Sales Teams Figured Out AI. Marketing Is Next.
The one thing you need to know in AI today | AI-Ready CMO
Salesforce published its State of Sales 2026 report (pdf), surveying over 4,000 sales professionals worldwide. The headline finding is that AI agents are the #1 growth tactic for sales teams this year. 87% of sales organizations are already using AI. 54% have deployed AI agents, and nearly 9 in 10 plan to by 2027.
As our reader following this space, none of this should surprise you. The more interesting story is how companies react to these changes.
Everyone is productive. Time to show the money.
For the past two years, every AI vendor has sold the same pitch: save time, do more with less, free up your team from busywork. Salesforce's own data supports it: agents are expected to cut prospect research time by 34% and content creation by 36%. Fine.
But here's what's shifting: sales leaders are realizing that productivity is a terrible success metric for AI because AI will blow past any productivity target you set.
Of course it's faster. It's software.
Futurum Research found that "productivity" as the #1 measure of AI success fell nearly 6 points in just six months. What replaced it is direct financial impact — revenue growth and profitability — which nearly doubled as the top measure. Saving time is no longer the point. Making money is.
Here’s what we think the report undersells: sales is going to be one of the most durable jobs in the AI era, and this data explains why.
High performers aren't replacing salespeople with AI agents — they're 1.7x more likely to use agents for prospecting, the part of the job reps hate most, and that requires the least human judgment.
Sales isn’t just about relationships. It’s about responsibility. Someone has to own the number. Someone has to look a client in the eye when the implementation goes sideways. Someone has to sign the deal, carry the quota, and be accountable when things don’t work.
AI can prospect 24/7, score every lead, and draft every follow-up email. It cannot take responsibility. And until it can — which is a much harder problem than automation — you still need a human in the chair.
If you’re a marketer reading this and thinking “good for the sales team,” look again. This pattern is coming for you next.
Sales is ahead of marketing in figuring out the AI division of labor: automate the mechanical, keep humans on the decisions that carry real consequences. In sales, the human stays because someone has to own the number. In marketing, the human stays because someone has to have taste — to know which brief to write, which story will land, which bet is worth the budget. Both are accountability jobs. Both are safe for the same reason: AI can execute, but it can’t be responsible for the outcome.
The productivity shift matters even more on the marketing side.
We’ve spent years measuring ourselves by output volume — posts published, emails sent, impressions served — and AI is about to make all of those metrics meaningless. Every team will be absurdly productive. Every team will be able to generate a hundred assets a week. That stops being a differentiator instantly.
The question that replaces it is the same one sales leaders are already asking: did it make money? Did the campaign open a market that was previously out of reach? Did the content drive a pipeline that didn’t exist before?
If your AI strategy is “do the same things faster,” you’re optimizing for a metric that’s about to stop mattering. The teams that win will be the ones who use the freed-up capacity to go where they couldn’t before.
— Torsten and Peter
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Our January AI in Marketing Report is out.
AI isn't slowing down in 2026. This report gives you the strategic context you need to stay ahead.
January brought major model releases, new enterprise adoption patterns, and shifts in how marketing teams actually use AI. We’ve uncoverd the pattern analysis across 31 days of developments. What’s accelerating. What’s overhyped. What you should be testing now.
The report includes implementation frameworks, budget guidance, and forward indicators for Q1. Built for leaders who need to make decisions, not just stay informed.
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The point about responsibility is underappreciated. AI can execute, but someone still has to own the outcome. That's why the human in the chair isn't going anywhere, they're just getting better tools.