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AI is moving into nearly every part of marketing, from ad buying and email writing to team training. But alongside the opportunity comes a growing warning: if input data is poor, critical thinking is weak, or skills are not upgraded, AI can push budgets, performance, and decision quality off course.
The stories below show AI’s two-sided impact on marketers: it helps teams move faster, while also forcing businesses to do things more correctly.
Bad data is causing AI to spend ad budgets in the wrong places
MarTech warns that as automation now covers many advertising stages such as content creation, bidding, and delivery optimization, data has become the final “lever” but also an easily overlooked weakness. If the input signals are wrong, AI will learn those distortions and optimize for people who are not truly relevant.
The article highlights an important shift: in the past, faulty tracking mainly distorted reporting; in automated advertising environments, dirty data can directly send budgets to audience groups that do not deliver value. For marketers, this means checking data sources, the consistency of conversion tracking, and signal quality must be placed on par with, or even above, creative discussions.
Source: MarTech – Bad data is teaching AI to waste your ad budget
AI makes email marketing easier, but not automatically better
From MarTech’s perspective, AI is helping email marketing shed much of its routine workload: from subject line suggestions, drafting copy, and summarizing customer feedback to recommending segments and outlining nurture journeys. This is why many understaffed email teams are easily “persuaded” by AI’s convenience.
However, the article emphasizes one notable point: an email that “looks fine” does not necessarily convert. If marketers hand too much over to AI without editing, tone checks, and adjustments for brand context, campaigns can become safe, bland, and unconvincing. In other words, AI can shorten production time, but humans still need to take final responsibility for quality.
Source: MarTech – AI made email marketing easier. It needs us to make it better.
A MarTech reminder: don’t fall into “cognitive compliance” with AI
MarTech’s third article uses a rather interesting concept: “cognitive compliance,” meaning the habit of accepting AI output without questioning it. The author argues that when results are presented smoothly, professionally, and too quickly, people tend to trust them before they have time to verify them.
The worrying part is that this does not only affect a single answer. If marketing teams gradually become used to relying on AI for every decision, from positioning and content to analysis, independent critical thinking and source-checking skills will erode. This is an important reminder for every brand: AI should be a tool that supports thinking, not a replacement for it.
Source: MarTech – Why marketers need to push back against AI
Google: the AI skills gap is the real productivity challenge
In a post on the Google AI Blog, the company said the top 15% of AI users are seeing better results in performance reviews, salary increases, and time savings. But rather than treating that as a story about a small group, Google says the bigger issue is that the majority still lack the skills needed to use AI effectively.
Research data in the United Kingdom shows that AI adoption at work has risen sharply over the past year, but the pace is uneven across worker groups. The article’s main message is clear: if companies only deploy tools without investing in training, the productivity gap will continue to widen. For businesses, this is why AI training should not stop at “knowing how to use it,” but should move toward “knowing how to use it for the right task, in the right context.”
Source: Google AI Blog – Unlocking Britain’s next era of productivity: Building a nation of AI trailblazers
A perspective for the Vietnamese market
For Vietnamese marketers, these four stories point to a practical conclusion: AI does not create growth on its own, but amplifies the quality of the system already in place. If input data is not clean, campaigns are more likely to drift off target; if editing processes are weak, AI content will only be faster, not necessarily more effective; if teams lack the habit of verification, brands may pay the price in messaging mistakes and lost trust.
As Vietnamese businesses accelerate AI adoption, the priorities should be three things: standardizing marketing data, setting up review processes for AI output, and training staff to work with tools rather than depend on them. That is how AI can be turned from an “accelerator” into a sustainable competitive advantage.
Compiled and edited based on the international sources above.
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This article focuses on AI for marketers with a perspective for the Vietnamese market.
References
- Bad data is teaching AI to waste your ad budget
- AI made email marketing easier. It needs us to make it better.
- Why marketers need to push back against AI
- Unlocking Britain’s next era of productivity: Building a nation of AI trailblazers
