AI makes it easier to produce marketing content, but faster production doesn’t mean more time for strategy, planning, or better work.
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AI has made it easier to produce email marketing, but not necessarily easier to produce better email marketing. AI can generate copy, suggest subject lines, and help us move from a blank page to a first draft faster. But it still needs marketers to provide the strategy, judgment, customer understanding, and critical thinking that make the work worth sending.
Knak’s Marketing Production in the Age of AI report suggests that AI might help marketers produce more work without giving them more time. According to the study, 85% of marketing teams surveyed missed at least one campaign launch date over the last year because of workflow constraints. Meanwhile, 82% still spend at least half of their time on production rather than planning or strategy.
We were sold on AI as a tool that would take on the grunt work and free up time for strategic thinking. Yet we’re still waiting for this time to materialize. We may have misunderstood the real problem all along.
AI has accelerated the beginning of the process
In the Knak study, 64% of respondents said they use AI to generate first drafts of email or landing page copy. More than half (56%) use it to generate or edit images. Another 56% use it to analyze performance and suggest optimizations, and 48% use it to produce subject line variations.
You can open ChatGPT and have a first draft within seconds. You can generate 10 subject lines almost as fast as you used to produce a single one. An initial campaign idea can morph into copy, imagery, and alternative creative treatments before the tea gets cold.
But generating a first draft isn’t the same as producing a campaign. Someone still needs to review the draft and rewrite it to reflect the brand’s voice, customer needs, and campaign strategy. And someone has to design, build, proof, approve, test, and schedule the email.
AI may have shortened the first stage of that process. But it hasn’t had the same effect on everything that comes afterward.
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The bottleneck was never writing copy
Knak’s findings illustrate where marketing teams are really losing time. The biggest reported delay, according to 47% of respondents, is securing approvals and sign-offs, followed by design and creative production (38%) and coordination across teams (36%). Sixty percent of teams need at least four people to produce a single email, while 69% go through two or three rounds of revisions before receiving approval.
These are workflow problems, not copywriting issues. They arise from complicated approval processes, unclear responsibilities, and too many handoffs between people and teams.
Using an AI tool at the beginning of that process simply helps reach the bottleneck faster.
You may save an hour producing the first draft, but that time doesn’t automatically become available for strategy. It can disappear into another revision, approval meeting, or version of the campaign. It may even vanish into a request from somebody who now knows you can produce content more quickly.
More content creates more decisions
There’s another possible reason AI hasn’t given marketers back the time they expected. AI produces considerably more marketing, not just the same amount of marketing faster.
When creating alternatives required time and effort, teams had to be selective. They might have developed two subject lines, one creative route, and a single email version. Now they can generate 10 subject lines, five opening paragraphs, three calls to action, and multiple visual treatments within minutes.
Is that progress? Maybe, at first glance. But every additional option requires another decision.
Somebody has to review those subject lines and compare the different versions. Stakeholders need to decide which direction they prefer. They may opt to combine elements from several alternatives and request yet another version.
AI reduces the time cost of creating options, but it doesn’t eliminate the cognitive cost of choosing among them. It may even increase it.
This opens the door to choice overload and distinction bias. The more alternatives you see side by side, the more likely you are to search for minor differences. Instead of deciding whether the campaign is strategically sound and ready to send, you debate whether version seven is marginally warmer than version four.
The result isn’t always better marketing. Sometimes, it’s simply more marketing to review, discuss, and revise.
The editing burden hasn’t disappeared
The Knak findings also challenge the assumption that an AI-generated draft is almost ready to use. Although 70% of teams have deployed AI within marketing production, 88% say its output still requires moderate or substantial human editing. The report suggests that AI contributes at the creative stage, while editing, brand alignment, approvals, and rendering still depend heavily on people.
AI is good at generating competent content. But that doesn’t mean it’s distinctive or strategically appropriate. It isn’t automatically persuasive, accurate, or recognizably yours either.
The first draft can be ready faster, but you still need to judge whether the message reflects the objective. Is it relevant, and does it present the offer clearly? Does it compel the audience to act?
AI can create the illusion of progress. It generates something to look at, so the work appears well underway. But if the strategic thinking hasn’t happened yet, the team could spend three rounds of revision trying to retroactively apply the strategy.
When AI shaves minutes off production time, that level of efficiency becomes the new baseline. Bonus capacity goes into increased output, more channels, more variations, and higher expectations.
Teams produce more campaigns because they can, and they create more versions because the tools make it easy. They increase the number of messages without pausing to ask whether each one is worth generating.
Faster teams use AI strategically
One finding from the study bolsters my contention that teams must use AI strategically to reap the benefits. Teams that can complete an email in around four hours tend to involve fewer people and use AI deliberately rather than experimentally.
This suggests that the AI advantage comes not from merely having access to AI but from deciding where and how to use it. This might be the real lesson: Teams need to use AI in the parts of the process that create bottlenecks.
- When approvals require six people, AI-generated subject lines won’t solve the problem.
- If teams build every campaign from scratch, faster copy won’t fix the production model.
- With unclear brand guidance, AI won’t prevent conflicts in stakeholder feedback.
- When teams work across disconnected tools, producing faster first drafts won’t make much difference for the eventual launch date.
AI can’t repair an unexamined process
Before investing in another tool, marketing teams must understand how their work travels from idea to launch:
- Who’s involved?
- Who must approve the campaign?
- Which decisions always cause delays?
- Where do teams duplicate work?
- How many tools, documents, messages, and meetings do teams use to launch one email?
- What could teams standardize using templates, modular design systems, shared strategic principles, and clearer approval rules?
- Does the team measure the production process itself?
Marketing departments are accustomed to measuring what happens after an email is sent. They track opens, clicks, conversions, revenue, unsubscribes, and deliverability.
Fewer teams measure how much time and effort they spent to produce the campaign. Without that visibility, organizations can celebrate the time AI saves on a single task while overlooking the hours lost elsewhere.
AI hasn’t failed, but implementation might have
The problem isn’t whether or not AI has failed to speed up marketing. It’s that we’re using the same fragmented, approval-heavy production process while expecting the technology to transform the entire system. As Knak Chief Marketing Officer Jennifer Delevante observes in the study, marketers were promised that AI would give them back time for strategy, but the data suggests that has not happened yet.
AI can still fulfill that promise, but it’ll require more than generating drafts more quickly. It’ll require us to rethink the production workflow.
Marketers must improve the systems that turn ideas into launched campaigns. Until then, AI will keep producing more marketing, not more time.
Contributing authors are invited to create content for MarTech and are chosen for their expertise and contribution to the martech community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. MarTech is owned by Semrush. Contributor was not asked to make any direct or indirect mentions of Semrush. The opinions they express are their own.
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