A senior Adobe executive is making the case that AI-generated marketing content has a sameness problem, and that small businesses need to actively fight it rather than assume the tools will handle it for them. The comments, part of a broader push by Adobe to position its creative software as a companion to AI rather than a replacement for it, land at a moment when nearly every marketing platform is racing to add generative features.
The core argument is straightforward: AI models are trained on massive pools of existing content, so left unedited, they tend to produce writing and imagery that sounds like everyone else's. For a small business trying to stand out in a crowded market, that's a real cost, not just an aesthetic quibble. The suggestion is that businesses should use AI to generate drafts, options, and variations quickly, but rely on a human to make the final judgment calls about tone, humor, and what actually fits the brand.
This isn't a new idea in creative circles, but it's notable coming from Adobe, a company whose products sit at the center of how small businesses actually produce marketing material. Adobe has spent the last two years layering generative AI (Firefly, AI-assisted editing in Photoshop and Premiere) into its core software, which means it has a direct commercial interest in customers trusting AI-assisted workflows. Framing the technology as a tool for taste rather than a replacement for it is also a hedge against the criticism that AI content is flooding the internet with interchangeable copy.
The timing tracks with a broader shift among marketing and design platforms. Canva, Jasper, and HubSpot have all rolled out some version of a brand voice or style profile feature over the past year, letting businesses feed in past content so AI outputs match an established tone. The pattern suggests the industry has recognized that generic AI output is becoming a liability, not a selling point, and vendors are scrambling to sell the fix.
For small businesses, this fits into a larger reckoning happening across content marketing. Search engines and social platforms have both signaled, in different ways, that they're deprioritizing content that reads as mass-produced or low-effort AI filler. Google's search updates and several social algorithm changes over the past year have specifically targeted content with no distinct point of view. The practical effect is that generic AI content isn't just uninspired — it can actively underperform.
What this means day to day: a small business using AI for blog posts, ad copy, or social captions should treat the first draft as a starting point, not a finished product. That means keeping a running document of phrases, jokes, and framing that sound like the business, and feeding that context into whatever tool is being used — most major platforms now support some version of this. It also means budgeting actual human time for editing, even if the goal of using AI was to save time.
There's a cost trade-off here worth naming. Skipping the editing step is faster and cheaper in the short term, but the risk is content that blends into the background and does little to build brand recognition. Investing the extra time or hiring a part-time editor to review AI drafts costs money now, but it's the difference between AI as a shortcut and AI as a crutch.
Watch for how brand voice and style-training features get priced going forward. Several platforms currently include basic brand voice tools in mid-tier plans, but as these features mature, there's a reasonable chance they migrate to premium tiers, following the standard pattern of software companies moving from free trial to paywall once a feature proves popular.
The bottom line: AI tools can speed up marketing production, but the tools themselves won't create a distinct brand voice — that still requires deliberate human editing, reference material, and time that businesses need to plan for rather than assume away.