Over the past couple of months, we’ve explored a subject that’s top of mind for most marketers: how artificial Intelligence (AI) can enhance the “know, like, trust” factor with customers. In our last blog, we covered the “Like” factor — particularly how AI can help brands deepen customer relationships by connecting with people at an emotional level.

With growing data privacy restrictions, pressures to perform at lower costs, and incredible breakthroughs in AI technology, marketers are eager to put AI to work. Not surprisingly, accelerating the move to new digital technologies or platforms ranked as the highest CMO priority for 2023. In this final of a three-part series, we look at how AI can enhance the “trust” factor with customers.

AI’s data collection and privacy capabilities make it a strong trust-building solution.

One of the top ways AI helps build customer trust is through personalization. AI can tailor content to suit each customer’s unique needs using data from customer interactions, behaviors, and preferences.

Another area of strength for AI is customer service, where AI-powered chatbots or virtual assistants can provide faster, more efficient customer service and prompt solutions to customer problems.

Perhaps the most compelling use case for AI in trust-building is data security. AI technology can detect, identify, and address security issues much faster than manual solutions, reducing the risk of data loss or misuse. By developing a reputation for keeping customer data safe, you can enhance customer trust, improve your brand reputation, and potentially increase your customer base.

AI’s quirks can also quickly erode customers’ trust in a brand.

Despite the advantages, there’s a downside to AI that every marketer must weigh. AI can misbehave while performing marketing tasks, such as wrongly predicting a user’s interests or overlooking a key demographic. Inaccurate personalization, inappropriate ad targeting, and insufficient data transparency are a few of the AI issues that can lead to customer frustration or outright mistrust of a brand.

The potential issues can go even deeper. Several years ago, Amazon scrapped an AI-powered resume analyzing tool that had been trained to identify desirable candidates for technical roles. Pre-existing biases in the training data caused it to systematically reduce the number of female candidates for those roles. Not great for trust-building.

Although AI technology has evolved considerably since then, a more recent example underscores the ongoing struggle. The unveiling of Bard, Google’s equivalent of ChatGPT, demonstrated the damage that can occur when AI goes off the rails: Parent company Alphabet dropped about $100 billion in value after the chatbot made a high-profile blunder. The adage that it takes a long time to build trust and only a moment to knock it down applies.

To secure customers’ trust, keep AI in check.

Gartner predicts that by 2025, 70% of enterprise CMOs will rank accountability for ethical AI among their top concerns — and that by 2027, 80% of enterprise marketers will create content authenticity teams to combat misinformation. These trends show that, as always, marketing is moving ahead of the potential issues.

To mitigate the drawbacks of AI, make human oversight a mandatory part of your strategy. This will help ensure that algorithms operate ethically and transparently. And prioritize diversifying your data sets to ensure that small errors don’t grow into massive, ingrained biases.

Automation bias — the tendency to rely too heavily on machine-generated decisions — can undermine the best-laid marketing plans. But with the right human guardrails in place, AI can help you build customer trust, retention, and revenue.

If you’d like to learn more about how you can harness the power of AI to build trust with clients, talk to one of our archers.