Is Your Marketing Agency Using AI the Right Way? Questions to Ask Before You Renew
Most agencies claim AI expertise. Here is how to evaluate whether your agency is actually adapting strategy for AI search or just using AI tools internally to work faster. Published July 11, 2026.
Most marketing agencies in 2026 claim AI expertise. The meaningful distinction is between agencies that use AI tools internally to work faster and agencies that are actively managing how AI search affects their clients' visibility and buyer journey. Before renewing a contract with your current agency, six questions will tell you which category they are in. The answers also reveal whether you need a different type of marketing leadership entirely.
Agency relationships are easy to renew by default. The contract expires, nothing is on fire, and the path of least resistance is another twelve months. That pattern made reasonable sense when the marketing environment was relatively stable. It is a riskier default in 2026, when the fundamental mechanics of how buyers find businesses have changed enough that an agency maintaining your program without adapting to those changes is quietly managing a declining asset.
AI search is not a future risk. Organic click-through rates dropped 61% on queries where Google AI Overviews appear. Ninety-three percent of Google AI Mode searches produce zero external clicks (Semrush, 2025). More than half of B2B buyers now start vendor research with an AI chatbot. These are current conditions, not projections, and they require specific changes to what a marketing agency builds and measures on your behalf.
This is not a checklist for finding fault with your agency. It is a practical framework for understanding whether your current relationship is calibrated for the environment your buyers are operating in.
Why Is Your Agency's AI Competence Worth Evaluating Before You Renew?
Most agency contracts were written when organic traffic was growing, traditional SEO metrics were meaningful proxies for business impact, and the concept of AI-mediated buyer research was not yet a delivery consideration. A lot has changed since then.
An agency running the same playbook from 2022 is not necessarily doing bad work. They may be executing well against a set of tactics that no longer move the same levers they used to. The problem is not incompetence. It is a mismatch between the strategy being executed and the environment it is being executed in.
The business risk is specific. If AI Overviews are answering the queries that used to send your top-of-funnel organic traffic, your traffic will decline whether or not your rankings change. An agency that is tracking rankings and reporting them as green while not addressing the AI-mediated layer above the organic results is reporting an incomplete picture. You deserve to know whether the measurement framework your agency uses captures what is actually happening to your business.
What Does Genuine AI Expertise Look Like vs. Surface-Level Claims?
Almost every agency in 2026 has added AI language to its pitch materials. Evaluating the claim requires one clarifying question: is the AI expertise about what happens inside the agency, or what happens for your business?
Internal AI expertise means the agency uses AI tools to draft content faster, automate reporting, or summarize competitive research. That is an operational efficiency improvement. It may or may not affect your outcomes. Most agencies that claim AI expertise mean this version.
Strategic AI expertise means the agency has changed what it builds and measures for you based on how AI search has changed the buyer journey. It means your content is being structured so AI systems can extract and attribute it. It means your agency knows your Share of Answer baseline and is actively working to improve it. It means someone on your account understands how AI Overviews are affecting your organic CTR and has a specific response strategy.
The difference is not subtle. You can identify it in a single conversation.
What Questions Should You Ask Your Agency About AI Search?
These six questions create a clear diagnostic picture. Strong answers indicate an agency that has genuinely adapted. Vague or deflecting answers indicate the gap.
"Are you tracking our Share of Answer in AI tools, and what is our baseline?" Share of Answer measures how often your brand appears in AI-generated responses across ChatGPT, Perplexity, Claude, Gemini, and Copilot for the queries your buyers use. An agency managing your AI visibility should have run this baseline and be tracking it monthly. If they have not heard the term or cannot tell you what your current baseline is, that is a meaningful gap.
"How has our content strategy changed to account for AI Overviews reducing organic CTR?" The correct answer involves specific changes: BLUF-structured content, FAQ schema implementation, direct-answer formatting in informational content, or GEO/AEO optimization on your highest-traffic pages. A vague answer about "quality content" is not an answer to this question.
"How are you measuring the impact of AI-influenced traffic that does not click through?" Zero-click search means buyers are researching your brand in AI tools before visiting your site. That activity shows up in direct traffic inflation, branded search increases, and higher-intent first sessions. Your agency should have a framework for reading those signals. If measurement is limited to clicks and impressions, the picture is incomplete.
"What GEO or AEO optimization have you done on our existing content?" This question asks for specific past actions, not future plans. Answers should include: content restructuring for AI extractability, FAQ schema additions, entity signal improvements, or structured data expansion. If the answer is "we're planning to look into that," the work has not started.
"How do you evaluate whether AI tools are moving our metrics vs. saving your team time?" This question separates internal efficiency claims from client impact claims. An honest answer distinguishes between the two and is specific about which outcomes are being attributed to AI-assisted work.
"What has changed in your measurement approach since Google AI Overviews expanded?" The right answer demonstrates that the agency tracks more than traditional SEO metrics. If nothing has changed in how they measure your program, that is an answer.
What Should Your Agency Be Measuring That It May Not Be?
In a search environment where AI systems intercept buyers before they click, traditional traffic metrics tell an incomplete story. The metrics your agency should be tracking alongside the standard dashboard include:
Share of Answer: The percentage of relevant AI-generated responses that include your brand across the five major platforms. This is the leading indicator of brand presence at the stage of the buyer journey that now precedes most website visits.
Direct traffic composition: In a zero-click world, AI-influenced buyers who researched your brand in an AI tool often arrive via direct traffic with no referral attribution. Direct traffic volume and conversion rate are meaningful signals of pre-visit AI exposure.
Branded search volume trends: When buyers see your brand mentioned in an AI tool, they often search your brand name directly shortly after. Rising branded search impressions in Google Search Console alongside flat or declining non-branded impressions is a signal of AI influence on your buyer journey.
Conversion rate per session: Traffic volume is a less useful metric when a growing portion of non-click searches are answering queries that previously sent traffic. Session quality, measured by conversion rate and depth of engagement, is a better proxy for marketing effectiveness than pageview counts alone.
What Are the Signs Your Agency Is Not Keeping Pace with AI Changes?
The clearest signals are visible in reporting and communication patterns, not technical audits.
Traffic is declining without explanation. If organic traffic is dropping and the agency's response is to adjust rankings targets or point to algorithm updates without addressing the AI-mediated layer, the diagnosis is incomplete.
Reporting contains no mention of AI search behavior. Monthly reports that cover only impressions, clicks, CPC, and keyword rankings are not measuring what now matters most. The absence of Share of Answer, direct traffic analysis, or AI visibility commentary is a signal in itself.
Content strategy has not changed in over a year. If your content calendar looks the same as it did in 2023 and no one has raised the question of AI extractability, that is a gap. The structural requirements for content that performs well in AI-mediated search are specific and known. Ignoring them is a choice, even if it is an uninformed one.
When asked about AI, the conversation stays internal. Answers about how AI tools help the agency work faster are not answers to the question of what AI search means for your business.
What Does It Mean If Your Agency Fails This Evaluation?
There are three realistic scenarios.
The agency acknowledges the gap and has a credible plan. This is the best case. Some agencies are behind but adaptable. If they can name specific changes they will make, describe how they will measure them, and give you a reasonable timeline, the relationship may be worth continuing with clear expectations.
The agency cannot adapt. Either the talent is not there, the processes are not built for it, or the leadership does not prioritize it. In that case, continuing the relationship is a decision to accept the status quo. A different agency may close the gap faster than trying to develop it internally within a relationship that is not calibrated for it.
The problem is strategic, not executional. This is the scenario the first two can mask. If your marketing program needs a different strategic direction, not just better execution of the current one, an agency relationship is not the right tool. Agencies execute against a strategy. If the strategy itself needs to change, because AI search has shifted your buyer journey, because your growth has stalled, or because your marketing investment is not connecting to revenue, that is a leadership problem. It requires a different type of engagement. The fractional CMO model exists specifically for this scenario: strategic marketing leadership for businesses that need direction, not just execution.
For more context on how to think through the agency vs. FCMO decision, see fractional CMO vs. marketing agency and how to choose a digital marketing agency. For context on what AI-forward marketing leadership specifically looks like in 2026, see what an AI-forward fractional CMO does differently.
Two capabilities are worth probing directly: whether the agency can build E-E-A-T signals that influence AI citation, and whether it can measure marketing results when buyers research in AI and never click.
Frequently Asked Questions
Evaluating Your Agency's AI, Answered
How often should I evaluate my marketing agency's AI capabilities?
Once a year at minimum, aligned with contract renewal cycles. In a rapidly changing environment, semiannual check-ins are more appropriate. The pace of AI search development means that an agency that was genuinely ahead six months ago may have fallen behind if they have not continued investing in the capability. The questions in this post are a useful template for a structured evaluation conversation. They are not confrontational. They are the kind of questions a well-informed client should be asking regardless of how long the relationship has been in place.
What if my agency is honest that they don't have AI expertise yet?
Honesty about a gap is meaningfully better than false claims of capability. An agency that acknowledges where they are behind and can describe a specific plan to close the gap is a better-informed partner than one presenting polished AI language over underdeveloped practice. The key follow-up question is whether the plan is credible and the timeline is specific. Vague plans to "invest in AI training" or "explore GEO optimization soon" are not plans. A concrete roadmap with deliverables and a measurement framework is a plan.
Is there a difference between an AI-first agency and an established agency that has adapted?
Yes, and the distinction matters less than most buyers assume. An AI-first agency built around AI tools from the start may have stronger internal workflows but less track record managing complex marketing programs with human judgment in the loop. An established agency that has genuinely adapted has the track record, the client relationship experience, and the AI-adapted methodology. What matters most is not whether AI was present from founding but whether the team managing your account understands AI search mechanics well enough to build your strategy around them.
Should I be evaluating my agency on AI competence or hiring a Fractional CMO instead?
These are not mutually exclusive decisions. An agency evaluates to execution quality on a defined scope. A Fractional CMO evaluates to strategic direction across the entire marketing program. If your agency is executing well but you lack someone who owns the overall strategy, decides what channels to prioritize, and makes the call on whether GEO optimization belongs in next quarter's priorities, that is an FCMO-shaped gap. If your agency is executing the wrong strategy well, that is also an FCMO-shaped gap. If the strategy is sound and execution is the question, the agency evaluation framework in this post is the right lens.
What does a realistic timeline look like for an agency to get up to speed on AI search?
A competent team with genuine leadership commitment can run a Share of Answer baseline, audit existing content for AI extractability issues, and begin implementing FAQ schema and BLUF structure within four to six weeks. Full GEO optimization across a site's most important pages takes two to three months depending on content volume. Building the measurement framework to track AI-influenced traffic patterns takes one to two months. If an agency is quoting timelines significantly longer than this for basic AI visibility work, the bottleneck is probably prioritization, not complexity.
My agency says AI search doesn't matter for my industry yet. How do I evaluate that claim?
Ask for the data. Specifically: what percentage of the queries that drive your organic traffic now trigger AI Overviews, and what has happened to the click-through rate on those queries over the past twelve months? Google Search Console provides impression and click data at the query level, and the CTR movement on AI-affected queries is measurable. If the agency cannot show you this data or has not looked at it, that is a more informative answer than whether they believe AI search matters. The claim that AI is not yet affecting a specific industry is sometimes accurate, but it requires data to support it rather than assumption.
About the author. Jaron Mossman is the founder of 360ROI LLC, a boutique digital marketing consultancy based in Castle Rock, Colorado. He spent two years managing multimillion-dollar advertising accounts at Google's Manhattan office for Fortune 500 travel and hospitality brands before founding 360ROI in 2013. He delivers Fractional CMO engagements for growth-stage businesses across medical aesthetics, B2B manufacturing, and nonprofits.