet. The decision should rest on demonstrated work, clear responsibilities and the needs of your business.