Why Radical Honesty And Building Trust Are Essential To AI’s Future

This voice experience is generated by AI. Learn more.This voice experience is generated by AI. Learn more.Dirk Wakeham is the President and CEO of Realpage, a leader in property management technology.

gettyCurrent social media trends suggest that AI will either steal jobs or end the world. TikTok and Instagram posts warn, “Enjoy your last real year of meaningful work,” and joke that Terminator 2 was a documentary. The recent call by AI leaders to slow down development has only amplified the doomsayers.

What drives these dreadful predictions? Tech giants promised utopia for two decades while harvesting data, trapping users in walled gardens and disregarding social fallout in the AI era. Public cynicism was inevitable.​

The tech industry can solve its problems only by embracing a rarely used strategy: radical honesty and building trust. ​

Building trust means a company and its executives must do what they say and be transparent in their vision for AI. If it’s meant to replace humans, then they should say it. If it’s meant to work with humans and make their jobs easier, they must say that, too.

Technology companies must commit to this if they want to survive public mistrust and regulatory crackdowns. ​​

AI didn’t create tech’s trust issue; it merely amplified it, and its rapid growth has only deepened the mistrust.

For years, software companies hid behind opaque terms of service and grew more secretive. Now, as they ask for trust in autonomous decisions and generative media, the public is pushing back.​​

Building trust and radical honesty are essential as these tech companies roll out AI, because prioritizing ethics and consumer privacy allows users to understand what this technology means for them.

Building trust often means implementing responsible AI best practices, which starts with the technology itself. Then, demonstrating cultural change that is fully integrated across organizations will speak louder than policy statements.​

Radical honesty requires companies to communicate concretely how AI will benefit people, rather than hide behind buzzwords. This approach involves clearly disclosing which user data is involved and how it will be used, making trust the foundation of robust AI strategies.​​

You don’t build trust by claiming your software works magically. Trust comes from transparency. When I took over as the CEO of Realpage, we had a trust problem. I joined Realpage as we were settling with the Department of Justice. We had intentionally designed our software to comply with the law, and we ultimately settled with no findings or admissions of wrongdoing. But our customers, employees and the market didn’t trust the company.​

One of the very first things I did as CEO was undertake a listening tour, where I heard honest, open and sometimes difficult feedback from our customers and employees. I used that feedback to serve our customers better. This led to critical incidents falling 20%, time to resolve down a third and a chronic backlog down from a third at its peak.

The listening I did, followed by the action we took, showed that we, as a company, can be trusted again because we followed through on our word.​

In a competitive market, trust can be the ultimate differentiator, with 88% of consumers in recent Edelman research saying that trust is important or even a dealbreaker.

Trust, therefore, must become part of a tech company’s daily operations. It must become their operating system. Every release, renewal, forecast and one-on-one either deposits trust or withdraws it. ​

To live this at Realpage, we instituted the five principles to ensure our AI inspires trust:​

• AI is designed to reason from industry-specific data and workflows rather than the open internet.

• Every metric carries a governed definition.

• Every recommendation is designed to show its work, including the inputs and guardrails.

• AI is built to operate within compliance frameworks with auditable actions.

• A person is always accountable for the decisions AI supports.

Other leaders should consider all of these principles when designing AI solutions, but the last one is probably the most important. AI carries the volume, people keep the judgment and the signature is always human.​​

I believe that companies that practice radical honesty and are truthful about AI’s complexity and imperfections will thrive in the long term. Reliability, ownership and better collaboration will define how trust shows up every day. Sales and customer success may be on the front lines, but every team and team member shapes the customer experience.​

Some of these AI systems will fail in ways we can’t yet imagine. In those situations, when you open doors and admit blind spots, you become less of a target. Hide, and you guarantee heavy regulation by those unfamiliar with your technology.​​​

While AI will not eliminate all jobs or cause apocalyptic outcomes, the way forward depends on tech companies practicing radical honesty. This builds public trust and confidence about the future of AI.​​​ ​​

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