Marketing has to be data-driven.
The average marketing team now juggles several analytics tools, often without realizing their full potential. And marketers who use AI tools without a second thought can end up using compromised data in ways that undermine consumer confidence.
As marketers race to deploy AI-powered tools for personalization, segmentation, and content creation, they must remember that their effectiveness depends entirely on the quality and quantity of consumer data and on how they use it.
Consumers are paying attention, and they’re looking for a new kind of trust at a time when AI is quickly becoming an antitrust signal, even though it doesn’t have to be.
Balancing AI value with a new kind of trust
A number of studies have found consumer confidence drops when AI is used in marketing. However, research has found surprising reasons for this.
The Nuremberg Institute for Market Decisions recently asked 600 marketers if they were using AI in their activities, and 100% of them were. That’s understandable. It’s hard to resist tools that promise to exponentially boost efficiency and increase quality in the customer journey.
But optimization isn’t everything, and neither is transparency. Simply labeling content as AI-generated can actually hurt its performance. The study found that when people knew an ad was made by AI, it reduced trust, undermined engagement, and dampened enthusiasm around it. Skepticism spiked, despite the honest messaging.
This is partly because brands aren’t building trust in the right areas. Acknowledging the use of AI is one element, but it’s more important to be transparent about things like how it uses consumer data.
Organizations expanding their use of AI across marketing and customer-facing initiatives are running up against this tension between AI innovation and responsible data practices.
One example is EY, which supports clients in different business sectors. The global professional services firm is already highlighting ethics, pragmatism, and human-centered deployment as key elements of its artificial intelligence consulting services. The firm advises companies to see AI use as inherently about building trust through ethical use.
That reflects the growing importance of implementing AI in ways that drive business value while maintaining trust that the data it uses is managed ethically. Brands that fail to establish trust in their transparent data practices risk limiting the effectiveness of their AI investments, despite gains in efficiency.
Translating transparency into trust
Although there are risks associated with the use of consumer data in AI marketing, it isn’t all bad news.
Research shows AI can build trust, too. Not surprisingly, the key here is a combination of transparency and intention about the data in use. For instance, payment platforms can use AI to detect and prevent fraud in real-time. This type of feature can reassure consumers about the platform’s safety.
The reckless use of AI to cut corners risks destroying trust. However, thoughtful use of AI under human guidance can increase it.
Building trust in this way benefits companies by strengthening customer relationships and enabling more successful, efficient AI-driven marketing strategies. It all starts with the right kind of transparency. Here are ways to do that:
- Start with security. Share clear summaries of privacy safeguards, security practices, and related areas where you use customer data.
- Always offer data preferences so consumers can understand how they’re allowing AI to guide their customer journeys.
- Don’t just explain that something is AI-generated. Clarify what data was collected and why it improved a person’s overall experience.
- Regularly audit your AI models for bias, accuracy, unintended consequences, and hallucinations.
- Ask your customers what they think. Invite feedback on AI experiences, data visibility, and any other areas where customer trust might erode during AI interactions.
Consumer data trust in the AI age
Trust is and has always been the cornerstone of good marketing. With AI, that means focusing more on the data behind the AI rather than the tool itself.
Labeling content as AI-generated is a good starting point, but it’s not enough. Take the extra step and communicate with customers how you’re using their data with your AI tools. Give them preferences, lay out security features, and make sure to treat every consumer interaction as a chance to prove that you’re using AI the right way. They’ll trust you more for it.
The post Consumer distrust of AI isn’t all about the AI appeared first on MarTech.