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Study Highlight: Message vs. The Machine

Study Highlight: Message vs. The Machine

We. Communications and USC Annenberg Center for Public Relations have released a new research report titled, "Message vs. The Machine". The study examines how communicators perceive AI’s impact on brand reputation, and the opportunities and challenges that come with it.

Awareness vs. Action
The rise of generative AI has led to the “zero-click search” phenomenon, where users rely on AI summaries instead of clicking through to websites. Communicators recognise the shift: 62 per cent believe that generative engine optimisation (GEO) - the practice of tailoring content for large language models - represents the biggest opportunity in communications since search.

However, skill and understanding lag behind awareness. Only 12 per cent of communicators strongly feel they understand how AI decides what information to present about their brands. Nearly half (49 per cent) say that if they were asked to review content for GEO today, they wouldn’t know where to begin.

According to the report, time and attention are key factors behind this gap. Rapid AI development, and economic or geopolitical pressures all contribute. Despite these challenges, the study notes that communicators still have a relative advantage in GEO compared to other business functions.

Measuring success in generative AI
The study identified another opportunity with the rise of generative AI: measuring AI prominence. The practice refers to establishing new KPIs to track how a brand appears in AI results

One approach is AI share-of-voice (AI SOV), a rough measure of how often a brand is mentioned in questions about its industry or competitors. When asked how their organisation monitors the accuracy of AI-generated brand content, the largest share of respondents (34 per cent) cited reliance on third-party tools or platforms, followed by 33 per cent who said they regularly query AI with brand-related prompts.

Yet measurement still trails recognition. Only 23 per cent of communicators say their organisation currently tracks how often they appear in AI output. Others are planning to do so (31 per cent), believe they should despite having no current plans (30 per cent), or have no plans at all (17 per cent). The study underscores that “you can’t optimise what you don’t measure,” highlighting the urgency of monitoring AI output.

New waves of crises and threats
AI introduces new forms of reputational risk, including misinformation, outdated content, and challenges around authority. A majority of respondents (64 per cent) believe AI-related reputational damage is a serious threat today, and another 64 per cent fear AI could amplify negative narratives.

Additional concerns include AI misrepresenting the brand or its values (58 per cent), AI rewriting or distorting carefully crafted messaging (60 per cent), and stakeholders potentially trusting AI over official communications (57 per cent).

These concerns are not hypothetical. 30 per cent of communicators say their organisation has already faced reputation issues due to AI-generated content, while 36 per cent report instances of AI providing inaccurate information about their products or services. Despite these risks, only 39 per cent feel prepared to correct or prevent AI-driven misinformation.

Key takeaways for communicators:

  • Learn what AI prioritises: Understand the sources AI cites for your industry and brand, and identify recurring narratives.
  • Track brand health in AI: Audit product and brand messaging in AI outputs regularly to ensure accuracy and consistency.
  • Strengthen authority and storytelling: Build strategies to influence authoritative sources and ensure repetition of your key narratives across credible outlets.
  • Prepare an AI-based crisis plan: Incorporate AI-driven risks into simulation exercises, and align responses across legal, C-suite, and other stakeholders.
  • Leverage this moment to drive communications value: Package GEO-related insights and demonstrate to stakeholders how communications can shape what AI says about the brand.
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Conducted by OnePoll on behalf of Sefiani, the research surveyed 150 marketing and communications leaders at Director level and above from organisations with more than 50 employees, exploring how strategies have been adapted in response to AI search.

According to the report, 91 per cent of cross-departmental leaders are revising their strategies to influence AI-driven discovery, although an internal "turf war" is emerging over who controls brands' AI search visibility. The research found that ownership currently sits across five functions: data / analytics (23 per cent), comms / corporate affairs (20 per cent), brand (19 per cent), digital (17 per cent), and performance (16 per cent), which the agency said reflects a structurally fragmented approach within many organisations.

The "silo" challenge
To complement its findings, Sefiani collected qualitative insights from leaders through a series of executive GEO-focused sessions and a recent panel moderated by Mandy Galmes, Managing Partner at Sefiani. Speakers included Johanna Lowe, Chief Marketing and Communications Officer at the University of Sydney; Brad Pogson, Head of Communications at Lendi Group; and Tom Telford, Chief Digital Officer at Clarity Global.

Based on these discussions, several themes emerged around managing reputation in AI-driven environments:

  • Internal silos as a key barrier: Participants noted that while some leaders are encouraging cross-functional experimentation, others remain 'nihilistic' about breaking down traditional departmental walls, leading to stalled effort and wasted budgets. The panel identified the rise of AI as a 'shadow task' layered on top of existing senior role requirements without removing previous duties, which further delays progress.
  • The forever life of reputational issues: According to panellists, LLMs draw on long-term patterns across coverage, reviews, forums, and owned content, meaning historic issues may continue resurfacing in AI-generated responses. This suggests that organisations might need to take a more data-led, cross-channel approach to finding, correcting, and rebalancing inaccurate information.
  • Quality content remains critical: Insights from the discussion indicated that AI models do not discriminate by content format, but they do reward depth. The findings suggest that high-quality, thought leadership content performs better within LLM training sets, so it should be considered as central to strategies across channels moving forward.

The cost of siloed GEO: Misinformation and reputational risk
The agency stated that a lack of clear ownership over GEO is already having tangible consequences. Based on the research, AI search was cited by leaders as the most structurally siloed channel, with 77 per cent reporting problems in the last 12 months. This included a slower response to issues, conflicting messages across channels, and AI tools amplifying yesterday's problems instead of today's narratives.

The study also found that the risk is compounded by the speed at which AI-generated misinformation can spread, with 25 per cent of leaders reporting that incorrect, inconsistent, or outdated brand information has already appeared in AI answers.

"Reputation used to be managed channel by channel, but AI search has changed the rules. Because these systems read across everything - earned coverage, on-site content, social signals, and search authority - siloed marketing and communications are quietly muting your AI visibility," said Tom Telford.

"When your channels don't tell the same story, or teams are chasing independent KPIs with separate budget pots, these silos also become a major reputational liability. It is only when functions are truly connected that the models become trained on a consistent brand message and compound visibility across AI services over time. This is the crux of GEO, Generative Engine Optimisation, and done well it becomes the multiplier on everything you already invest in brand, PR and digital."

The "citations race": PR and earned media take centre stage
The report also suggested that a shift toward AI-first discovery is changing budget priorities.

According to the findings, 49 per cent of leaders have already allocated five to 10 per cent of their marketing and communications budgets to AI visibility, with 90 per cent of that spend being reallocated from traditional channels like paid digital and brand. A further 30 per cent reported allocating up to 20 per cent of their budgets.

Citing external analysis from Gartner, the agency noted that the majority of sources referenced by AI systems are non-paid, which the report argues increases the strategic importance of PR and earned media in AI-driven discovery.

Mandy Galmes said: "When LLMs answer a question in your category, they’re drawing overwhelmingly on non-paid, third party sources. If your spokespeople, experts, case studies and proof points aren’t in those sources, you’re invisible at a key moment in the buyer journey." 

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