Despite the promise of greater efficiency, many business leaders remain uneasy about one critical aspect of artificial intelligence (AI) — trust. This skepticism is especially pronounced when it comes to AI-generated content — where accuracy, credibility, and the human connection are essential. That’s why building trust in AI doesn’t start with machines. It starts with expert human writers. In fact, trust in AI-generated content depends on expert human writers.
Understanding the need for expert human oversight of AI content begins with a closer look at how trust in AI is evolving worldwide. The varying levels of AI acceptance shape how AI-generated content is received and evaluated. This has direct implications for how brands build credibility, maintain transparency, and protect their reputations today.
Trust in AI Is in the News
Looking first at the global landscape for trust, the 2025 Edelman Trust Barometer noted that trust in AI can vary widely. In China, for example, 72% of people trust AI, but in the U.S., that number drops to 32%. This isn’t a difference in policy or regulation, according to the report, but is instead a reflection of how societies perceive risk, control, and opportunity. Some see AI as a force for progress, while others worry about its unintended consequences. But the disparity in trust doesn’t stop at national borders. Older adults, those with a lower-income, and women are less likely to trust AI.
Looking more closely at the U.S., a Brookings report noted that a large number of Americans harbor major doubts about AI, citing a 2025 survey from The Heartland Institute, where 72% of U.S. adults said they had concerns about AI. Among other issues, they worry about privacy, security, a lack of transparency, and racial and gender biases.
Interesting, amid all these issues, Rei Inamoto, founding partner of I&CO, wrote in Fast Company how trust has now become the primary currency for brand growth, surpassing traditional marketing and storytelling. He introduces a new take on the traditional marketing funnel by focusing on earning and building trust rather than the traditional top-down company builds, brand attracts, and customers buy the product.
These articles strike at the heart of the challenge paradox that must be navigated if we are to truly trust AI-generated content. Trust is a delicate balance, and it must be based upon transparency, accuracy, security, and the commitment to present unbiased information, even when dealing with sensitive or divisive subjects. When any one of those factors is hazy or disappears completely, our trust in AI erodes.
The Roots of Mistrust
The mistrust of AI has its roots in various factors. The one that I consider the most important is factual accuracy. Time and time again AI has generated factually inaccurate text (“hallucinations”). At the same time, AI can perpetuate biases because AI’s large language models (LLMs) are trained on vast datasets that may have inherent biases. They can absorb, amplify, and perpetuate those biases, leading to text that reinforces harmful stereotypes, propagates inaccurate information, narrows perspectives, and denies exposure to diverse ideas, such as the recent problems with Grok, the large language model woven into X, Elon Musk’s social network.
Another key issue is the lack of transparency and accountability in AI systems. Many of these models operate as “black boxes,” making it difficult to understand their decision-making processes fully, even by those that have designed and work with them. This opacity raises concerns about the potential for unintended consequences, errors, or even malicious exploitation.
Privacy and security risks are also a significant source of mistrust. As AI has become increasingly integrated into various aspects of our lives, there are legitimate concerns about the potential misuse of personal data and the vulnerability of these systems to cyberattacks or unauthorized access.
Trust in AI-Generated Content Still Depends on Expert Human Writers
Based on these factors, it is easy to see how this lack of trust in AI has serious implications for its adoption and utilization in generating content. Here are some of the key areas where this “trust deficit” can rear its ugly head:
Content Credibility: One of the most significant challenges is the perceived lack of credibility of AI-generated content. Many individuals remain skeptical about the accuracy, objectivity, and reliability of content produced by AI systems. This can range from consumers shopping online to industries where factual integrity is paramount, such as healthcare, law, journalism, and academic research.
Creative Industries: Creative industries like writing, design, and multimedia production are concerned about the potential for AI to undermine human creativity and originality. Because it’s actually just a pattern of words based on probability, AI-generated content lacks the authenticity and emotional resonance of human-created works. Writers in particular can face the inaccuracy of AI content checkers, which can flag original content as AI-produced and vice versa. All authors must be aware that their writings may be in a database that companies use to train their AI programs.
Brand Reputation: Companies that rely heavily on AI-generated content may face reputational risks if their audiences perceive the content as unreliable, biased, or off-brand. This can erode brand trust and damage customer relationships.
Legal and Ethical Considerations: The use of AI-generated content raises complex legal and ethical questions. These include copyright, intellectual property rights, and the liability for potentially harmful or inaccurate content generated by AI systems.
Expert Human AI Editors Overcome the ‘Trust Deficit’
To fully realize embrace generative AI content, it is crucial to address the underlying trust issues. Here are some strategies that can help bridge the trust gap:
Human Oversight and Fact-Checking: Implementing robust oversight and fact-checking by highly skilled human AI editors can mitigate the risks of inaccuracies or biases in AI-generated content. At the same time, they can produce clear, concise, and compelling messages that will resonate with their intended audiences. The collaboration between human experts and AI systems should leverage the strengths of both to produce higher quality content.
Transparency and Explainability: AI developers and companies need to prioritize transparency and explainability in their systems. By providing insights into the decision-making processes, data sources, and potential biases of AI models, human editors can better understand and evaluate the outputs.
Ethical AI Frameworks: The development and adoption of ethical AI frameworks, guidelines, and best practices can help ensure that AI systems are designed and deployed in a responsible and trustworthy manner. These frameworks should address issues such as fairness, accountability, privacy, and transparency. This in turn can help ensure that the editors reviewing AI-generated text are not exposed to any ethical issues or can be on heightened alert to eliminate them.
Continuous Improvement and Monitoring: AI systems need to be continuously monitored and updated to address emerging issues or biases. Regular audits, feedback loops, and improvements can help enhance the reliability and trustworthiness of AI-generated content over time. This will help to ensure higher quality AI-generated text, but it will still need experienced human editors to oversee the content to publication.
The Road Ahead
As generative AI continues to evolve and become more widely adopted, trust will continue to remain of paramount importance. I hope that the technological improvements promised by new and future AI models will help alleviate this distrust in AI. However, it is really up to the companies that are using AI to generate content. They need to make the commitment to employ highly skilled human AI editors to check any and all of their AI-generated content. They have too much at stake to avoid this crucial step in their AI workflows.
“It takes 20 years to build a reputation and five minutes to ruin it. If you think about that, you’ll do things differently.” — Warren Buffett
If you or your team is developing AI content and struggling with maintaining trust, I’m an AI content editing consultant that helps companies integrate expert editing into their AI workflows. Contact Randy Savicky at (203) 571-8151 or send me an email at randy@writingforhumans.co.
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