AI agents for marketing agencies

An agency's own website has an awkward job: it has to sell marketing to people who know marketing. Prospects read it skeptically, compare it with three other agencies, and often decide whether to book a call before anyone on your team knows they visited. An AI agent on that site has to be as careful with claims as your best account director, and as quick as your contact form is slow.

Who visits a marketing agency website and what they need

• Prospective clients. Marketing managers, heads of growth and founders. They want to know whether you have done this before in their industry, how you charge, what the minimum is, how long the contract runs and who owns the ad accounts and data afterwards.
• Referral partners and other agencies. Looking for overflow or white-label capacity. They need a different conversation from direct clients, often with a different person.
• Existing clients. Trying to reach their account manager or find a report. Sales follow-up is the wrong response.
• Job candidates and freelancers. They read the same pages as prospects but belong on the careers page.
• Vendors pitching you. Tool sellers and link brokers. A polite redirect to a general inbox saves your team time.

The pages that do the selling are the services pages, the case studies and, if you have one, a pricing or "how we work" page. Thin versions of those pages produce thin answers.

Which ASDK agents fit an agency website

ASDK is in early access. Sales, Chat and Agent-Ready are early-access agents; Forms is coming soon.

Sales: qualifies before the discovery call

Example flow: a visitor asks whether you run paid social for B2B software. Sales answers from your services page, then asks the questions you set in plain language: monthly budget, channels, current setup, start date. If the budget clears your minimum, it offers a slot on the right strategist's calendar through Cal.com, Calendly or Google Calendar, and the lead arrives with the transcript, by email or Slack and in your CRM through webhooks and Zapier or Make, so the call starts at question five instead of question one. Below the minimum, it says so plainly and points to your guides. More on question design in how to qualify inbound leads with AI.

Chat: answers the questions prospects are shy to ask

Example flow: "If we leave, do we keep the Google Ads account?" Chat answers from your terms or FAQ page and links to it. If the answer is not on the site, it says it does not know and offers to pass the question on, which is better than a confident guess about contract terms.

Agent-Ready: makes the agency visible to AI assistants

A buyer can now ask an assistant for an agency shortlist by specialty, industry and location. Agent-Ready hosts an llms.txt file that points to your services, case studies and pricing model, exposes actions such as "book a call" through the widget, and, on Pro and above, shows which AI agents read which pages. For an agency that sells generative engine optimization to clients, your own site is also the demo.

Forms (coming soon): scope quiz instead of "contact us"

When Forms ships, it will turn a static inquiry form into a short conversation (channels, markets, monthly budget, start date) that ends with a price range built from rules you describe. The lead arrives with a budget attached.

Guardrails that matter for agencies

• No promised results. Google's own hiring guide says no one can guarantee a #1 ranking, and the same applies to ROAS or lead volume. The agent can quote a case study exactly as published; it should not extrapolate "you could expect" numbers for a new prospect.
• Client names stay where you put them. Only clients already named on your site, with permission, should appear in answers. Clients under NDA must not be in the knowledge base at all.
• Ranges, not quotes. Share your pricing model and minimums; a proposal stays a human job.
• No free strategy audits in chat. A short, general answer is fine. A plan for their account is what the discovery call is for.
• Route the side traffic. Candidates to careers, vendors to a general inbox, existing clients to their account manager. Every chat shows an AI disclosure, and a handoff to a person is always available.

How AI assistants research agencies for buyers

In Gartner's May 2026 release, 45% of B2B buyers surveyed said they used generative AI during a recent purchase, mainly to gather information on vendors and products. The same survey found that 69% prefer to validate AI-generated insights with a sales rep, so the assistant can put you on the list, and your team still has to win the deal.

What an assistant needs to put an agency on a shortlist:

• Specific services. "Technical SEO for SaaS" beats "digital growth solutions".
• Industries and client size you serve, and the ones you do not.
• Pricing model and minimum engagement, even as a range.
• Locations and time zones you work in, and whether you work remotely.
• Platforms and partner programs you work with, linked to the partner's own directory where one exists.
• Case studies with dates, scope and method, so a quoted result has context.

Google says its AI features need no special optimization beyond normal SEO, and that structured data should match the visible text. Describing each offer with Service markup, including areaServed and serviceType, keeps the facts consistent for every reader. To see where your site stands, run the free Agent Readiness Checker, then read how Agent-Ready keeps those signals current.

Running agents for your clients

Agencies that build or manage client websites can run ASDK across them on the Agency plan. Its white-label widget and dashboard, client reports and custom widget domain are coming soon, not available yet; current limits are on the pricing page. Start on your own site first, so you know what the first month of questions looks like before you put the same setup in front of a client.