Why AI Efficiency Shouldn't Mean Smaller Marketing Budgets
Mia Mohamed
8/7/20265 min read
The efficiency argument is starting to go too far
There's no doubt AI is making marketers more productive. The evidence is becoming increasingly compelling. Controlled studies have shown professionals completing knowledge-based tasks 40% faster while improving the quality of their output by 18%. Other workplace studies are reporting employees saving around two hours a week through the use of generative AI, while McKinsey estimates the productivity opportunity in marketing could equate to 5–15% of total marketing spend.
I've experienced those efficiencies myself. AI has fundamentally changed how I research, analyse markets, interrogate ideas and take some of the heavy lifting out of work that previously took hours. The problem isn't the productivity gains. It's the conclusions we're starting to draw from them.
I'm seeing more commentary suggesting that as AI makes marketing teams more efficient, businesses should naturally expect to spend less on marketing. In short: fewer people, less reliance on agencies, greater automation and ultimately lower costs.
And this is where I start to disagree as being able to do certain things faster doesn't mean businesses suddenly need to do less marketing. If anything, it creates an opportunity to do more of the things that actually drive growth. Rather than simply banking the savings, I'd argue we should be reinvesting that newly created capacity into the areas technology still can't replace.
We still need to show up
I've spent much of my career marketing into complex B2B and financial services markets, and one thing hasn't really changed: you have to show up, and everything matters. From online ads, content and email communications to building or deepening relationships. In a nutshell, visibility through reputation building and presence matters. You have to show up in the places where your customers, prospects and industry peers spend their time and technology helps facilitate this but marketers make it happen.
That means proprietary events and industry events. It means PR, advertising, awards, partnerships and content syndication. It means putting your executives on stages and creating opportunities for customers and prospects to actually spend time with your people. These things require investment, and their value doesn't disappear because we've found a faster way to produce a piece of content or analyse a set of data.
AI can certainly help us make better decisions about where to invest. It can help us understand which events are worth attending, research the people we want to meet, prepare more intelligently, create supporting content and get far more value from the activity afterwards. That's where I see a very real opportunity, but it doesn't replace the need to be there in the first place.
Efficiency and effectiveness aren't interchangeable
Here's where I think the current conversation needs more nuance. If AI saves a marketing team 20 hours a week, the immediate question shouldn't necessarily be how many roles that allows us to remove. I'd rather ask what that team can now do with those 20 hours that it couldn't do before. Could they spend more time understanding customers? Work more closely with sales? Look properly at what's changing in the market? Strengthen positioning? Develop better ideas? Get to some of those strategic priorities that constantly lose out to the day-to-day demands of running marketing?
The same principle applies to budget. If technology allows us to produce something for £20,000 that previously cost £40,000, we've created £20,000 of capacity. Of course a business may choose to take some of that saving, but I'd hope the marketing conversation also includes where that money could now work harder. Perhaps it's an event where there was never any budget before to network, speak or sponsor, but highly relevant to where customers and prospects attend. Or, perhaps, its investing in proprietary research that could give a stronger voice in the market, a targeted PR programme or simply putting more investment behind the things known to work or currently working.
That's a very different conversation from assuming greater efficiency should automatically equal a smaller marketing budget.
Measurement matters, but so does understanding how B2B buying actually works.
I'm a big believer in marketing accountability. We should be able to explain where we're spending money, why we're spending it and what we're getting in return. Better data and technology should absolutely help us do that.
What I don't subscribe to is the idea that every valuable marketing interaction can eventually be attributed neatly to revenue. Particularly in B2B, buying simply doesn't work that way. Someone might see your CEO speak at an event, come across your research several months later, read about you in an industry publication and then hear your company mentioned by someone they trust. Or consistently come across subtle advertising shared on platforms they frequent for news and commentary. When a need eventually arises, you're one of the businesses they think about.
Which interaction created the opportunity? Probably no single one of them.
That's why I'm wary of allowing greater measurability to become the definition of greater value. Some of the things that matter most in marketing, trust, reputation, familiarity and relationships, are built over time and across multiple interactions. We should absolutely get better at understanding their contribution, but pretending we can attach a precise revenue number to every one of them risks giving us confidence in the measurement rather than insight into what actually influenced the buyer.
Use AI to find the waste, not simply the savings
There is plenty of marketing spend that should be challenged. We've all seen businesses attend the same events year after year because they've always gone, produce content because the calendar says something needs publishing or continue agency relationships long after anyone has questioned whether they're delivering enough value. If AI and better data help us identify those things faster, I'm all for it.
But once we've found the waste, I'd like us to have a more ambitious conversation about what happens next. Could we use that investment to get closer to customers, build a presence in a market we're trying to enter, create genuinely useful research, put our experts in front of more of the right people or strengthen the reputation and trust that ultimately makes the job of Sales easier?
That's where I think the real opportunity sits. Not in asking how cheaply we can now run marketing, but how much more intelligently we can invest in it.
Concluding thoughts
I'm not arguing that marketing budgets should be protected regardless of performance. If something isn't working, challenge it. If AI removes the need for certain activities, redirect that investment.
What I do question is the growing assumption that greater efficiency should automatically mean lower marketing spend. Boards and investors are rightly focused on improving margins, but there is a difference between cutting cost and building value.
Businesses like Monzo spent years investing in customer growth, brand and market presence before achieving sustained profitability. That required patience and conviction, not simply relentless cost reduction.
AI gives us an opportunity to think differently. Instead of asking, "How much can we save?", perhaps the better question I'd ask is, "Where can we now invest more intelligently?" I think those businesses that use AI to remove waste while investing more deliberately in long-term growth via marketing spend will be the successful ones.
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