Neumeier is CEO of the Atlanta-based Arketi Group, a marketing agency. He was the guest for the July 29 episode of Strategies & Tactics Live, PRSA’s monthly livestream on LinkedIn that delves deeper into the topics covered in its Strategies & Tactics publication.

When attempting to measure the impact of public relations campaigns, “For decades now, we’ve been talking about ad-equivalency being dead, and audience-reach being a red herring, and everyone knows [those things] won’t cut it,” Neumeier said.

Today, that shift “has not only earned PR folks a seat at the table, but made it an important seat.”

In May, the Arketi Group released its first  “CMO Signals & Shifts” report, based on a survey of marketing and public relations executives. The research found that although chief marketing officers have greater influence and stronger executive relationships than ever before, only 38% of CMOs surveyed say the role is positioned to succeed.

John Elsasser, editor-in-chief of Strategies & Tactics and host of S&T Live, asked Neumeier what accounts for the apparent contradiction.

“I think that number will increase over time,” Neumeier said. But for now, “The role has expanded faster than the resources, authority and organizational support behind it. That could have left many comms leaders feeling like they don’t yet have the ability to control the outcome, even though it’s not their own fault.”

As Elsasser pointed out, the report also calls alignment with the CEO the number-one driver of success for communications leaders. But what does alignment with the CEO look like in practice?

It used to be that a brand’s image could be tightly controlled with the marketing mix, Neumeier said. “Today, people don’t have to look very far to see if you treat your customers and employees in alignment with the brands you’re putting out in the marketplace,” he said. “It’s so transparent now, which is what I think has earned the chief communications officer and CMOs and the heads of PR a seat at the table, at the right hand of the CEO.”

In the past, the job descriptions companies used to recruit communications leaders often didn’t match what the CEO wanted, Neumeier said.

“The job description might have talked about brand awareness and perception, but when you dug into it, the CEO cared about lead generation. That means they hired the wrong person” for the top communications role.

In recent years, CEOs have become more sophisticated in understanding the types of communication professionals they need, Neumeier said. As a result, more companies are recruiting communications leaders who will enter their roles positioned for success, he said.

Communicators underestimating AI’s impact?

The Arketi Group report shows that public relations leaders have widely adopted artificial intelligence tools in their work. Elsasser asked if some communications leaders nonetheless still underestimate the impact of AI on their industry.

The rise of AI in communications and in the world at large “is moving at rocket speed,” Neumeier said. “Communicators may very well be underestimating how profoundly AI will change not just content creation, but how audiences discover information, how they evaluate criteria, and the opinions they form about your organization.”

Large-language models — artificial intelligence systems that can understand and communicate in human language — “are devouring our content and producing their own interpretations of that content,” Neumeier said. The AI’s interpretation “might not be the interpretation that you or your organization thinks or hopes it will be.”

In the age of AI, Neumeier said, communicators must figure out “how to put the right message out there that is being interpreted in the right way, to showcase what we think, feel and believe.”

Here, Neumeier takes part in the S&T Live Lightning Round…

The post As They Gain Respect, Comms Leaders’ Responsibilities Grow first appeared on PRsay.

Press releases measure the output of what you sent, not what landed. In a communications environment where audiences are spread across social media platforms, digital news outlets, podcasts, newsletters, and owned media, a single distribution report tells you almost nothing about whether your message actually moved the needle.

Having a story picked up by 50 media outlets means little if the tone is negative, the message is off, or the coverage doesn’t reach our stakeholders. Today’s communications landscape demands measurements that can turn fragmented data into clear, actionable intelligence. That’s where the reputation scorecard comes in.

Business leaders increasingly expect communications teams to demonstrate measurable outcomes, not just activity. That expectation is driving a real shift in how PR is practiced and evaluated.

A reputation scorecard is a structured, data-driven framework that aggregates key performance indicators across earned, owned and shared media into a single, decision-ready view. Unlike a traditional media-monitoring report, which typically catalogs coverage, a scorecard is built to drive action.

Think of it less like a report card and more like a live dashboard. Using AI and real-time analytics, it shows how your brand is being perceived, whether your messages are breaking through, and where you lead or lag against competitors. The reputation scorecard puts that intelligence directly into the hands of communicators and executives who need to make fast, informed choices.

Metrics that matter

Of course, not all metrics are created equal. A scorecard built on vanity metrics, raw impressions, total mentions, and raw clip counts will mislead more than guide. Meaningful reputation measurements focus on a different set of indicators.

Sentiment analysis tells you whether media coverage is working for you or against you. Message pull-through tracks whether your key narratives appear in media coverage or whether reporters frame the story differently. Share of voice measures your position relative to competitors, while narrative positioning reveals whether your brand is being associated with the themes and values that you want to own.

Qualitative insights matter as much as quantitative data. Who is saying what, in which outlets and to which audiences are factors that put numbers into context. The best scorecards tie these metrics directly to business and brand objectives, so every data point has a clear “so what” behind it.

AI is changing reputation management

Retrospective reporting has always been better than nothing. But in a news cycle measured in minutes, knowing what happened last week is often too late to matter.

Modern AI tools detect patterns in real time. They identify emerging narratives, flag potential reputational risks before they escalate, and reveal opportunities that manual review alone would almost certainly miss.

Predictive insights allow communications teams to get ahead of issues rather than simply react to them. Early warning systems built on AI reduce the blind spots that have historically made crisis management so reactive. The result is a communications function that is faster and more strategic, leaving PR pros far less likely to be caught off-guard.

A reputation scorecard earns its value by informing decisions, not by sitting in an inbox. In practice, scorecard insights help guide messaging strategy by revealing which narratives resonate and which ones fall flat. Such insights can optimize campaign planning in real time, enabling course corrections before significant budget is spent on a direction that the data no longer supports.

With reputation data, PR teams can prioritize media relationships and refine media pitches. Marketing teams can use it to sharpen positioning. Reputation data helps leadership teams assess brand health and benchmark progress against competitors.

Shifting from an output-focused PR practice to an insight-driven one doesn’t happen overnight, and it doesn’t mean abandoning what works. Press releases, media pitches, and traditional tactics remain valid, but they should be components of a larger measurement architecture, not the architecture itself.

The practical steps are straightforward: Align your communications metrics with specific business objectives; invest in tools that provide real-time, AI-assisted reputation analysis; and put insights in front of decision-makers at the right moments,

The harder work is cultural. Communications teams need to be comfortable saying “the data tells us to pivot.”

Organizations that make this shift position their communications function as a strategic asset rather than a support service. The reputation scorecard is the tool that makes that positioning credible and sustainable.

Ted Skinner is a marketing and PR strategist for Fullintel and one of the authors of the bestselling business book “Predictable Results: How Successful Companies Tackle Growth Challenges and Win.” Leveraging decades of experience, including an early role at eWatch, one of the first online media monitoring services, he integrates artificial intelligence and real-time analytics into data-driven communication campaigns.

Illustration: AYSIA

The post Beyond Press Releases: The Reputation Scorecard as a Strategic Communications Tool first appeared on PRsay.

More than five years after the coronavirus pandemic began, Americans remain anxious about a growing list of concerns, according to research from The Harris Poll and PRSA. Inflation, misinformation, political divisiveness, global instability, artificial intelligence and climate change continue to weigh on people’s minds.

In the last six months, “AI has overtaken climate change as a stressor in Americans’ day-to-day lives,” said Drew Higham, vice president of strategy for The Harris Poll.

“Americans are fixated on affordability,” he said during the July 27 livestream of Member Mondays, one of PRSA’s regular professional-development offerings. In the poll, respondents said groceries were harder to afford in 2025 than in 2024, while about half said tariffs had been bad for their finances.

The research also suggests that many Americans’ perceptions of the economy don’t always align with economic indicators. Some 57% of those polled said the U.S. economy is in a recession, “when we know it’s not,” Higham said. “They think unemployment and inflation are increasing, despite what the data may say.”

Urban and rural Americans hold starkly different views of the U.S. economy and how it’s affecting their personal fortunes, the research finds. But in America’s large cities, people also feel the strain of high prices, difficult job markets and uncertain futures.

Some 48% of urban Americans in the poll agreed that the economy in their community is strong, compared to 27% of rural respondents. Asked about the cost of living, 23% of urban Americans said it’s improving in their area, versus just 10% of rural Americans.

“There’s a growing divergence between how rural and urban Americans are feeling,” Higham told Heide Harrell, MA, APR, PRSA’s 2026 chair and host of Member Mondays.

‘Illusion of affluence’

Even for Americans who believe they’re doing well financially, their affluence might be an illusion, the research suggests. Among respondents whose households earn more than $200,000 a year, nearly half (46%) rely on credit cards to make ends meet. Of those, 80% use credit cards for purchases because they’ve run out of cash.

Among Americans who earn $200,000 or more, 48% feel they’re one unexpected bill away from financial chaos, the research finds.

“About half have to check their bank balance before buying groceries,” Higham said. “Americans are struggling to stay ahead.”

Gen Z and millennial men turn to alternative means to build wealth

With Bloomberg reporting that more than half of Americans (51%) say the economy isn’t working for them, 64% of Gen Z and millennial respondents to the Harris Poll agreed that the only realistic way to build wealth is through alternative methods such as cryptocurrencies, gambling, or trading stocks in personal accounts.

Among Gen Z and millennial men polled, 46% said the main reason they turned to legal sports gambling or prediction markets — which allow people to bet on the outcome of events — was to improve their finances.

“When people feel trapped economically, they’ll bet on anything to get ahead,” Higham said. “Young people are pessimistic about their futures, and they’re looking for financial alternatives.”

He showed a slide that read: “Teen Boys Are Losing Everything at Crypto Casinos.”

In the poll, 57% of respondents said they have friends who have become less social because of their gambling habits.

AI brings both obsolescence and hope

Many members of Gen Z, on track to be the most educated generation in American history, can’t find entry-level work. More than 4 million Gen Zers are unemployed, and some experts argue that certain degree programs don’t adequately prepare graduates for today’s job market.

Some 82% of Gen Z professionals already use AI at work, even as 65% fear the technology will render their skills obsolete. More than half of Gen Z workers polled (56%) fear they’re training their own AI replacements.

For their part, nearly all business leaders polled, 97%, said AI will benefit their companies and their own careers. Higham said the findings highlight a widening gap between how business leaders and younger workers view AI’s impact on the future of work.

“Companies are freezing a lot of the entry-level roles for new graduates,” Higham said. As a result, young Americans are feeling “pessimistic about their future and how they can get a head start in their career.”

Illustration credit: Olga Gorkun

The post Surveys Find Americans Worried About AI, Affordability and the Future first appeared on PRsay.

Founded in 2016 by Jesse and Emily Cole, the Savannah Bananas have transformed a fan-first version of baseball into one of the hottest tickets in sports. Known as Banana Ball, the game blends fast-paced action with showmanship, fan participation, and plenty of theatrics, from dancing players to bright yellow baseballs stitched with navy-blue laces.

Since becoming head coach in 2018, Tyler Gillum has helped fuel that rise.

“We’re living our dream, and trying to create the greatest show in sports,” he said.

This season, the Bananas and their sister teams are expected to entertain 3.4 million fans, with another 4.3 million people on the waiting list for tickets.

Ahead of his keynote at PRSA ICON 2026 on Oct. 18 in Orlando, Fla., Gillum spoke with PRsay about betting on yourself, building winning cultures, embracing the courage to be misunderstood and why success starts with putting people first. The interview was edited for length and clarity.

What first drew you to baseball, and when did you know you wanted to coach?

I’m a small-town country boy from Ada, Oklahoma. My dad was a bull rider. My mom was a cheerleader.

My journey is baseball. When I was 10 years old, we dogpiled for the first time. We won a championship. That feeling was unlike anything else. I’d been chasing that feeling ever since.

When I got to high school, I won four state championships and played for Eddie Collins, who became the winningest high school baseball coach in the country. He taught me more about life than baseball. I call him my hero.

My parents were loving and supportive, but they struggled with addiction. The baseball field became my getaway. It was my oxygen.

I’ve wanted to be a coach since I was 16 years old. I’ve never really thought about doing anything else.

Before joining the Bananas, you spent 13 years coaching college baseball, 11 of which were at South Mountain Community College in Phoenix. In a March Instagram post, you reflected on taking an unpaid, volunteer coaching position in Arizona because you believed it would offer you the best opportunity to learn and grow. What did that experience teach you about making career decisions?

I’ve never taken jobs based on money or benefits. I’ve always been chasing this coaching dream.

After earning my master’s degree, there wasn’t a full-time coaching position available. I believed Phoenix was the best place in the country to learn the game.

What philosophy has guided your career?

I’ve always followed a North Star of three things: learn, grow and network.

Every decision I’ve made comes back to asking: Can I learn? Can I grow? Can I build relationships with successful people?

That’s why I chose Phoenix. I cold-emailed every junior college coach in the area, drove 17 hours with almost no money, interviewed for two days, and stayed in a Denny’s parking lot to save money.

South Mountain offered me a volunteer job. I worked field maintenance from 4:30 a.m. until 1:30 p.m., coached from 2 until 6 every afternoon, and eventually started teaching classes after earning my master’s degree.

I wasn’t chasing a paycheck. I was chasing an opportunity.

“Bet on yourself” has become one of your signature messages. What does that phrase mean to you?

The first time I really bet on myself was when I went from high school to junior college. I had scholarship offers, but I wanted to attend Seminole State because it was where winners went.

My own high school coach actually advised against it.

I knew I probably wasn’t going to start. I knew I’d have to compete every single day. But I wanted to become the best version of myself.

You’ve also said leaders need “the courage to be misunderstood.” Can you explain that mindset and why you think it’s important?

We have a saying with the Bananas: You have to have the courage to be misunderstood.

When people have big dreams, even those closest to them often can’t see their vision. You have to trust yourself.

That decision to attend Seminole was probably my first real “bet on yourself” moment. In my first year, 42 players came out for baseball. Seventeen quit.

I’ve always believed life is a war of attrition. I’m not the smartest guy in the room. I’m just willing to stay in the arena longer than most people.

You’ll be speaking to many students and new professionals at PRSA ICON. What advice would you give someone just starting a career?

Find something you love enough to do even if you weren’t getting paid. People ask me all the time about all the travel. I love it. I’d do this for free. But not everyone finds that passion immediately. Try different jobs. Meet different people. Go to conferences.

Everything comes down to people. I recently saw a shirt that said: “Do hard things with good people.” That’s great advice.

Here, Gillum shares what he hopes ICON attendees will be inspired to do differently after hearing his keynote:

The post ICON 2026 Preview: Tyler Gillum Discusses the Importance of Betting on Yourself first appeared on PRsay.

As AI reshapes how organizations measure communications, Lazarova is helping lead the profession’s shift away from vanity metrics and toward proving real business impact. In this conversation with PRsay, she discusses the opportunities and risks AI presents, why communicators must connect their work to organizational outcomes, and what the future of measurement and evaluation looks like.

What is the biggest challenge facing communications measurement today?

Number one is the notion that AI can solve all problems. There’s an expectation that AI can provide cheap, even free, solutions to meaningful communications measurement. And the temptation to take those shortcuts is big. The truth is that there isn’t any universal technology that can answer an organization’s communications objectives.

The second risk I see is that, as a result of the proliferation of AI, there is a growing complexity in what communicators are dealing with. Making sense of what is important to the business is becoming increasingly complex. There’s more data than ever, not less. There’s more disinformation out there. Measuring business impact is getting harder.

The job of our profession is to provide clarity amid that complexity. Our job is to hold the line on high-quality, trusted data, credible methodologies, and ethical, honest accountability in communications.

You’ve spoken about the need to move beyond counting coverage and toward measuring business impact. Why is that shift still difficult for some organizations?

Counting coverage is easy. You can present it consistently, you can give it as a number, and everyone understands it.

The problem is that that number usually doesn’t tell you whether communication actually worked, if it delivered on the business objectives that it has been given by investors, senior leadership, et cetera.

From my perspective, demonstrating business impact requires three things to happen in parallel within an organization: Number one is that it requires data beyond just communications data, beyond what we see as outputs in the media.

It requires digital assets that reside within the organization, such as website traffic, sales, reputation tracking, customer behavior, and investor sentiment. Those areas are owned by other functions in the organization, which leads us to the second prerequisite: internal relationships.

The communications team needs strong internal relationships with the rest of the business to demonstrate the value of their work.

Number three is the need for patience and consistency when building measurements and frameworks. All three need to happen for us to demonstrate business results.

But a lot of times, you will see reluctance in terms of [a communications professional] raising a hand and saying, “I want to volunteer and start measuring what I do in this particular way.” Communicators are sometimes afraid even to start thinking about measuring business impact, because that makes them accountable for it. It requires a cultural shift.

Where do you think AI will create the greatest opportunities for communicators who are seeking deeper insights?

Before the advent of AI, insights were considered a luxury — something that only big organizations and communications teams with bigger budgets could afford. Now, AI gives more organizations access to deeper, more genuine insights.

AI gives us the opportunity to process large amounts of data at scale and relatively cheaply, providing the foundation on which we can then apply our consultancy minds and critical thinking, which is key for the profession in this day and age when AI is eroding the business of agencies and vendors alike. We can provide deeper insights and link communications activities with business outcomes.

Research shows consistently that earned media dominates AI responses. The core of our profession is to effect change and perception when it comes to reputation [through] earned media, owned media, et cetera — and then to connect that with what you see downstream in terms of AI citations.

What measurement trends do you think will have the greatest impact on the profession over the next three to five years?

The need to mature our thinking about measuring AI visibility across different large language models, sometimes referred to as Generative Engine Optimization, as part of bigger communications-measurement frameworks.

The trend will be for more transparency. There will be more pressure on businesses that deliver those insights to publish their methodologies and apply high standards for quality and the ethical use of data.

I would be remiss if I didn’t mention the trend for deeper integration of commerce measurement with business performance and business impact. Although it’s a slow process, more organizations will have access to measurement and insights into their PR activities.

We need to be able to connect share-of-voice metrics, narrative, AI visibility, to brand health, to business performance, to whatever the business objective is.

This isn’t something that applies only to for-profit organizations. In fact, we have seen an increasing number of not-for-profits and other organizations becoming AMEC members and applying the integrated evaluation framework, one of AMEC’s best-practice assets. Objectives can be defined by the goals you have for influencing different stakeholder groups.

When you look ahead to the end of your second term as AMEC chair in 2028, what do you think success will look like for AMEC and the communications-measurement profession?

I would like to see communications treated as a strategic function. That has definitely improved over the last few years, but there’s still a long way to go.

Measurement and evaluation are the tools communicators need to demonstrate business impact and outcomes, positioning them as a strategic function. We see ourselves as the prime tool for communicators to achieve that desired strategic position.

Looking forward, again, although we launched the GEO-measurement principles a couple of weeks ago at our annual summit in Dublin, I want to see those principles embedded in practice, not just on paper or on our website.

I want to see more PR awards around the world applying and referencing the GEO-measurement principles, [with] more ethical, grounded-in-quality data and consistent application of those GEO principles.

Personally, I want to make sure we remain relevant and continue to help the profession. I want the community to feel better equipped and more confident to thrive, not only survive, for whatever comes next.

Clearly, we are going through a disruption at the moment. It’s not something anyone, or many people, in our profession foresaw two years ago. But it’s happening. It’s a bit like COVID: Going through that crisis helped us all to be better equipped and prepared for what’s to come next.

And personally, I want to see the global community of measurement professionals better prepared for the future. The way I see my job as chair is to give the profession better frameworks, principles and standards, and a shared language they can use when dealing with those challenges.

We are here to create principles and standards and to uphold the highest standards. We have our annual AMEC awards that recognize best practices in communications measurement, and we will continue doing that work with passion. I want to make sure that we continue to be relevant and to help the profession.

Here, Lazarova discusses the momentum she feels emerging from the recent 2026 AMEC Global Summit.

The post Measuring What Matters: Q&A With AMEC Chair Raina Lazarova first appeared on PRsay.

Nearly three-quarters (73%) of PR professionals say generative-engine optimization (GEO) is at least somewhat important to their communications strategy, even as 29% say no one at their organization is responsible for it.

Generative-engine optimization is the practice of making content easier for artificial intelligence systems to find, understand and reference in their responses. Large-language models such as ChatGPT, Claude, and Gemini rely on context, authority, recentness, and factual accuracy when deciding what information to cite.

Among PR professionals surveyed by Muck Rack, 39% say they are not measuring GEO at all, even though 45% cite media measurement and reporting as a major part of their work.

Among those tracking generative-engine optimization, 25% monitor brand mentions in AI-generated responses. Some 17% monitor referral traffic from AI tools, while another 17% track earned-media placements tied to AI visibility.

“Most PR professionals recognize that AI visibility matters, but many companies still haven’t decided who owns it or how to measure it,” Greg Galant, cofounder and CEO of Muck Rack, said in a statement. “This is a critical moment where better data and better tools can make all the difference in how we approach this shift in the PR workflow.”

AI is reshaping communications strategy.

As organizations adapt to AI search, communicators are also adjusting their media strategies.

Some 55% of PR professionals say they are securing coverage in high-authority publications to improve visibility in AI-generated responses. Half say they are creating more authoritative, data-driven content and optimizing it for search.

The report also found that 80% of PR pros already use generative AI in their workflow, while 61% expect AI and automation to grow in importance over the next five years.

LinkedIn remains the dominant social platform for communicators. It is included in 87% of communications strategies, followed by Instagram at 72%. Additionally, 60% of respondents identified LinkedIn as the most valuable social platform for their work.

More than half (51%) of respondents say that creating thought-leadership content now accounts for at least one-quarter of their work, a 6-point increase from last year.

Media relations remains challenging.

Even as AI changes communications strategies, traditional media relations remain at the center of the profession.

Some 55% of PR professionals say securing coverage in high-authority publications is their most common tactic for improving AI visibility. Yet arranging earned media has become increasingly difficult. Nearly half (49%) of PR pros say they pitch more than 20 journalists per campaign, while 71% report low response rates from journalists and 61% cite shrinking media lists in relevant beats.

Online and digital outlets remain the most commonly pitched media type, selected by 91% of respondents. Traditional media continue to receive significant outreach as well, with newspapers (69%), magazines (64%), television (60%) and podcasts (57%) all remaining common targets.

Long hours continue to define PR work.

The demands of the profession continue to extend beyond the traditional workday.

More than half (55%) of respondents reported working more than 40 hours in the previous week. After-hours work remains commonplace, with 77% reporting working outside regular business hours at least once that week. Nearly half (47%) did so one or two days, while 30% worked late nights, early mornings or weekends at least three days.

The workload appears to be taking a toll. Two-thirds (66%) of respondents rated their work stress as high.

The report suggests that while AI is becoming a standard part of communications practice, the fundamentals of public relations remain the same. Building relationships with journalists, producing authoritative content and demonstrating measurable results continue to be the foundation of successful PR — even as AI increasingly influences how audiences discover information.

Illustration credit: Yuliia

The post Long Hours, Fewer Reporter Responses, AI Optimization: 2026 ‘State of PR’ first appeared on PRsay.

Artificial intelligence “is changing how we create content,” Angela Dwyer, APR, said. “AI search is a huge channel, in terms of influence.”

For PR pros, getting clients mentioned in the news media is no longer the end goal. Today’s PR professionals must craft messages that will also be cited by the AI models many consumers increasingly rely on to answer their questions.

Earned media still matters

According to Muck Rack’s research, AI models tend to favor credible journalism as sources. Some 94% of the sources AI models cite are non-paid content, 84% of which is earned media mentions that PR pros have worked to arrange.

Artificial intelligence favoring earned media is “super exciting for comms professionals today,” said Martin, a longtime PR and media relations pro who serves as managing director of media and influence for Allison Worldwide in New York.

The research findings “validate our business” and create a mandate “to look at how AI is impacted by the work that we do,” he said. AI answer engines often rely on unpaid content as one signal of authority when evaluating the information they serve to users, he said.

Content from YouTube and LinkedIn is also being cited more often by AI models, Martin told Dawn Robintette, APR, Fellow PRSA. Robintette, owner of Tale to Tell Communications in San Antonio, moderated “AI Pulse” for regular host and immediate PRSA past chair Ray Day, who was on vacation.

Executive thought leadership on LinkedIn, as well as content from influencers on LinkedIn and YouTube, can also increase visibility in AI-generated responses, Martin said.

“These are areas that we as comms professionals need to think about when applying strategy,” he said. “Discovery-based communities like Reddit and Quora are becoming another important source of earned visibility.”

Creating content AI will cite

Different AI models rely on different types of sources, the research found. While earned media is the top source for ChatGPT answers (at 35%), it falls to third place on the more scholarly Claude AI, which prefers research papers and government sources.

Earned media also drops to third place for Google’s Gemini AI, which favors content from its own YouTube platform and wider Google ecosystem. Similarly, Microsoft’s Copilot favors the company’s LinkedIn platform and the index of its Bing search engine, pushing earned media to third place.

“Things are changing in the world of earned media,” said Dwyer, vice president of Insights at Fullintel, a media-monitoring and measurement company.

From clicks to citations

Website clicks might be down, “but people are still being influenced by the content,” she said. “They’re just getting it from a different source. They’re going to AI search, or, more old-fashioned, they’re still going to Google, where they type in their search and get an AI overview. You want to be one of the links cited.”

In some industries, for example, health care, owned content such as websites is seen as credible by AI models, she said.

Along with authority and trust, other content characteristics influence what AI will cite, Dwyer said, drawing on her own research.

“The number-one thing is educational content, which goes hand-in-hand with the second one, which is answer articles. Across the board, educational content is getting cited more.”

People don’t like promotional content, she said. “But we do like our questions to get answered.”

The discussion underscored how media relations, thought leadership and educational content remain central to PR strategy — not only for reaching journalists and audiences, but increasingly for influencing the AI systems people use to find information.

Illustration: Blankstock

The post Why Earned Media Matters More in the Age of AI first appeared on PRsay.

An increasing number of people are no longer using traditional search engines to find information, but are relying on the answers provided by AI language models (LLMs). However, LLMs work fundamentally differently from Google & Co.: rather than linking to individual websites, they summarise information from numerous sources and provide an interpreted answer. As a result, an AI response is always an interpretation of information, and it is precisely this interpretation that is increasingly shaping the perception of companies, brands, and topics.

Communications managers are therefore faced with two challenges. First, they must determine whether their company is included in AI models at all. Second, they must examine how their company is portrayed in AI responses, in terms of both tone and associations.

AI as both a reputation actor and an analysis tool

Language models play a dual role: they are both the subject of investigation and the analytical tool.

On the one hand, the focus is on monitoring AI-generated statements about companies that affect their reputation. The central question here is: What do AI systems say about a company? This involves systematically collecting, analyzing, and evaluating the responses that language models provide to typical user questions, such as those about quality, trustworthiness, scandals, sustainability, or employer attractiveness. This form of monitoring is comparable to classic media or social media monitoring, but it refers to a new actor: AI itself as a “communicator”.

On the other hand, AI is used to observe and measure reputation, i.e., AI-supported reputation monitoring. In this case, AI is not the object of observation, but the tool. Language models evaluate large volumes of text to derive reputation indicators such as tonality, topics, trust, risk factors, and narratives.

These two levels are closely intertwined. This is because the training data and response patterns of language models are derived from the very public discourse that AI analyses. Consequently, reputation is increasingly emerging within a cycle of public communication, AI-supported evaluation, and AI-based reproduction – marking a fundamental change that is redefining strategic reputation management.

From an experienced to a discursive reputation

Against this backdrop, LLMs are not instruments for measuring experienced reputation, but for analyzing discursive reputation. The focus is not on what real customers think after specific interactions, but on the image that has become established in public discourse.

This is where language models’ particular strength lies. Trained on vast amounts of text, they excel at recognizing and summarising dominant narratives. They process opinions expressed in the media, on social networks, in forums, and on review platforms, thereby condensing public discourse. In other words, while language models do not have direct access to reality, they do have a highly developed model of how people talk and think about the world — or, in this case, about a company or brand.

If reputation is understood as the result of discursive condensation, it can be heuristically structured along three central dimensions: awareness, attitude, and attribution. All three dimensions can be systematically observed and evaluated using language models, albeit in different ways.

Awareness: Is the company even considered?

Awareness describes whether and to what extent a company occupies the market’s cognitive space. In an AI-mediated information environment, this means one thing above all: does the company appear in language models’ responses when real decision-making and orientation questions are asked?

In practice, I use two approaches to answer this question. First, I rely on specialized tools that systematically record companies’ visibility in various language models. Second, I work with standardized prompts that reflect typical user questions, such as “Which providers are leaders in the field of…?” or “Which companies are considered trustworthy when it comes to…?” These prompts are deliberately formulated neutrally and used identically across multiple models.

What matters is not the individual mention, but the aggregated pattern. The responses provide an overview of market visibility: how often a company is mentioned, in which contexts it appears, and what position it occupies relative to competitors. This reveals whether a brand is on the shortlist or plays a little role in decision-making processes. Here, awareness is reflected not in reach metrics, but in discursive presence in relevant decision-making situations.

Attitude: How is the company evaluated emotionally?

The second dimension concerns the emotional and evaluative coloring of this presence. The question is whether the perception of a company is predominantly positive, negative, or ambivalent. This dimension cannot be derived directly from language model responses, as LLMs do not make independent evaluations, but rather condense existing discourses.

An intermediate step is therefore required to combine the aggregated market voice reflected in language models with real user experiences. In practice, communications managers must systematically process current customer reviews and use them as the basis for analysis.

To do this, reviews from relevant sources — such as Trustpilot, app stores, or industry-specific platforms — are exported for a clearly defined period, for example, the last two to three months. The data is then consolidated, cleaned, and structured so that all analyzed companies can be compared on the same basis.

Next, several language models analyze the same review dataset. It is crucial that the models work exclusively with the available comments and do not incorporate any external knowledge. Based on this material, they identify overall sentiment, recurring positive and negative themes, and changes over time.

Finally, the results are synthesized. The models summarise the prevailing mood, extract typical patterns of experience, and highlight areas of high satisfaction, frustration, or structural problems. Because all providers are evaluated using identical data and analysis prompts, this approach produces an up-to-date and consistent comparison of emotional evaluation across the market.

Attributions and associations: What does the company stand for?

The third dimension concerns the substantive meaning of a brand. This is not about sentiment, but about the characteristics, themes, and associations attributed to a company in the market. This dimension can be captured by using language models to systematically identify, cluster, and consolidate recurring terms, attributes, and associations.

To do this, communications managers define uniform prompts that explicitly address key reputation issues. Examples include: “Is the company considered reputable?” “What topics is it most often associated with?”, or “Is its positioning clear, contradictory, or difficult to grasp?” Multiple language models systematically answer these prompts.

The responses are then compared. If the models provide consistent descriptions, this indicates a coherent reputation. If the assessments diverge significantly or contradict one another, this points to a fragmented market identity. At the same time, the topics and attributes mentioned are collected, structured, and classified as positive, negative, or ambivalent.

The result is a set of dominant reputation clusters that reveal whether a brand is primarily associated with trust, innovation, regulation, risk, or controversy. Finally, the clarity of positioning is assessed: if the models’ descriptions largely converge, the profile is considered stable. If they diverge, the result is a blurred or contradictory image that requires targeted communication efforts.

Dr. Lydia Prexl is a communications strategist. Since 2021, she has been responsible for internal and external communications at the European payment service provider Unzer. Before that, she established the communications function at the fintech insurer Getsafe.

Illustration: Kiattisak

The post How to Set Up Reputation Monitoring in Language Models first appeared on PRsay.

AI tools don’t read your content the way humans do — they extract it. If your content makes extraction seamless, AI cites you. If it doesn’t, AI cites your competitors.

When you trap your ideas inside dense paragraphs, AI engines can’t map their way through them. But when you switch to a highly scannable layout, you’ll get more AI citations. (More good news: Scannable content works better for readers, too.)

Here are two ways to format content that AI will extract — and that readers will skim, scan and read:

1. Use tables to compare and contrast.

Any time you need to compare multiple items against a single set of criteria — before vs. after, old vs. new, here vs. there, this vs. that — put it in a table.

Content with tables gets cited 2.5 times more often than content without, according to Discovered Labs’ analysis of GEO content strategy and AI citation patterns.

That’s because tables give AI structured, pre-organized information chunks it can lift directly. (More good news: Tables also make it easier for readers to compare and contrast.)

One caveat: Tables are hard to read on mobile. Limit yours to two columns. More than two, and your readers will be pinching and scrolling instead of scanning.

2. List lists.

Any time you have a series of three or more items, put it in a list. And make those lists substantial — not labels.

Lists are among the most-cited formats in AI search. Nearly four out of five URLs cited in ChatGPT include at least one list, according to an AirOps’ analysis.

AI doesn’t read content — it pulls passages. Lists give AI pre-packaged, discrete units of thought that it can lift directly.

A paragraph buries the answer. A list serves it up. (More good news: Lists also make it easier for readers to follow your ideas.)

And make sure to write lists that are substantial and self-contained.

Your ideas deserve to be found.

AI won’t hunt for your ideas. It won’t dig through dense paragraphs. It will move on.

Format your content so AI doesn’t have to work for it. Then watch AI do the work for you.

Ann Wylie (WylieComm.com) helps PR professionals Catch Your Readers through writing training. Her workshops take her from Hollywood to Helsinki, helping communicators in organizations like Coca-Cola, Toyota, Eli Lilly and Salesforce draw readers in and move them to act. Never miss a tip: FreeWritingTips.wyliecomm.com.

Copyright © 2026 Ann Wylie. All rights reserved.

The post Format Your Way to AI Citations first appeared on PRsay.

A journalist, entrepreneur, best-selling author, and breast cancer survivor, Natale made history in 2017 as the first Latina to win three Daytime Emmy Awards. The awards honored her talk show “SuperLatina,” which she launched in 2007 in a studio she and her husband, Andy, built in a former carpet warehouse in Texas. “SuperLatina” was later picked up by the Spanish-language network V-me TV.

Through her work as a storyteller, speaker and advocate, she has inspired audiences around the world with messages of resilience, reinvention and overcoming barriers.

On Tuesday, Oct. 20, Natale will take the stage at PRSA ICON 2026 in Orlando to deliver her keynote presentation, “PIONEER: Embrace Your Uniqueness, Break Barriers and Redefine What Is Possible.”

Ahead of her appearance, Natale shared her insights with PRsay on cultivating a “pioneer mindset,” building a memorable personal brand and embracing the qualities that set communicators apart.

You’ve built a career at the intersection of storytelling, media and leadership. What sparked your interest in the power of communication?

I come from a family of lawyers, and when I was growing up, there was a fairly conservative view of career choices. Journalism, television and being on stage were not considered priorities.

Because I wanted to see the world and spoke multiple languages, I chose international relations. But during a semester abroad at the University of Westminster in London, I realized I was spending every disposable pound I had at the London Film Festival.

I returned to Argentina, graduated with a degree in international relations, then studied television production and earned a master’s degree in journalism.

What skills matter most for communicators right now?

The pace of innovation makes continuous learning essential. There are many things today that can be automated and scaled with AI. But there are also things that cannot be replicated, and that’s where our attention should go.

AI models are good at identifying patterns based on what has already been said, what has already happened and what ideas have already been shared. If all we’re seeing is the dominant pattern, how are we going to create something new? It means paying special attention to our taste, our point of view and our discernment.

In an era when we’re constantly validated by likes and engagement, the ability to be temporarily disliked is becoming an important skill. Sometimes having a point of view means expressing an opinion that may not be immediately popular. If we’re fulfilling our responsibility as communicators with an open heart, we need to cultivate the ability to withstand that discomfort.

Your work helps people and organizations stand out in crowded environments. What mistakes do communicators make when trying to differentiate themselves?

Even when communicators are trying to differentiate themselves, they’re often playing it safe. They’re pursuing the same opportunities, targeting the same audiences, chasing the same messages or adopting similar styles of delivery.

That’s what I call the “emulator mindset” — when we look around, see what everyone else is doing, and then set our future goals based on someone else’s past results. Emulators don’t move the world forward. They perpetuate the status quo.

What we’ll talk about in Orlando is the opposite approach, what I call the “pioneer spirit” — the idea that we must believe in our vision before we have results to validate it.

What’s your advice for communicators who want to strengthen their own personal brands and build their professional visibility?

Make full use of all the tools available to us today. When I graduated in 1995, everything depended on gatekeepers. That’s no longer the case. Not all of us had these opportunities when we started our careers, and even today many people aren’t taking full advantage of the opportunities available to them.

Technology now allows our voices, ideas and messages to travel farther than we can imagine. That’s something I emphasize when I train professionals at Fortune 500 companies and organizations around the world.

Don’t underestimate the power of your voice. Don’t underestimate the power of your story. You can create an impact that you can’t even imagine today.

No matter where you work, chances are, you’re operating in a crowded environment. There are many talented people competing for limited opportunities. So how do you stand out? Part of it is doing great work and striving for excellence. But another part is developing a style of your own. And how do you develop your own style if you’re never willing to take risks?

If you visit the Pablo Picasso Museum in Barcelona, you can see his entire artistic journey. His earliest paintings reflect what I would call an emulator mindset. They resemble the work of many other artists of the era — similar subjects, similar techniques and similar approaches.

But over time, you can see a deliberate decision to view himself and the world differently. That’s when the first hints of Cubism begin to appear. By the end of the museum, it’s clear that Picasso created an entirely unique style. But that only happened because he gave himself permission to take risks and express himself fully.

What a loss it would have been if he hadn’t allowed himself to explore his full potential and creativity. That’s the message for all of us. We need to give ourselves permission to express our own potential and greatness.

There may be an equivalent of Cubism in your profession, your craft or your delivery. There may be a spark that only you possess. If you’re simply imitating what everyone else is doing, you’ll never discover it.

Here, Natale shares one idea that she hope PRSA ICON attendees will take away from her keynote:

The post ICON 2026 Preview: Gaby Natale on Finding Your Pioneer Spirit first appeared on PRsay.