Omar Oakes wrote a piece this morning that stopped me mid-scroll - I've followed his thinking for a while and normally I'm nodding along to every line, but this one is half brilliant and half dangerous.
The brilliant half: AI used for creative judgment is making everyone sound the same. Verbose and declarative and oddly empty. WPP claiming they've bottled decades of creative expertise into "Super Agents" is exactly the kind of bullshit that deserves calling out. Omar's right - when you use AI to replace thinking rather than sharpen it, you get convergence and you lose friction and, as Omar says, "friction is where meaning lives."
I will die on that hill with you, Omar.
And I've made the point before that CFOs who see "20% time saved" and immediately think "20% headcount reduction" are making a terrible mistake. Jobs are messy. The friction that people bring - the dissent, the judgment, the "this doesn't feel right" - is exactly what Omar says we're at risk of losing. I agree with that too.
So where's the dangerous half?
It's the risk that Omar's argument gets used to tar all AI automation with the same brush. Because technical automation and creative automation are not the same thing. And treating them as the same problem leads to the wrong conclusions.
For instance... when I was CEO of media at Dentsu, the digital teams had the highest burnout and the highest churn and the lowest satisfaction scores. They weren't burned out because they lacked creative opportunity. They were burned out because the technical work never stopped - pulling data, building reports, troubleshooting performance drops, validating account setups, flagging tracking issues, running optimisations, doing QA. All of it manual and urgent and all of it eating up time they didn't have.
And they were still expected to do the strategic thinking and the client work on top. That's why they burned out. There literally weren't enough hours.
That's not friction where meaning lives. That's just friction.
And here's the bit that really mattered: those people didn't want to be spreadsheet and data monkeys. They wanted to do more strategic work. More client relationships. More of what they thought they were actually getting paid for. The drudgery wasn't just tiring - it was frustrating. It was stopping them doing the work that Omar rightly says matters most.
MCP - Model Context Protocol - is the direction of travel here. Google Ads already has an official MCP (read-only for now), and others are emerging. Even today, AI can query live data, pull reports, and surface issues without anyone touching a spreadsheet. The reporting layer doesn't get faster - it starts to disappear. Write access - letting AI propose and execute optimisations - is coming, but we're not there yet at enterprise scale. When it arrives, the rest of that technical work shrinks dramatically. My back of the fag packet numbers suggest 45% of a typical paid social team's time could be freed up. Some of that's possible today. All of it will be soon.
That 45% isn't creative judgment being automated away. It's people being freed FROM technical drudgery TO exercise more of the judgment and dissent that Omar rightly wants to protect.
And in this instance, everyone wins. The people get to do the work they actually wanted to do - less burnout, more fulfillment. The clients get more strategic thinking on their accounts. The agency gets happier clients who stay longer and spend more. Lower churn or higher revenue - probably both.
That's not "AI takes jobs." And it's not just "AI saves money." It's "AI makes the whole thing work better for everyone."
So Omar - I'm not disagreeing with you. I'm asking you to be more precise. Your headline says "technical labour" but your argument is about creative judgment. Those aren't the same thing. And when you blur the line, you risk scaring people away from the automations that would actually free them to do the work you're trying to protect.
Let me give you a real working example of an AI workflow I use almost every day. It's this LinkedIn piece - and just about every LinkedIn piece I write. Claude helped me draft this. Here's how it worked; I did the thinking - the idea, the structure, the argument, the challenge. Claude put flesh on the bones, then I edited the hell out of it until it sounded like me.
That's the right use of AI for me because I'm not a natural writer. My grammar and spelling are awful and I waffle on and repeat myself and go in circles as I write down what I'm thinking. I find it really hard to edit that rambling mess into something people might actually want to read. It gets overly long and confusing and self-referential. It's not good.
But AI is excellent at sorting out my spelling and grammar and making sense of my circular thinking. It puts it in a form I'm more comfortable with. Yes, I could probably get there myself - but it would take a lot longer. And I'd rather spend that time on the argument.
Which is sort of the whole point I'm making.
What do you think, Omar?
I edited this piece on 14th January 2026 to clarify the current state of MCP integrations that I inadvertently OVER HYPED. The original version overstated what's available today - the direction is right, the timeline was wrong. There ARE MCPs available that technically can do all this today, but they are not official and very brittle. The only official MCP is Google's AdWords read only version and even that is clunky. BUT it IS the direction of travel. The rest of the article still holds true.