What the AI conversation is telling business leaders

It seems every business has something to say about AI but people are starting to tune out. Nearly six in ten believe companies exaggerate their use of AI, while almost half pay less attention to a message simply because AI is mentioned. What does cut through is evidence. 60 per cent responds positively when businesses link AI to measurable improvements in productivity, efficiency, accuracy or speed. 

This comes as AI stops being solely a technology story. Our analysis of more than 6,000 articles across 45 markets, which builds on an earlier analysis of 12,000 articles focused on prominent AI conversations, found the debate shifting towards who controls AI, who is accountable for it, and what it means for economies and geopolitics. Business leaders now need to show the benefits of AI and be open about the technology, partners and decisions behind it. 

From productivity story to power story 

Last year the dominant media narrative was straightforward: AI was a productivity miracle, driven by product launches, enterprise adoption figures and investment headlines.  

Now that hasn’t disappeared, productivity and efficiency remain the most widely covered benefits of AI, but the context around them as grown considerably more complex. 

By the first half of 2026, coverage of AI’s role in defence and geopolitics had surged. This was accelerated by the US-Iran conflict but rooted in a longer running competition between the USA and China. Topics around rivalry, access to critical AI infrastructure, export restrictions and the race for semiconductors accounted for two-thirds of all geopolitical coverage of AI. The debate moved from who can build the best model to who controls access to the infrastructure underneath it. 

Ongoing conflicts have put pressure on every part of the supply chain. A company’s reputation now extends to the partners it works with and the technology and infrastructure it relies on, as well as what it produces. 

The trust gap and what it means for reputational strategy 

Here is the part that should reassure some communicators and worry others in equal measure: public trust in AI is rising. It moved from 26% in 2025 to 30% in the first half of 2026, trust overtook excitement as the leading public response to AI. “AI as a trusted partner” narrative also grew in 2026, this could imply that audiences are receptive for messaging around transparency, governance, human augmentation and trust. With audiences starting to see it as a familiar part of everyday life, rather than a technology they’re dazzled by. 

However, trust signals within the media moved in the opposite direction, falling from 35% to 26% over the same period. That gap is why it matters to track both the press narrative and the online conversation where public sentiment gets expressed. Follow only one, and you get half the picture. 

Executive visibility is not the same as executive credibility 

When Amazon CEO Andy Jassy told employees that increased use of generative AI would eventually reduce the company’s corporate workforce, he gave a human consequence to the language of efficiency. At the start of this year, Amazon announced thousands of job cuts, making it easy for employees and the media to connect Amazon’s investment in AI with a smaller workforce, even where automation wasn’t the only factor behind the decision. 

As technology companies invest heavily in AI while cutting roles elsewhere, leaders can no longer talk about productivity without expecting questions about what it means for jobs. Media analysis reflects that tension. 11% of CEO commentary on AI touched on job cuts, and more than half of that was negative, compared with just 18% that was positive. CEOs may have generated close to a third of all AI commentary and attracted the most positive coverage overall, but their optimism carried less weight with audiences than the more balanced views offered by academics and journalists. 

For leaders, the answer is not to find a trusted third party to endorse the company’s position. It’s about communicating openly when AI will change roles, what support or retraining will be available, and which decisions will remain in human hands. Independent academic and technical experts can add value when they are involved early enough to test the company’s assumptions and challenge its approach, rather than being brought in to validate decisions that have already been made. 

 AI has a generational credibility problem 

The research found a clear generational divide in attitudes towards AI. Under-20s and over-60s were the most likely to express fear, while individuals between those age groups were largely enthusiastic. This could create a blind spot for businesses whose AI strategies are developed by people who feel more comfortable with the technology. 

For younger audiences, the concerns are immediate. Coverage of AI’s effects on employment, education and mental wellbeing was overwhelmingly negative, while job losses were the single biggest concern among respondents under 20. Separate research found that hope in AI among Gen Z in the US had fallen from 27% to 18% in a year, with almost half of young workers believing its risks outweigh its benefits. 

This can affect whether a graduate applies for a role, how an employee responds to new technology and whether a customer trusts an AI-supported service. Older audiences may have different questions, including whether human support will remain available and how their data will be used. 

Leaders should therefore resist treating enthusiasm within their own organisation as evidence that every audience feels the same. Communication needs to begin with the concerns each group is likely to have, from job security and career development to privacy and access to human support and explain what the business is doing about them. 

What this adds up to 

None of this suggests AI is losing ground as a business story. Opportunity still outweighs risk in media coverage by a wide margin, and productivity narratives are still holding up, even as coverage moves past the initial hype. But business leaders should take three things from this. 

First, transparency. Being upfront about how and why AI is used gives companies the chance to reassure stakeholders before problems arise, rather than responding after the fact. 

Second, stay attuned to how the conversation is fragmenting. As opinion splits by age and platform, a single-channel view of your reputation won’t tell you much. Track perception across multiple platforms to understand how your business specifically is being read, and where it sits in the wider AI conversation. 

Third, be specific. Differentiation matters more now that most businesses claim some AI involvement. Without clear specifics on what the AI does and why it’s trustworthy, customers can’t tell a genuine capability from a company simply following the trend, and that ambiguity erodes trust in responsible use.