What Staying Ahead of AI at an SEO Agency Actually Looks Like

Honestly, not everyone walked in fully convinced that a whole day away from client work was the best use of time. That skepticism didn't last long.

A lot of preparation went into it. The agenda covered AI's evolving role in SEO and GEO, where it's shifting how search works, where the value sits for clients, and how we continue to stay ahead of it as a team. The conversation was open and wide-ranging, drawing on the different levels of technical experience and AI depth across the team, and a lot of it was refreshingly honest. There were plenty of "it depends" and "I don't know yet" answers, which is a pretty reasonable response in a space moving this fast.

Part of the day also involved getting hands-on with a new internal project management system (Our own OptMCP), custom-built specifically around how we work, bringing together campaign details, tasks, client comms, and performance analytics from our key platforms, with AI integration built in. The brief when we sat down with it was to try and break it, because that's how you find out where it needs to improve. It's still being actively workshopped, with the team feeding back on a rolling basis.

For our Senior SEO Specialist, Brandon, that kind of integration is where things get interesting. "So much of the conversation we have as a team is riddled with 'it depends," he said, "and what the platform helps us do is actually rationalise what that means. We can pull feedback from similar work, use data more efficiently, and end up with strategies that genuinely reflect the circumstances of each campaign rather than a one-size-fits-all approach."

Even in a team that's already across this stuff, some questions are worth asking. One of them is whether AI just means everyone is expected to do more in the same amount of time, faster output, more tasks, indefinitely.

That's not the direction we're heading. SEO Specialist, Taylor, put it clearly: "Utilising AI properly doesn't mean we need to be doing ten more tasks because we can do them quickly. It means we can spend more time on the tasks that will really move the needle, and do them really well. If AI can do the mundane jobs, we can spend more time becoming the strategy experts and knowing the client and their industry inside out.

It's easy to look at the adaptation of AI as a speed test for real people. It's faster, yes, but that framing misses what still needs to happen on the human side.

Harry, Head of Client Services, made a point that stuck: for larger-scale analysis, AI is effective at surfacing high-level insights quickly, but only if you're working with the right data points. Knowing what to pull, why that's the right data, and how to interpret what comes back, is still the skilled part. The tools may move faster, but the judgment doesn't come with them.

Some of what's now possible has moved remarkably fast, and the integration opportunities are exciting. But the reason it works is because skilled people are directing it, questioning it, and applying it in the context of real client goals and real industry knowledge. That's not something a prompt can replace.

Brandon made a similar point from a different angle. Less time jumping between platforms and spreadsheets to chase down insights means more time on the work that's harder to systematise: industry research, understanding what's actually driving the people behind the sessions and purchase figures, and finding better ways to connect with them. That's where the interesting thinking happens.

The day was a checkpoint, not a conclusion. The platform will keep evolving, the team will keep testing and improving it, and the conversations that started that day are already showing up in how briefs are being framed, how analysis is being approached, and how we're thinking about strategy for clients.