By Jim Misener, President, 50,000feet
As AI becomes integral to marketing and customer service, businesses face a paradox. On the one hand, consumers are enjoying improved convenience, personalization, and efficiency. On the other, AI exists beneath a cloud of consumer uncertainty and distrust. 57% of consumers believe AI poses a significant threat to their privacy, and 81% are concerned that companies might misuse their data.
This tension is evident in how consumers interact with AI today: while they may hesitate to embrace AI-driven applications, millions unknowingly benefit from them. For instance, Netflix’s personalized recommendations and Spotify’s curated playlists are powered by AI algorithms that enhance user experiences.
Despite this hesitancy, consumers are increasingly engaging with AI tools including ChatGPT, which receives approximately 3.6 billion monthly visits. This duality presents a challenge: how can brands build trust in AI while encouraging its adoption? The answer lies in thoughtful design and communication. Below are eight strategies businesses can use to bridge the trust gap and build meaningful relationships with their customers.
Open the Black Box
One of the most effective ways to build trust is by making AI systems more transparent. When businesses explain how AI works and why it makes certain decisions, they help demystify the technology for consumers. Adobe has taken a proactive approach by disclosing the datasets used to train its Firefly generative AI tools. This transparency informs users and reassures them that the technology is built responsibly.
Salesforce incorporates transparency into its AI-powered customer service tools by signaling when an AI model is uncertain about its answers. This candid acknowledgment of limitations allows users to make informed decisions and fosters confidence in the system.
Prioritize Fairness and Accountability
According to a YouGov survey, 62% of Americans do not trust AI to make ethical decisions, while 55% do not trust it to make unbiased decisions. This data creates a clear signal that businesses need to discuss how they make AI responsible.
Microsoft’s Responsible AI Standard shows how businesses can embed ethical principles, such as fairness, accountability, and inclusivity, into their technology development processes. Microsoft demonstrates a commitment to using AI responsibly by conducting regular audits to identify potential biases or risks.
IBM has also established a Center of Excellence for Generative AI, which focuses on creating frameworks that guide ethical deployment. These initiatives show how companies can align their technological advancements with societal values, addressing consumer concerns about bias or misuse.
It’s important to both make AI more responsible and discuss publicly actions to make AI more responsible.
Safeguard Data Privacy
Privacy remains one of the top concerns for consumers when interacting with AI, and many companies are showing that in fact AI can be used to protect privacy by stopping fraudulent activity and data breaches. This proactive approach prevents future issues and signals to customers that their data is being handled with care, and businesses would do well to discuss how they’re using AI this way.
In healthcare, Aetna uses machine learning for patient risk assessments while adhering to strict privacy regulations like HIPAA. By balancing innovation with robust safeguards, Aetna ensures that sensitive information remains secure, which is an essential step in earning consumer trust.
Bridge the Knowledge Gap
Sometimes. distrust stems from a lack of understanding. That’s not a consumer’s fault; it is up to brands to educate consumers about what AI can—and cannot—do. Apple offers workshops and online resources that help consumers navigate privacy settings and understand how their data is used within its ecosystem.
Lush takes a different approach by engaging customers in conversations about ethical technology use through social media campaigns. Through dialogue, Lush builds transparency and positions itself as a brand that values consumer input.
These efforts can help empower users to take control of their digital interactions.
Keep Humans in the Loop
While AI automation enhances efficiency, consumers often prefer knowing that humans remain involved in decision-making processes—especially in sensitive areas including healthcare or recruiting. Starmind combines human expertise with AI capabilities to ensure that critical decisions are validated by professionals. This hybrid model reassures users that human judgment remains central, even as automation simplifies routine tasks.
Ease into Change
Introducing new technologies incrementally can help consumers adapt without feeling overwhelmed. Brands can learn from effective employee communications. For instance, TELUS has rolled out generative AI tools gradually across its teams. This measured introduction has allowed employees to familiarize themselves with the technology while maintaining privacy controls—a strategy that saves time without compromising trust.
Listen to Feedback
There is no shortage of public data reporting consumers’ concerns about AI. Companies like Fiddler provide tools for monitoring real-time performance and refining algorithms based on user input. Unilever takes this further by conducting risk analyses for its AI projects, identifying potential ethical issues before they escalate.
These practices show businesses can and do collaborate with customers when designing trustworthy technologies.
Be Authentic
Authentic communication is about how businesses present themselves and their use of AI in a way that feels genuine and transparent. It’s not only about educating consumers but also about creating an emotional connection and trust through honesty in messaging.
For instance, OpenAI publishes detailed research papers on technologies like ChatGPT, outlining its capabilities and limitations. This openness builds trust within the broader community while encouraging informed engagement with the tools.
Authentic communication is about being truthful in a way that resonates emotionally with consumers. It involves sharing stories that reflect a brand’s values, admitting imperfections when necessary, and ensuring that AI-driven interactions feel human-centered rather than transactional.
Next Steps for Building Emotional Trust With Consumers
Where do you start designing experiences that build trust? Here are two recommendations (among many):
Start Small and Build Gradually
Rather than launching large-scale AI initiatives immediately, pilot smaller projects to test consumer reactions and refine their approach. Introducing an AI chatbot as a supplemental tool rather than a replacement for human customer service allows consumers to experience the benefits of AI without feeling overwhelmed or alienated. This approach also provides valuable feedback that can inform larger rollouts.
Experiment With Co-Creation
Involving consumers in the development of AI-powered products or services can build a sense of ownership and trust. Brands could invite users to participate in beta testing or provide input on features they’d like to see in future updates. This collaborative approach is an effective way to test whether you are on the right track.
Design AI Experiences With Empathy
One of the most powerful ways to build trust is to design with empathy. AI systems should be designed to reflect empathy and understanding of consumer needs. This involves not only tailoring interactions to individual preferences but also ensuring that responses feel human-like and considerate. The path forward requires balancing technological advancement with human connection. When you are empathetic, you can achieve this delicate balance by building trust alongside innovation.
