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What Makes Someone an Expert?

A practical guide to identifying expertise across your organization and putting it to work

Co-Founder & CEO

Co-Founder & VP Product

 When you are first introduced to expertise marketing it can be hard to imagine that there are experts hiding within your organization. We tend to think of experts as a small group at the top but in reality that is just the tip of the iceberg. Across teams and departments there are people with the knowledge, skills and experience to contribute to meaningful conversations with your audiences.

These individuals may not always carry the title of expert but their perspectives can help explain complex issues, contribute to research and shape the content your organization produces. When their expertise is recognized and supported it can help build trust with key audiences including media, industry partners and prospective clients.

The challenge many organizations face is knowing how to assess expertise in the first place. To identify these hidden experts and understand the role they can play in an expertise marketing program it helps to start with a simple question.

What actually makes someone an expert?  The 7 Attributes of Expertise  By definition an expert is someone with comprehensive or authoritative knowledge in a particular area of study. While formal education and certifications can be important starting points many fields do not have a clear set of criteria that determines expertise.

In practice expertise develops through a combination of training, research, professional experience and real-world application. It is also shaped by the level of trust and recognition someone has earned within their profession or community.

When evaluating expertise across your organization it is important to consider the different roles people can play. Many individuals have invested years developing deep knowledge in their fields but not everyone is interested in speaking at conferences or appearing in the media. That does not reduce the value of their expertise. Many contribute through research, insights and content development that support broader visibility for the organization.

Here are several attributes that help define expertise and the roles people can play within an expertise marketing strategy.

Authority: Has a reputation with an audience as a trusted source of insight and perspective. Advocate: Demonstrates a commitment to advancing a professional community or area of practice. Educator: Teaches and inspires others through lectures, presentations or classroom instruction. Author: Develops articles, commentary or thought leadership that expands their reach and influence. Researcher: Generates new insights through research, analysis or field work. Practitioner: Applies specialized knowledge in a professional setting by delivering services or solutions. Graduate: Has formal education or professional training that demonstrates proficiency in a subject area.  Understanding these attributes helps organizations see that expertise exists across many roles. Once those individuals are identified the next step is determining how their expertise can contribute to broader visibility and engagement.
 
The 4 Levels of Expertise  Understanding how to promote expertise is an emerging discipline for many organizations. Unlike traditional career paths expertise does not always follow a predictable hierarchy.

When we consider which experts are most visible to audiences it becomes clear that visibility is not always tied to seniority or authority within an organization. Professionals at many stages of their careers are now sharing insights through social networks, industry publications and personal platforms.

This means that a senior researcher with decades of experience and a younger professional actively sharing insights online could have a similar level of visibility.

Because visibility is influenced by personal motivation and interest in public engagement many organizations recognize the need to better identify and support experts across their teams. Doing so helps ensure that valuable knowledge is not overlooked and that more voices can contribute to meaningful conversations.

The framework below can help organizations take inventory of their expertise and develop a path for individuals who are interested in contributing content and building visibility with key audiences.

 Now that we’ve provided a broader picture of what expertise looks like, it’s time for you to ask, “How does my organization stack up?”
 
Bench Strength: Taking Stock of Expertise Across Your Organization  Expertise is in high demand. Audiences are looking for credible voices who can provide context and insight on complex issues.

For organizations, this means it is critical to understand how their collective expertise can be channeled into meaningful conversations with their audiences.

As you review the attributes and levels of expertise outlined above you may begin to recognize individuals within your organization who have valuable knowledge but may not have been considered visible experts before. Identifying these individuals is an important first step but recognition alone is not enough.

Mobilizing expertise marketing requires support and investment from leadership across the organization. Senior leaders will want to understand the value of elevating internal expertise and how it contributes to reputation, visibility and opportunity.

The organizations that succeed are those that recognize expertise as a strategic asset and take deliberate steps to surface it, support it and share it with the audiences who are actively searching for it.
The Complete Guide to Expertise Marketing For a comprehensive look at how expertise marketing benefits the entire organization and drives measurable return on investment, follow the link below to download an industry-focussed copy of ExpertFile’s Complete Guide to Expertise Marketing: The Next Wave in Digital Strategy 

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How to Make Your Experts “AI-Ready"

Why you need an LLMs.txt file to go with your SEO Meta & Schema Data

 AI is changing how people discover expertise. 

Today, journalists, event organizers, researchers, and the public increasingly turn to tools like ChatGPT, Claude, Perplexity, and Google Search’s AI summaries powered by Gemini. Instead of clicking through pages of links, they expect clear, credible answers—often delivered instantly, with citations.

That shift has major implications for organizations.

It’s no longer enough for your experts to “rank well.”
They need to be understood, trusted, and accurately represented by AI systems. So the real question becomes:

When AI talks about your experts, does it get it right? This is where LLMs.txt plays an important role—especially when paired with an ExpertFile-powered Expert Center.

 What is LLMs.txt (In Plain English)? ...and why is it essential for expert content LLMs.txt is a small, machine-readable file placed on your organization’s website—in the case of your expert content alongside your main Expert Center. Its purpose is simple:
to explain your expertise to AI systems clearly and unambiguously. “AI systems don’t just scan for keywords; they look for clear meaning, consistent context, and clean formatting — precise, structured language makes it easier for AI to classify your content as relevant.”  Microsoft: Optimizing Your Content for Inclusion in AI Search Answers  Rather than forcing AI to infer meaning from scattered pages, LLMs.txt explicitly tells systems:

Who your experts are Which pages represent official, curated content How expert profiles differ from articles, Q&A, or research content How your organization’s expertise should be interpreted as a whole  Think of it as a table of contents and usage guide for AI —helping large language models understand your site the way a communications professional would.

 Why This Matters for Visibility and Trust It Establishes Your Organization as the Source of Truth AI systems routinely synthesize information from multiple places. Without guidance, they may rely on outdated bios, scraped content, or secondary references.

LLMs.txt provides a clear signal:

This is our official expert content. This is what represents us. For ExpertFile clients, this matters because the platform already centralizes and curates expert content—from profiles and directories to Spotlights and Expert Q&A—ensuring that what AI sees is current, governed, and institutionally endorsed.

The result: Greater accuracy, stronger attribution, and reduced risk of misrepresentation when your experts appear in the ever growing AI-generated overviews and answer.

 ahrefs: AI Overviews Have Doubled  How It Improves Discovery Across AI Platforms It Makes Structured Expertise Easier for AI to Use ExpertFile is purpose-built to publish structured expert content at scale—content that goes well beyond static bios. LLMs.txt simply helps AI recognize and use that structure correctly.

It clarifies the role of key ExpertFile content types, including:

Expert Profiles → Canonical identity, credentials, and areas of expertise Spotlight Posts → Timely commentary, thought leadership, and research insights Expert Q&A → Authoritative answers to real-world questions Directories, Research Bureaus, and Speakers Bureaus → Curated collections of expertise by topic or audience  This makes it easier for AI systems to:

Match your experts to breaking news and trending topics Pull accurate summaries for AI-generated responses Identify the right expert for journalists, event organizers, and researchers  Combined with ExpertFile’s extended distribution through expertfile.com and the ExpertFile Mobile App, your expertise is not only published—but actively discoverable across channels used by key audiences .

 How It Builds Organizational Authority It Connects Individual Experts to Institutional Credibility Without context, AI may treat expert pages as isolated profiles. LLMs.txt helps connect the dots.

It tells AI that:

Your experts are curated and endorsed by the organization Their insights are part of a broader expertise ecosystem Your institution has depth across priority subject areas  This aligns closely with how ExpertFile structures content to support E-E-A-T (Experience, Expertise, Authority, Trust)—not just at the individual level, but across the organization .

The outcome: Your organization is recognized not just as a collection of experts, but as an authoritative source of knowledge.

How It Works with Google, Gemini, and AI Search Supports AI Summaries, Citations, and Knowledge Panels  LLMs.txt helps ensure that when Google’s AI:

Summarizes your organization Cites expert commentary Builds “about this topic” panels  …it draws from your official, structured ExpertFile content, rather than fragmented third-party sources.

This complements ExpertFile’s existing SEO and AI-discoverability foundation, which includes clean code, proper meta data, schema markup, and frequent crawling by both search engines and AI bots.

 How LLMS.txt Fits with SEO, Meta Tags, and Schema  LLMS.txt doesn’t replace SEO—it builds on it. Traditional SEO elements such as page titles, meta descriptions, schema.org markup, and internal linking remain essential for helping search engines index and rank your content.

ExpertFile already delivers these fundamentals out of the box, continually testing and evolving SEO and GEO (Generative Engine Optimization) standards as search changes .

“Semantic SEO helps search engines understand context... it now helps bridge a critical gap between traditional SEO and newer generative engine optimization (GEO) and AI optimization (AIO) efforts.”  Search Engine Land: Semantic SEO: How to optimize for meaning over keywords  LLMS.txt adds a layer designed specifically for AI systems: Schema explains individual pages LLMs.txt explains your entire expertise ecosystem  In simple terms: SEO helps your content get found LLMs.txt helps AI understand, summarize, and cite it correctly  Together, they ensure your experts are not only visible—but accurately represented wherever AI is shaping discovery.

 Why This Is Especially Powerful on ExpertFile  ExpertFile was designed to future-proof expert visibility—offering structured publishing, governance, distribution, inquiry management, analytics, and professional services as part of a continuously evolving SaaS platform .

LLMS.txt acts as a multiplier on that foundation:

Turning your Expert Center into a machine-readable expertise hub Strengthening AI discovery without adding operational burden Supporting emerging use cases like automated expert matching and AI-assisted research  It’s not about chasing new technology.

It’s about ensuring your expertise is clearly defined, properly attributed, and trusted—now and in the future.

 The Takeaway  An LLMs.txt file on your ExpertFile organization page helps ensure that:

Your experts are found by AI tools, not overlooked Your content is interpreted correctly, not flattened or misrepresented Your organization earns authority and trust in AI summaries, citations, and search results  “AI search isn’t eliminating organic traffic. But it is reducing visits to source websites… Measure presence (citations, mentions) alongside traffic to see real impact.” Semrush: AI Search Trends for 2026 & How You Can Adapt  As AI becomes the front door to information, LLMs.txt helps make sure that when people ask for expertise, your organization is the answer they get. 

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ChatGPT-5.2 Now Achieves “Expert-Level” Performance — Is this the Holiday Gift Research Communications Professionals Needed?

With OpenAI’s latest release, GPT-5.2, AI has crossed an important threshold in performance on professional knowledge-work benchmarks. Peter Evans, Co-Founder & CEO of ExpertFile, outlines how these technologies will fundamentally improve research communications and shares tips and prompts for PR pros.  OpenAI has just launched GPT-5.2, describing it as its most capable AI model  yet for professional knowledge work — with significantly improved accuracy on tasks like creating spreadsheets, building presentations, interpreting images, and handling complex multistep workflows. And based on our internal testing, we're really impressed.

 For communications professionals in higher education, non-profits, and R&D-focused industries, this isn’t just another tech upgrade — it’s a meaningful step forward in addressing the “research translation gap” that can slow storytelling and media outreach.

According to OpenAI, GPT-5.2﻿ represents measurable gains on benchmarks designed to mirror real work tasks.  In many evaluations, it matches or exceeds the performance of human professionals.

Also, before you hit reply with “Actually, the best model is…” — yes, we know. ChatGPT-5.2 isn’t the only game in town, and it’s definitely not the only tool we use. Our ExpertFile platform uses AI throughout, and I personally bounce between Claude 4.5, Gemini, Perplexity, NotebookLM, and more specialized models depending on the job to be done. LLM performance right now is a full-contact horserace — today’s winner can be tomorrow’s “remember when,” so we’re not trying to boil the ocean with endless comparisons. We’re spotlighting GPT-5.2 because it marks a meaningful step forward in the exact areas research comms teams care about: reliability, long-document work, multi-step tasks, and interpreting visuals and data. 

Most importantly, we want this info in your hands because a surprising number of comms pros we meet still carry real fear about AI — and long term, that’s not a good thing. Used responsibly, these tools can help you translate research faster, find stronger story angles, and ship more high-quality work without burning out.

When "Too Much" AI Power Might Be Exactly What You Need  AI expert Allie K. Miller's candid but positive review of an early testing version of ChatGPT 5.2 highlights what she sees as drawbacks for casual users: "outputs that are too long, too structured, and too exhaustive."  She goes on to say that in her tests, she observed that ChatGPT-5,2 "stays with a line of thought longer and pushes into edge cases instead of skating on the surface."

 

 Fair enough.

All good points that Allie Miller makes (see above).  However, for communications professionals, these so-called "downsides" for casual users are precisely the capabilities we need. When you're assessing complex research and developing strategic messaging for a variety of important audiences, you want an AI that fits Miller's observation that GPT-5.2 feels like "AI as a serious analyst" rather than "a friendly companion." 

That's not a critique of our world—it's a job description for comms pros working in sectors like higher education and healthcare. Deep research tools that refuse to take shortcuts are exactly what research communicators need.    So let's talk more specifically about how comms pros can think about these new capabilities:

1. AI is Your New Speed-Reading Superpower for Research That means you can upload an entire NIH grant, a full clinical trial protocol, or a complex environmental impact study and ask the model to highlight where key insights — like an unexpected finding — are discussed. It can do this in a fraction of the time it would take a human reader.

This isn’t about being lazy. It’s about using AI to assemble a lot of tedious  information you need to craft compelling stories while teams still parse dense text manually.  2. The Chart Whisperer You’ve Been Waiting For We’ve all been there — squinting at a graph of scientific data that looks like abstract art, waiting for the lead researcher to clarify what those error bars actually mean.

Recent improvements in how GPT-5.2 handles scientific figures and charts show stronger performance on multimodal reasoning tasks, indicating better ability to interpret and describe visual information like graphs and diagrams. 

With these capabilities, you can unlock the data behind visuals and turn them into narrative elements that resonate with audiences.  3. A Connection Machine That Finds Stories Where Others See Statistics Great science communication isn’t about dumbing things down — it’s about building bridges between technical ideas and the broader public.

GPT-5.2 shows notable improvements in abstract reasoning compared with earlier versions, based on internal evaluations on academic reasoning benchmarks. 

For example, teams working on novel materials science or emerging health technologies can use this reasoning capability to highlight connections between technical results and real-world impact — something that previously required hours of interpretive work.

These gains help the AI spot patterns and relationships that can form the basis of compelling storytelling.  4. Accuracy That Gives You More Peace of Mind...When Coupled With Human Oversight Let’s address the elephant in the room: AI hallucinations.

You’ve probably heard the horror stories — press releases that cited a study that didn’t exist, or a “quote” that was never said by an expert.

GPT-5.2 has meaningfully reduced error rates compared with its predecessor, by a substantial margin, according to OpenAI 

Even with all these improvements, human review with your experts and careful editing remain essential, especially for anything that will be published or shared externally.  5. The Speed Factor: When “Urgent” Actually Means Urgent With the speed of media today, being second often means being irrelevant.  GPT-5.2’s performance on workflow-oriented evaluations suggests it can synthesize information far more quickly than manual review, freeing up a lot more time for strategic work.  

While deeper reasoning and longer contexts — the kinds of tasks that matter most in research translation — require more processing time and costs continue to improve. 

Savvy communications teams will adopt a tiered approach: using faster models of AI for simple tasks such as social posts and routine responses, and using reasoning-optimized settings for deep research.   Your Action Plan: The GPT-5.2 Playbook for Comms Pros  Here’s a tactical checklist to help your team capitalize on these advances.

#1 Select the Right AI Model for the Job: Lowers time and costs • Use fast, general configurations for routine content
• Use reasoning-optimized configurations for complex synthesis and deep document understanding
• Use higher-accuracy configurations for high-stakes projects

#2 Find Hidden Ideas Beyond the Abstract: Deeper Reasoning Models do  the Heavy Work • Upload complete PDFs — not just the 2-page summary you were given
• Use deeper reasoning configurations to let the model work through the material

Try these prompts in ChatGPT5.2 “What exactly did the researchers say about this unexpected discovery that would be of interest to my <target audience>? Provide quotes and page references where possible.”

“Identify and explain the research methodology used in this study, with references to specific sections.”

“Identify where the authors discuss limitations of the study.”

“Explain how this research may lead to further studies or real-world benefits, in terms relatable to a general audience.”


#3 Unlock Your Story  Leverage improvements in pattern recognition and reasoning.

Try these prompts: “Using abstract reasoning, find three unexpected analogies that explain this complex concept to a general audience.”

“What questions could the researchers answer in an interview that would help us develop richer story angles?”


#4 Change the Way You Write Captions Take advantage of the way ChatGPT-5.2 translates processes and reasons about images, charts, diagrams, and other visuals far more effectively.

  
Try these prompts: Clinical Trial Graphs: “Analyze this uploaded trial results graph upload image. Identify key trends, and comparisons to controls, then draft a 150-word donor summary with plain-language explanations and suggested captions suitable for donor communications.”

Medical Diagrams: “Interpret these uploaded images. Extract diagnostic insights, highlight innovations, and generate a patient-friendly explainer: bullet points plus one visual caption.”
	

A Word of Caution: Keep Experts in the Loop to Verify Information Even with improved reliability, outputs should be treated as drafts.  If your team does not yet have formal AI use policies, it's time to get started, because governance will be critical as AI use scales in 2026 and beyond.  

A trust-but-verify policy with experts treats AI as a co-pilot — helpful for heavy lifting — while humans remain accountable for approval and publication.    The Importance of Humans (aka The Good News)  Remember: the future of research communication isn’t about AI taking over — it’s about AI empowering us to do the strategic, human work that machines cannot.

That includes:
	•	Building relationships across your institution
	•	Engaging researchers in storytelling
	•	Discovering narrative opportunities
	•	Turning discoveries into compelling narratives that influence audiences

With improvements in speed, reasoning, and reliability, the question isn’t whether AI can help — it’s what research stories you’ll uncover next to shape public understanding and impact.



FAQ  How is AI changing expectations for accuracy in research and institutional communications?  AI is shifting expectations from “fast output” to defensible accuracy. Better reasoning means fewer errors in research summaries, policy briefs, and expert content—especially when you’re working from long PDFs, complex methods, or dense results. The new baseline is: clear claims, traceable sources, and human review before publishing.
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Why does deeper AI reasoning matter for communications teams working with experts and research content?  Comms teams translate multi-disciplinary research into messaging that must withstand scrutiny. Deeper reasoning helps AI connect findings to real-world relevance, flag uncertainty, and maintain nuance instead of flattening meaning. The result is work that’s easier to defend with media, leadership, donors, and the public—when paired with expert verification.
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When should communications professionals use advanced AI instead of lightweight AI tools?  Use lightweight tools for brainstorming, social drafts, headlines, and quick rewrites. Use advanced, reasoning-optimized AI for high-stakes deliverables: executive briefings, research positioning, policy-sensitive messaging, media statements, and anything where a mistake could create reputational, compliance, or scientific credibility risk. Treat advanced AI as your “analyst,” not your autopilot.
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How can media relations teams use AI to find stronger story angles beyond the abstract?  AI can scan full papers, grants, protocols, and appendices to surface where the real story lives: unexpected findings, practical implications, limitations, and unanswered questions that prompt great interviews. Ask it to map angles by audience (public, policy, donors, clinicians) and to point to the exact sections that support each angle.

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How should higher-ed comms teams use AI without breaking embargoes or media timing?  AI can speed prep work—backgrounders, Q&A, lay summaries, caption drafts—before embargo lifts. The rule is simple: treat embargoed material like any sensitive document. Use approved tools, restrict sharing, and avoid pasting embargoed text into unapproved systems. Use AI to build assets early, then finalize post-approval at release time.

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What’s the best way to keep faculty “in the loop” while still moving fast with AI?  Use AI to produce review-friendly drafts that reduce load on researchers: short summaries, suggested quotes clearly marked as drafts, and a checklist of claims needing verification (numbers, methods, limitations). Then route to the expert with specific questions, not a wall of text. This keeps approvals faster while protecting scientific accuracy and trust.

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How should teams handle charts, figures, and visual data in research communications?  AI can turn “chart confusion” into narrative—if you prompt for precision. Ask it to identify trends, group comparisons, and what the figure does not show (limitations, missing context). Then verify with the researcher, especially anything involving significance, controls, effect size, or causality. Use the output to write captions that are accurate and accessible.
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Do we need an AI Use policy in comms and media relations—and what should it include?  Yes—because adoption scales faster than risk awareness. A practical policy should define: approved tools, what data is restricted, required human review steps, standards for citing sources/page references, rules for drafting quotes, and escalation paths for sensitive topics (health, legal, crisis). Clear guardrails reduce fear and prevent preventable reputational mistakes.


If you’re using AI to move faster on research translation, the next bottleneck is usually the same one for many PR and Comm Pros: making your experts more discoverable in Generative Search, your website, and other media. ExpertFile helps media relations and digital teams organize their expert content by topics, keep detailed profiles current, and respond faster to source requests—so you can boost your AI citations and land more coverage with less work.                                             For more information visit us at www.expertfile.com  

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