My agency is already dead. And the thing that killed it isn’t AI in the generic sense everyone talks about. It’s something more specific: agentic AI. Systems that don’t just answer questions or generate text when you ask them to. Systems that work on their own. That research, decide, create, and deliver without a human in the loop at every step.
That distinction matters. A lot. And I’m going to explain it before I explain anything else, because if you don’t understand what agentic AI actually is, the rest of this post won’t make sense.
“Over the last couple of months I’ve come to the realization that our agency, our SEO company as it stands, is dead. They just haven’t started throwing dirt on our bodies yet. And it’s dead because of what’s happening in workplace automation, marketing, SEO, and what AI tools can do.”
What Is Agentic AI?
Most people’s experience with AI is ChatGPT or something like it. You type a question. It answers. You type another one. It answers again. You are doing the work. The AI is the tool you’re using to do it.
That’s generative AI. It’s powerful. It changed how a lot of people write and research. But it still requires you to be in the driver’s seat for every step of every task.
Agentic AI is different. An agent doesn’t wait for instructions at each step. You give it a goal, and it figures out how to accomplish it. It breaks the goal into tasks, executes those tasks, evaluates the results, adjusts if something isn’t working, and delivers the output. You’re not prompting it through every stage. It’s running the process.
Here’s a concrete example. Say you want a blog post about a competitor’s new product. With ChatGPT, you research the product yourself, paste in what you found, ask it to write a draft, review the draft, ask for revisions, clean it up, and then post it yourself. You touched every step.
With an agentic AI system, you give the agent a goal: research this company’s new product, write a 1,200-word post comparing it to our approach, optimize it for these keywords, and publish it to the blog. The agent goes and does it. It browses the web, pulls the relevant information, writes the draft, runs the SEO check, and publishes. You review the output. You didn’t manage the process.
That’s the shift. Not AI as a tool you use. AI as a system that works.
And that shift is what breaks the agency model.
The Honest Diagnosis
I’ve been in digital marketing for 25 years. I know what agencies sell because I’ve sold it.
Content production. Research: competition, market, user. Analytics and reporting. Technical SEO audits. Website architecture reviews. Performance testing. UX testing. Compliance reviews against Google’s quality guidelines and W3C standards. Social media strategy and execution. Link building and outreach. On-page and off-page SEO. Conversion rate optimization. Local SEO. Schema markup implementation. Site speed analysis. Content gap analysis. Editorial calendars. Monthly client reports. Quarterly strategy presentations.
That’s what an SEOl agency actually does. Every one of those services requires human expertise and human labor to execute at any meaningful scale. Writers, researchers, analysts, technical SEO specialists, outreach coordinators, social media managers, account managers, strategists. The whole stack.
Three of those services are worth examining in detail: content production, research, and reporting. They are the most labor-intensive, and they show exactly how fast this is changing.
Agentic AI handles all three.
Autonomously.
Content production: an agent doesn’t just write one article when you ask it to. It can run a full content operation. It identifies topics based on keyword gaps and competitor analysis, drafts posts, checks them against brand guidelines, optimizes for search, and queues them for publishing. The pipeline runs. Your content writer used to own that entire workflow. The agent owns it now.
Research: an agent doesn’t wait for a human to pull data from six platforms and synthesize a report. It connects to those platforms, gathers the data, identifies the patterns, and produces the analysis. The specialist who used to spend three days building a competitive intelligence brief? The agent does it in an hour, without anyone asking it to.
Reporting: an agent monitors your clients’ rankings, traffic, and conversions continuously. It detects anomalies. It generates the monthly report, writes the commentary, and sends it. The account manager who used to spend a full day on that deliverable is now managing the output and owning the delivery.
This isn’t theoretical. These systems exist today and they work. The question isn’t whether they can replace agency workflows. They already are.
Why This Is Different From Every Previous AI Wave
Every few years, some new technology gets declared the thing that will kill agencies. Usually it doesn’t. Not completely. The agency adapts, repositions, finds the thing the technology still can’t do.
This time is different, and here’s why: previous tools changed how agencies worked. Agentic AI replaces what agencies do.
When Google rolled out algorithm updates, agencies had to adapt their SEO approach. When social media took off, agencies had to build social media practices. When marketing automation arrived, agencies added automation to their service stack. Each wave changed the method. The underlying model stayed the same: the agency provides human expertise and human labour to do the work.
Agentic AI removes the need for most of that human labour. Not because agents are smarter than your team. Because they’re autonomous. They don’t need someone to manage them through each task. They run the task.
I watched something similar happen to AutoTrader. They started as a print catalogue. Thick, physical, you had to source it out and pick it up and sometimes buy it. It worked. Then the internet happened. The smart people at AutoTrader didn’t defend the catalogue. They recognized that classified car listings were the product, and the internet was a better format. They made the leap and became the most dominant digital automotive platform in Canada. I was at the leading edge of the transformation. I worked with the training department to build to tools the sales team needed to transform to selling digital products instead of print. After the training was built it was determined an expert was needed so I spent the next 18 months travelling back and forth across Canada delivering training multiple times. I built a team of digital marketing expats in each market that could help the transition and provide expertise while sales rep were brought current in digital marketing. I ran that team for years. When Auto Trader was sold by YPG I moved over to the Yellow Pages side and rebuilt another team of digital experts while also being designated as a key resource to high valued clients.
On the Automotive side the dealers who said “nobody’s buying cars online” lost market share they never got back.
The analogy for agencies is this: the old model defended human-executed workflows as the product. Agentic AI is the internet. The agencies that survive recognize the actual product is outcomes for clients, and agents are a better format for delivering them.
What It Means for Your Team
I’m going to say the part nobody wants to say.
Agentic AI doesn’t just change how work gets done. It changes how many people you need to do it.
With ChatGPT-style tools, the ratio still makes sense. The AI helps your writer work faster. You still need the writer to manage the AI, edit the output, and handle the judgment calls at every stage. You might get 30-40% more productivity out of the same headcount.
Agentic AI changes the math completely. An agent running a content operation doesn’t need a human overseeing each step. The human’s role shifts to setting the strategy, reviewing outputs, and adjusting the system when something isn’t performing. One person can now direct an agent workflow that used to require a team.
A content operation that used to need five people now needs one or two senior people and a well-configured agent system. That’s not an estimate. That’s what we’re living right now.
I’m not going to dress that up. AI Agents replace process, not just tasks. When the entire workflow runs autonomously, you don’t need the same headcount to execute it. The agencies still staffing at 2022 levels while using agentic systems are either doing it out of loyalty they can’t sustain, or they haven’t looked at the numbers honestly.
The companies that make it through are the ones that figure out the right team shape now: fewer people, senior, capable of directing AI systems rather than executing tasks those systems handle.
What the Future Model Actually Looks Like
The agency of 2027 isn’t built around human task execution. It’s built around agent coordination.
What does that mean in practice? The team isn’t managing writers, researchers, and analysts doing work. The team is managing agents doing work. The human role is strategy, quality control, client relationships, and system optimization. Not volume production.
Revenue doesn’t come from content packages and rank tracking reports. It comes from designing the agent systems that produce the content and generate the reports. From configuring those systems for a client’s specific business. From maintaining and improving them over time. From applying the strategic judgment that tells the agents what to prioritize.
SEO doesn’t disappear from the offering. It becomes one application of a broader system. The content operation runs on agents. The reporting runs on agents. The competitive research runs on agents. The human expertise that used to direct a team of people now directs a system of agents.
This is a real opportunity for Canadian SMBs, and the window is open right now. Most Canadian businesses are early. They know they’re supposed to be doing something with AI. They’ve got a ChatGPT subscription nobody really uses. They don’t have a system.
The companies that get their agentic systems dialled in this year will have a cost structure and output capacity their competitors cannot match. That advantage compounds. By 2027, the gap between companies that moved early and companies that waited is not going to be closeable. You can’t catch up to a competitor whose entire operation runs on agents while you’re still running on people.
The window is months, not years.
The Only Question That Actually Matters
The conversation most businesses are having right now is “are you using AI?” That’s the wrong question. It treats AI adoption like a binary. You have a ChatGPT login or you don’t.
The real question is: are you using agentic systems?
Are you running AI that takes a goal and executes it autonomously, or are you using AI as a slightly smarter search engine? Are your workflows still dependent on humans managing every step, or have you built systems that run those steps on their own?
That’s the line. Not “do you have AI tools?” but “are your AI tools doing the work, or are your people doing the work with AI tools helping?”
If you’re an agency owner, look at your workflows honestly. Map out every billable process. Ask: could an agent handle this end to end with minimal human oversight? If the answer is yes for more than half your processes, your current model is already dead. The billing hasn’t stopped. The clients haven’t cancelled. But the math doesn’t work anymore.
If you’re a business owner trying to figure out what this means for your company, the answer isn’t more ChatGPT usage. It’s agentic systems designed for your specific workflows. That’s where the real leverage is.
My agency is already dead. Not because AI is everywhere. Because agentic AI specifically made the labour model it ran on obsolete.
What comes next is built on agents. And we’re building it now.
David Henderson is the founder of Unwired Web Solutions. He’s been in digital marketing for 25 years and is currently rebuilding his agency as an AI consulting and integration company. He’s writing about it at davidhenderson.ca.