Gartner recently predicted that PR and earned media budgets could double over the next few years as AI tools increasingly replace traditional search. That headline is getting attention, but a lot of the discussion around it seems to be missing the point. Bigger budgets don’t signal comfort. They signal new demands and increased scrutiny. What’s changing isn’t just spend. It’s how influence actually works.

AI Is Reshaping How Information Is Found

More people are turning to tools like ChatGPT and Perplexity instead of typing queries into Google. Those systems behave differently than search engines. They don’t prioritize ads. They rarely cite press releases. They draw heavily from third-party coverage like news articles, research and institutional sources.

When someone asks about a company’s position on an issue, the answer is usually built from sources the company doesn’t control. That means external signals (media coverage, commentary, analysis, public records) shape the first layer of interpretation. That has real implications.

If AI systems become the default layer between audiences and information, earned credibility starts to function like infrastructure. It shapes how a company is interpreted before anyone visits its website.

That’s part of why PR budgets are rising. But this isn’t simply a call to “do more media relations.” It’s a shift in expectations.

The Scope of PR Is Expanding

The label may stay the same. The work behind it is widening. Influence now sits across multiple surfaces: traditional media, social commentary, expert networks, community discussions, long-form thought leadership, structured data sources.

The lines between PR, social, influencer, and search are thinner than they were even two years ago. That convergence changes how communications teams operate. It requires tighter coordination, clearer narrative strategy and a stronger understanding of how content travels across ecosystems both human and algorithmic.

Earned Media Carries More Weight But Comes With More Friction

There’s no evidence that coverage is becoming easier to secure. Newsrooms are smaller. Journalists are overloaded. Editorial filters are tighter. At the same time, earned authority is being amplified by AI systems that prioritize independent validation.

That tension matters.

Relationships need to be maintained between announcements, not just activated during them. When engagement only happens around a launch, it shows. Long-term familiarity still matters in a compressed media environment. Contributing to active conversations also requires more confidence. Waiting for perfect internal alignment often means arriving late. Adding something useful (a data point, a perspective, context) is more valuable than repeating polished positioning.

There’s also less room for trying to force a narrative onto the cycle. Attention already exists somewhere. The more practical approach is to understand where it is and participate constructively. Earned media is not softer or friendlier than it used to be, and its not going to be any time soon. It’s more selective.

Automation Is Changing Team Structure. Or At Least It Should Be

AI is absorbing a growing share of the base level, routine communications work - monitoring, transcription, translation, first-draft content, reporting. That doesn’t eliminate the need for communications professionals. But it does shift where value sits.

Work that is purely task-based will continue to compress. Strategic judgment, data fluency and the ability to connect narrative activity to business outcomes become more important. The middle layer of task-heavy communications roles will shrink. What remains are specialists who understand data and AI deeply, and leaders who know how to turn that insight into action. The expectations around performance will rise accordingly.

Measurement Can’t Be an Afterthought

Gartner’s projection that communications spending on data and analytics will double reflects something many executives already feel. Communications teams are still too often evaluated on outputs instead of outcomes. Advanced analytics won’t solve that automatically. But they do change what’s possible - real-time visibility into narrative shifts, stronger attribution modeling, tighter feedback loops.

Technology helps. Skill matters just as much. Teams need people who can interpret data and translate it into clear implications for leadership.

The pressure to demonstrate impact is unlikely to ease.

Where This Leaves Communications Leaders

Budget growth alone doesn’t define this moment. The deeper shift is about capability.

• Can your organization show up credibly across the surfaces AI systems rely on?
• Is narrative being managed consistently across media, social, and stakeholder communities?
• Are you measuring behaviour change, not just coverage volume?
• Is your team structured for more automation and more specialization?

Those are harder questions than budget allocation. They’re also the ones that will shape how the function evolves over the next few years.

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