I was recently invited to join a panel hosted by media monitoring and analytics company Vuelio on how AI is changing the information landscape and how communications professionals can factor these changes - and the uncertainty they create - into their strategies.
The session was chaired by Pulsar Group’s Head of Content Marketing Alex Bryson and brought together – alongside me – Pearson’s Director of Financial Communications Laura Ewart and Vuelio’s Head of Insights Strategy Amy Chappell. It was a timely discussion because, while AI is often framed as a disruptive force, I think its most immediate impact is more subtle: AI is not necessarily bringing about a paradigm change for communications, at least not yet. It is, however, a powerful accelerant.
AI as an accelerant
Many of the dynamics we associate with AI-enabled communications have been developing for years: faster story cycles, more fragmented audiences, less predictable patterns in which messages travel, and a declining reliance on traditional gatekeepers. AI is intensifying and sometimes exacerbating all of these trends.
The recently published Digital News Report, from Oxford’s Reuters Institute for the Study of Journalism, provides useful context. Its latest findings point to a continuing decline in engagement with traditional media sources, alongside growing reliance on social media; additionally, growing concerns about misinformation, trust in news, news avoidance all add to a highly volatile picture. In other words, the information environment was already fragmenting before generative AI became a mainstream concern.
One concept I raised during the panel was the idea of ‘context collapse.’ Messages that would once have been mediated through a relatively limited number of mass media channels are now travelling directly and unpredictably across platforms, reaching multiple overlapping communities and audiences. They can be reinterpreted, reframed, and redistributed at speed.
This makes communications strategy harder. It creates fertile ground for misinformation and disinformation to proliferate, while LLMs now insert additional layers of interpretation between organisations and the people they are trying to reach.
Organisations therefore need a clear understanding of where they are appearing, how their messages are being interpreted, and which voices or sources are shaping stakeholder perceptions.
AI as a new stakeholder
Another interesting point we discussed was whether AI should be treated as an audience in its own right. AI tools are already mediating information for users, summarising content, prioritising sources, and packaging answers for audiences: this has important implications for reputation management, because the signals AI systems draw from can shape how organisations are understood.
While communicators may increasingly need to consider LLMs as a new audience, the underlying objective remains familiar: establishing authority and ensuring that people can access trustworthy, relevant information in a noisy, synthetic information environment. That is why earned media, credible commentary, and authentic human voices become even more important in an AI-mediated world. They help establish authority with both human audiences and the systems increasingly shaping what those audiences see, hear, and trust.
Embedding intelligence into comms
My view is that the most pressing practical challenge for comms professionals is to gather enough evidence to build a baseline and understand this new landscape.
Communications teams should start by mapping how their organisation, brands, and products currently appear in AI-generated search and answer environments This means understanding which sources are being cited by LLMs, assessing their accuracy, identifying and addressing any gaps in the information ecosystem.
Communications professionals have navigated similar shifts before: the rise of digital news, the growth of social media, and the move toward visual and creator-led content all forced organisations to rethink how they measure influence, reputation, and trust. AI represents another such inflection point, requiring a fresh benchmark for understanding how information is discovered, interpreted, and acted upon.
This is where communications can become (even) more intelligence-led. There is an opportunity to understand and shape the dynamics of trust more holistically, and AI can play a role in this too, helping insight and comms professionals achieve more, and more efficiently.
AI-powered intelligence can help sift through signals to predict what’s around the corner for organisations; it can help turn that knowledge to power culturally relevant and impactful communication strategies; and it can support smarter measurement, evaluation, and attribution, helping teams demonstrate the impact of their work.
AI will continue to change the mechanics of communications. The organisations that succeed will be those that marry new tools and approaches with the long-standing fundamentals of the profession: building and protecting trust by delivering relevant, authoritative content with a healthy dose of empathy and human judgement. Or, as Edelman’s latest Trust Barometer puts it, acting as ‘trust brokers to bridge divides.’