Trust Recession: AI in Marketing & Advertising
Updated: Oct 21
Introduction: The Trust Recession Defined
We live in a world where all the information we could ever need is at our fingertips. We can check just about any fact we need at the speed of typing. This wealth of knowledge should boost our confidence in what we read and hear, right?
Not quite.
For brands, the trust problem is practical: readers need a reason to believe what they see. AI makes it easy to produce more content, but volume does not establish accuracy or expertise. When a claim has no clear source, the reader is left to decide whether to trust it.
Let's dive into what’s at stake, why the Trust Recession is happening, what it means, and how you can turn it to your advantage.
Why is the Trust Recession Happening?
1. Saturation of AI-Generated Marketing Content
One major reason people are switching off from AI-generated content is the sheer volume produced. Every brand, creator, and even casual users can churn out incredible amounts of content at an unprecedented scale. However, the main problem is:
Most of it is subpar.
There is increasingly little care or attention paid to what is being published. The focus is more on how much can be produced and how quickly. This trend undermines two essential qualities of great content: quality and accuracy. Everything is starting to look and sound the same, as Large Language Models (LLMs) generate similar sets of words in similar orders about any given topic.
This has led to consumer fatigue, where everything you read appears monotonous. It’s like an echo chamber, with an increasing number of voices shouting the same things. It’s enough to give anyone a headache.
Sometimes, more does not equal better.
2. Errors, Inaccuracies, and Hallucinations
With less oversight and original writing, we’re at the mercy of machines. Luckily, these super-intelligent beings can process vast amounts of information, so they can never be incorrect, right?
(Sometimes) Wrong!
LLMs can produce confident answers that contain factual errors. Treat generated material as a draft to check against reliable sources before it carries your brand's name.
A hallucination is a plausible-sounding but incorrect statement generated by an AI model. OpenAI's research explains why these errors can persist even as models improve. Read the source.
A convincing answer is not necessarily a correct one. Check quotations, figures and references against the original source before publishing them.
Tricky, eh?
3. Privacy, Data Concerns, and Misuse
You’ve crafted the perfect prompt, uploaded sensitive internal documents, and sent your chat off into the void. But where does that information actually go?
How your information is handled depends on the provider, product, contract and settings. Uploading a document does not automatically make it public or available to other users. For example, OpenAI states that ChatGPT Business, ChatGPT Enterprise and API data are not used to train its models by default. Read the source.
Before using a tool for client work, check its retention policy, training settings and access controls. Use only services approved by your organisation for the information involved.
Do not upload confidential material until you know which protections apply.
Consequences / What’s at Risk
Why should you care? If your brand publishes inaccurate claims or cannot explain how it handles information, customers have a reason to question the rest of your message.
Brand reputation: An unsupported claim can make people question your expertise and the care behind your work.
Engagement: Repetitive or inaccurate content gives readers less reason to return or share it.
Purchase decisions: Buyers need credible information to judge whether your product or service fits their needs.
Accountability: Explain where AI is used when that information matters to the audience, and check the rules that apply to your sector.
Internal quality: Give someone responsibility for checking the work before it is published.
Radical Honesty: Turning the Trust Recession on its Head
So, where does that leave us? When people question your message, more polish alone will not answer their concerns.
Radical honesty gives you a practical starting point: say what you know, acknowledge what you got wrong, and explain what you will do about it.
Radical honesty goes beyond a privacy slogan in the footer. It means being clear about your processes, limitations and mistakes, then backing that explanation with action.
Why Radical Honesty Works
Here are three ways to put that approach into practice:
Show who is responsible: Put a real name and relevant expertise behind the work, and make corrections visible.
Be specific about limitations: Explain what a product can do, where it is unsuitable and what evidence supports your claims.
Show what changed: Domino's described its late-2009 Pizza Turnaround campaign as the start of a more transparent approach to its advertising. It is an example of making the response to criticism part of the message. It does not establish that honesty alone caused a particular sales result. Read the source.
Clear communication cannot prevent a crisis or guarantee forgiveness. It can tell people what happened, what you are doing now and when they will hear from you again.
Some Inspiration for You (What Does Radical Honesty Look Like?)
Patagonia: Its 2011 Don't Buy This Jacket advertisement asked readers to consider the environmental cost of a purchase. The message reflects the company's stated position on consumption. It does not establish that the advertisement caused a particular sales increase. Read the source.
Everlane: The brand describes its approach as Radical Transparency, sharing information about production and costs. That gives customers specific information to examine rather than asking them to accept a general quality claim. Read the source.
Buffer: The company publishes its salary table and explains its pay approach. This makes its commitment to transparency visible and open to scrutiny. Read the source.
REI: The retailer began closing its stores on Black Friday in 2015 and made the commitment permanent in 2022. Its OptOutside initiative turns an outdoor-lifestyle message into a concrete business decision. Read the source.
Start with the claims you already publish. Keep the ones you can support, correct the ones you cannot, and make it easy for readers to find the evidence.
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