Marketers rapidly embrace AI despite consumer distrust
Marketing teams are moving fast with AI. They’re using it to understand customers, predict trends, and personalize at scale. Inside most companies, that looks like success, 93% of marketers say AI helps them understand their audience better. But from the customer side, the picture isn’t as bright. Only 53% believe brands actually understand what they want. That’s a serious trust gap, and it’s growing as AI spreads across more parts of the customer experience.
This gap matters. Technology can’t fix perception on its own. Executives should focus on closing the loop between how teams use AI and how customers experience it. The real goal isn’t just smarter automation, it’s alignment. If customers feel brands are guessing rather than listening, engagement suffers, no matter how advanced the tech may be. AI is already part of the infrastructure. What’s missing is confidence that it’s being used for the benefit of both sides.
For leaders, this moment calls for balance. Rapid adoption is good, but trust compounds over time. Transparency about how AI decisions are made, and clarity on how it improves customer outcomes, will define the companies that scale successfully.
According to Braze’s Global Customer Engagement Review 2026, 93% of marketers say AI enhances their understanding of customers, while only 53% of consumers agree that brands meet their expectations. Numbers like that show the work still ahead.
Emergence of AI intermediaries as a new engagement layer
Consumers are starting to use AI “agents” to interface with brands. These aren’t brand-owned tools; they sit in between, helping users manage choices, make recommendations, and cut through digital clutter. Right now, 19% of consumers report using AI intermediaries, but Braze forecasts that this could climb to 46% within a year. That’s a steep rise, and it’s coming fast.
This shift changes the basic rules of customer engagement. Marketers will no longer compete just for human attention but also for AI interpretation. When an AI agent becomes a user’s primary interface, how it ranks, explains, and recommends a brand becomes critical. Visibility in this new layer will decide whether a brand gets noticed or ignored.
Executives need to plan for this now. Optimizing for an algorithm, an AI assistant, or a recommendation engine is not about tricks, it’s about clarity of value and consistent data integrity. In this environment, precision in communication and ethical data handling will determine which brands AI agents trust and promote.
As Braze’s 2026 report predicts, consumer use of AI intermediaries could surge from 19% to 46% within twelve months, a clear signal to marketers and business leaders that consumer interaction models are evolving faster than most companies are prepared for. The smart move now is to make sure your brand is easy for both humans and machines to trust.
Consumer trust as a strategic imperative for AI-driven personalization
AI has improved how companies process customer data and deliver tailored experiences. But the real challenge is not technical, it’s emotional. Most consumers still don’t trust that brands use AI in their interest. More than half believe that businesses deploy AI mainly to drive profit, not to improve customer experiences. This perception reduces the effectiveness of advanced personalization and makes every interaction feel less authentic.
Executives should look beyond system performance metrics and focus on transparency. Customers expect clear communication about how their data is used and how AI enhances what they receive. When brands show direct benefits, faster responses, accurate recommendations, fewer irrelevant messages, they turn suspicion into confidence. This is no longer a marketing preference; it’s a competitive advantage.
Leaders must also ensure governance keeps pace with innovation. Data practices should be clearly outlined and auditable, from consent to algorithmic decision-making. Trust cannot be outsourced or guessed. It must be built deliberately, through responsible design and consistent accountability. Without that, even the smartest AI systems risk becoming background noise that customers ignore.
Future scenarios indicate divergent paths for AI engagement
The Braze Global Customer Engagement Review 2026 outlines four possible futures for AI in marketing, each depending on how trust evolves. The best-case scenario is one where AI agents are central and trusted, creating highly personalized, valuable experiences. The second sees technical improvement without public trust, resulting in slower adoption and muted returns. A third outcome involves an innovation plateau, where progress stabilizes and differentiation relies on human creativity rather than AI. The final, and most negative, possibility is a widespread rejection of AI-led engagement, pushing brands to scale back or reset expectations.
Today’s reality sits in a high-capability, low-trust zone. Marketers have the tools, but customers are cautious. For executives, this landscape demands deliberate, long-term planning. Strategic foresight, not speed, is what determines which future your organization falls into. Building ethical frameworks, integrating transparent communication, and continually measuring sentiment should all be part of that roadmap.
AI will keep advancing, whether trust catches up or not. The companies that commit early to transparency, deliver real value, and minimize uncertainty will define what successful AI engagement looks like in the next decade. The technology is strong; now it needs human-led credibility to match.
Transparency and demonstrated consumer value as the cornerstones for future success
AI adoption has reached a stage where efficiency alone no longer impresses customers. What matters is clear evidence that technology is improving their daily interactions with brands. Executives should focus on showing real outcomes, faster support, more relevant offers, and cleaner communication across platforms. Customers must see that technology is being used to simplify their experience, not to gather data without clear benefit.
Transparency must evolve beyond compliance checkboxes. It should become a consistent practice that strengthens trust at every touchpoint. That includes clear consent frameworks, detailed explanations of how data drives personalization, and visible commitment to responsible governance. Leaders who treat transparency as part of the product experience build credibility that compounds over time.
Governance also plays a major role here. It’s not enough for companies to claim responsible AI usage; they must be able to prove it through standardized processes and consistent communication. Executives should invest in ethical oversight structures that verify the outcomes of AI-driven engagement. This ensures both regulators and consumers see measurable accountability.
The next stage of AI-driven growth will not depend on bigger datasets or faster algorithms, it will depend on how successfully brands demonstrate value to every user. When a company aligns customer trust, transparent operations, and real benefits, AI shifts from being a background function to a visible enabler of satisfaction and loyalty. In this environment, credibility is the foundation that allows innovation to scale.
Key takeaways for leaders
- AI adoption outpaces consumer trust: Marketers are quickly integrating AI to personalize experiences, but 93% believe they understand customers better while only 53% of consumers agree. Leaders should prioritize transparency and communication to align perception with performance.
- AI intermediaries reshape engagement: Consumer use of AI “agents” to interact with brands may rise from 19% to 46% within a year. Executives should prepare marketing strategies optimized for how AI systems interpret and recommend their brand.
- Trust is the foundation for AI-driven personalization: Over half of consumers suspect that brands use AI mainly for self-serving purposes. Leaders should focus on responsible data stewardship, visible benefits, and clear governance to sustain credibility.
- Future success depends on bridging capability and trust: The Braze Global Customer Engagement Review 2026 outlines scenarios ranging from trusted integration to AI rejection. Decision-makers must plan deliberately to build customer trust while scaling technical innovation.
- Transparency and clear value drive competitive advantage: Growth will rely on demonstrating tangible customer benefits, faster service, relevant recommendations, fewer irrelevant messages. Executives should institutionalize transparency and governance to make AI a trusted part of the customer experience.
