What's behind the disconnect splitting the AI narrative?

While artificial intelligence (AI) has increasingly become an indispensable element of daily life, its integration has sparked intense human anxiety over tangible risks such as data privacy violations and the erosion of digital security.  

However, a profound disconnect has emerged between what the media portrays as frightening and what the public actually fears. According to the latest report from media intelligence firm CARMA, the dominant press narrative surrounding AI remains overwhelmingly positive, with 57% of all global coverage characterised by optimism focused on massive commercial investments, operational efficiencies, and breakthrough innovations.  

While journalists are slowly increasing their scrutiny, media fears tend to dwell on abstract concepts such as the philosophical loss of human control, automation's existential threat, and the rapid rise of AI-assisted content creation. 

This corporate-driven optimism often masks a growing consumer backlash against algorithmic integration. In conversation with MARKETING-INTERACTIVE, Hanks Lee, general manager of corporate communications and corporate services at the Construction Industry Council, noted that public paranoia is a completely natural reaction to the recent rise in AI-driven fraud. 

“Audiences aren't just passively consuming content anymore; they put on the lens of scrutiny, and criticise publicly on social media if they don’t feel right about it. This means genuine storytelling is getting caught in the crossfire. No brand is immune.” 

On the agency front, Red Surtida, Burson’s APAC head of intelligence and transformation, said the gap between media optimism and public sentiment isn't surprising. “Media covers AI through the lens of investment, innovation, and business transformation. The public judge it by whether it actually helps them or does it create new problems.” 

Surtida emphasised that while the majority of industry conversation remains fixated on future upsides such as productivity, growth, and competitive edge, corporate credibility cannot be built on future promises.  

“People are forming opinions based on what they've already seen: misinformation, scam calls that sound disturbingly human, privacy erosion, the question of whether their role still exists in three years. You can't talk someone out of those concerns with a slide deck about potential.” 

A common strategic blind spot is treating media sentiment as a proxy for trust, according to Sofia Yip, head of brand, Gen Z Lab APAC, Edelman. “Visibility may be strong, but stakeholder confidence is often far more uneven. When strategies are built around coverage alone, brands risk optimising for awareness at the expense of credibility. Brands need to pressure-test the narrative beyond media, because any disconnect is not a reporting nuance, it is a signal to act.” 

What can the government do?

To bridge this divide, industry experts argue that the metrics for deployment must fundamentally shift. Lee noted that while there is absolutely a place for AI in production, communicators must draw a hard line, using a simple ultimate test before deploying any AI asset: whether it helps build or defend trust.

Trust is non-negotiable. If an AI content jeopardises your brand's trust, you shouldn't be using it. 

"It circles back to why do we want to engage , and what really works - it’s always the authentic contents and If the audience doesn't feel a genuine human pulse behind your campaign, they will instantly disconnect. In the AI era, our primary job isn't just to innovate—it’s also to be guardians of truth."

Surtida clarified that this public hesitation is not an outright rejection of technology, but rather a gap between what has been promised and what has actually been proven.

"As AI gets deeper into everyday products and workflows, organisations need to stop explaining what AI can do and start showing what it already does, for real people, in ways they can verify. The AI industry has done an excellent job communicating possibility. The next challenge is communicating proof.”

This requirement for proof extends heavily into the regulatory space. David Ko, lead advisor at Humantize, suggested that governments can narrow this public-media gap by pivoting away from abstract AI boosterism or generic alarmism toward concrete protections and active civic participation.

Crucially, policymakers should involve unions, civil society and technical experts in shaping regulation, not just large vendors, he added. "When people see credible guardrails, enforcement capacity, and a path to adapt their skills, they are more likely to trust AI deployments and less likely to view every new project as a threat."

While many fall into the AI layoff paradox, using AI as a blanket rationale for headcount reductions, Carbo Yu, regional executive director, Sinclair, said authorities should turn ethics into operations by setting and honouring privacy and security standards, adopting content authenticity and investing in workforce transitions with real re-skilling and redeployment paths.

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