• 2 min read
AI Hype Is Over as Trust Becomes the Real Test
Calling a product AI-powered no longer stands out. The next fight is proving systems are useful, safe, and governed responsibly.
Image: TechRadar
The “AI-powered” label has lost its punch. What once helped companies look cutting-edge now feels as routine as saying they have a website.
That shift, argued by the founder and CEO of Drofa Comms in a TechRadar Pro Perspectives piece, marks a new phase for the industry. Early AI companies had to persuade people the technology was real and workable. Now the harder task is showing that a specific use of AI is trustworthy, useful, and worth attention in an already crowded market.
Over the last two years, the money has surged. Enterprise spending on gen AI rose from $11.5 billion in 2024 to $37 billion in 2025 — a 220% year-over-year increase. But public familiarity has risen too. People have now used these tools, seen hallucinations, received bad recommendations, and learned that AI can be helpful while still being unreliable.
That changes the core question. It is no longer whether a company uses AI, but what its AI actually improves for customers.
For financial services and fintech, that standard is even tougher because the product is built on trust. Users might forgive an entertainment app for making odd mistakes, but not a system handling their money or personal data. The article points to a clear trust gap: only 13% of consumers truly trust AI systems, while about 30% remain neutral rather than confident.
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Trust, oversight, and explainability
The piece argues that companies are also undermining trust themselves by deploying AI before putting proper controls in place. A recent McKinsey survey found that less than 15% of organizations secure full security and IT approval before deploying AI agents.
That makes transparency and governance more than compliance chores; they are becoming part of the product itself. Companies need to explain where their models work well, where they fall short, what safeguards exist, and when humans remain involved.
According to the author, this kind of clarity is no longer optional. Explainability, auditability, and visible responsibility frameworks are becoming some of the strongest trust signals a business can offer — especially as AI shifts from a marketing line to core operational infrastructure.
The market is no longer asking who uses AI. It is asking who can use it responsibly.
Enterprise Editor
Marcus follows the money. He covers enterprise software, cloud architecture, and the tectonic shifts in Big Tech strategy. He translates dense earnings calls and complex M&A activity into actionable insights about where the industry is actually heading. If a tech giant makes a silent pivot, Marcus is usually the first to notice.
via TechRadar
