Matrix Group International

Category: AI

  • Using AI to Power Smarter Membership and Marketing Strategies

    Using AI to Power Smarter Membership and Marketing Strategies

    Let me be blunt: if your AI strategy is focused on writing blog posts faster, generating social captions, or drafting catchier emails, you’re thinking too small.

    Yes, AI can absolutely help with those things. And yes, it can save your team time, but that’s not where the real value is. The real opportunity lies in using AI to rethink how your association operates: how you engage members, how you drive revenue, how you design experiences, and how you make decisions.

    That’s the shift from tactical AI to strategic AI. And for associations, it’s a big one!

    Right now, most organizations are applying AI at the end of the process. They’re using it to write an email, draft a blog post, summarize a report, or clean up meeting notes. There’s nothing wrong with that; those are useful applications, and they can save time.

    But when you use AI at the beginning of the process, you start improving the strategy itself. Instead of asking AI to write a renewal email, you can ask it to help you rethink your renewal strategy. You can explore which members are most at risk, when outreach should happen, which messages are likely to connect, and which channels are most effective. You can look at the full member journey and ask where friction exists and where intervention could make a difference.

    That’s a very different use of AI. At that point, you’re not just improving the content, you’re improving the entire content strategy.

    Most associations are rich in data, but poor in insight. They have no shortage of reports about renewal rates, meeting registrations, email performance, website traffic, and course attendance. The problem is that most of those reports tell you what already happened and stop there, when what you need to know is what’s likely to happen next. 

    That’s where AI can be especially useful. It can help associations move from reporting to intelligence by identifying patterns, surfacing risk, and helping teams act earlier. For example, AI can support:

    • Renewal risk scoring, so staff can prioritize the members who may need attention now, before it’s too late
    • Engagement trend analysis, so early signs of disengagement don’t go unnoticed
    • Event attendance prediction, so planning decisions are based on likely behavior rather than instinct
    • Signal detection, so staff can spot changes in member behavior before those changes show up in a year-end report

    That’s where the conversation gets more strategic. If you knew three months earlier that a member was at risk, what would you do differently?

    For years, many associations have delivered broad, generalized experiences because personalization felt too difficult or too expensive. Everyone got the same onboarding. Everyone saw the same website content. Everyone received roughly the same messaging. That’s not really a member experience; that’s just content distribution. 

    AI makes it easier to tailor the experience based on what members care about, how they behave, and where they are in their professional journey. That could mean:

    • Personalized content recommendations on your website
    • New member onboarding journeys based on job role, title, industry experience, and so much more
    • Tailored messaging, based on your generation cohort (i.e., talk to GenZ differently from GenX), interests, and engagement history

    Imagine a member logging in and seeing content that actually reflects what they care about. That’s not a future-state idea. That’s achievable now. 

    Mass emails are now remarkably easy to draft and send out. But just because content is easier to produce with AI, doesn’t mean that you should be messaging more. Quite the opposite, actually. The more messages we send, especially the ones that aren’t highly tailored or personalized, the more ineffective they become. 

    What AI can do, when used well, is help your team communicate more intentionally by improving segmentation, timing, and relevance. AI can help staff:

    • Identify disengaged members and trigger re-engagement
    • Surface topic interest and follow up with relevant content
    • Flag highly engaged members who may be ready for volunteer leadership, committee outreach, or a more personal touch from leadership.

    That’s a much better use of AI than simply flooding your members with more emails! 

    Most organizations are still thinking about AI as an internal productivity tool. That’s a good start, but what if AI became part of your member value proposition?

    Here are some of the things Matrix Group clients are working on in this area:

    • An AI-powered knowledge assistant
    • A compliance or standards guide
    • A career pathway tool
    • A skills gap analyzer

    For many organizations, this is the next step. Not just using AI behind the scenes, but building it into the member experience in a way that strengthens your association’s value proposition.

    If time and budget weren’t constraints, what would you build for your members?

    Associations also need to think about how AI is changing the way people discover information. People are no longer searching and clicking through pages of links to find the answer they’re looking for. They’re asking a question in Google, ChatGPT, Gemini, or even your site search and expecting a direct response in a succinct, complete narrative, not a list of links. 

    That shift has real implications. It means your content can’t just exist. It has to be structured in a way that makes your expertise easy to find, easy to interpret, and easy for answer engines to cite.

    So here’s the question: when someone asks an answer engine about your industry or profession, does your association show up in the answer?

    AI answer engines like Gemini, Claude, and ChatGPT prioritize:

    • Clear questions and answers
    • Structured content
    • Plain language
    • Accessible expertise

    This is where AEO and GEO come into play. Is your content structured to provide the AI answer engines with the answers that people are looking for? What content should be public and what content should be members-only?

    This can feel like a lot, because it is.

    Moving from tactical to strategic use of AI isn’t about adding one more tool to your stack. It’s about rethinking how your association works: across membership, marketing, education, research, volunteer management, and so much more.

    The good news? You don’t have to do everything at once. Start with one area:

    • Membership renewals
    • New member onboarding
    • Event engagement
    • Content strategy

    Pick an area where better intelligence, better personalization, or better decision-making could improve results for your organization, then ask a better question. Not “How can we use AI?” but “How could we redesign this process, this experience, or this strategy so it works better for members and for the organization?”

    At Matrix Group, this is exactly the work we’re doing with associations every day. Not just helping teams use AI to move faster—but helping them:

    • Rethink member journeys
    • Identify opportunities for personalization
    • Connect systems to enable smarter experiences
    • Uncover new ways to deliver value and drive revenue

    We know that for associations, the goal isn’t just efficiency. The goal is a stronger, more relevant, more valuable association. And AI, used strategically, can help you get there.

    So I’ll leave you with one final question: 

    Are you using AI to do what you’ve always done, just faster?
    Or are you using it to become something better?

  • Reflections and Predictions: What Associations Should Be Thinking About in 2026

    Reflections and Predictions: What Associations Should Be Thinking About in 2026

    Every January, I like to reflect on the previous year and consider what the coming year might hold for associations, nonprofits, and Matrix Group. This year, I did something different. I invited a few of my amazing team members at Matrix Group to join me on our podcast, Associations Thrive, to talk about the major trends they saw in 2025 and what they believe is coming in 2026.

    Joining me were Dave Hoernig (VP of Software Engineering), Jessica Parsley (Director of Project Management), and Alex Pineda (Creative Director). We had a wide-ranging conversation, and here are the key takeaways and predictions from our conversation:

    AI was, unsurprisingly, the biggest theme of 2025. Jessica talked about how many of our clients are turbocharging their teams by:

    • Investing in AI skills and training
    • Creating internal policies for responsible AI use
    • Building custom GPTs to speed up content creation
    • Using AI to streamline editing, content repurposing, and task management

    Dave shared how AI is revolutionizing content migration, especially turning PDF documents into accessible, searchable HTML. He also brought up a big existential question facing associations:

    What content should be visible to AI, and what should remain members-only?

    He talked about how associations are starting to experiment with making abstracts public while keeping full articles gated; this is the same approach academic publishers have used for years.

    AI is also influencing how we format content to make it discoverable to AI engines. Schema markup, summaries, and multimedia versions (like read-alouds) are increasingly important.

    Alex noticed a major shift in web design: associations are doing a better job of telling the story not just of the association, but of the profession or industry they represent. These “About the Industry” sections:

    • Help the public understand the value of the profession
    • Position the association as a thought leader
    • Offer lawmakers, potential members, and partners important context

    But it’s not easy. Crafting this content requires strategic thinking, consensus building, and often new storytelling skills.

    Jessica saw that many associations felt more budget-constrained in 2025. But instead of just of delaying projects, they asked:

    • “What small changes can we make to our website and email campaigns NOW that will have a big impact?”
    • “What are the biggest pain points experienced by our members or staff?”
    • “Can analytics guide our next move?”

    Alex noted that we’re increasingly using analytics to make smart, incremental improvements, like optimizing navigation, restructuring key pages, or adjusting content strategy. Full redesigns are great, but if there isn’t time or budget, then light refreshes are the way to go.

    There is a growing shift away from long blocks of text and toward audio, video, and interactive content:

    • Podcasts and read-aloud tools are making content more accessible.
    • Members, especially younger members, increasingly prefer to watch or listen, rather than read.

    Alex and Jessica both emphasized that younger generations are mobile-first, visual-first, and audio-first. If associations want to attract the next generation, their content and design strategies need to reflect that.

    We’ve talked about personalization for years, but 2025 was the year it became practical for more organizations.

    Dave shared that personalization is easier to implement now because:

    • You no longer need to manually tag every piece of content
    • AI can analyze member behavior and personalize on the fly
    • Tools can now offer Netflix-style, personalized recommendations based on user behavior and demographics

    Imagine offering a member a curated education journey based on their career stage. Duolingo is a great example of this! I’m an avid Duolingo-er and love that my practice lessons are customized just for me. That’s the future for associations and it’s already here.

    Alex noted that mobile traffic is growing, even if analytics still show desktop in the lead for most of our clients and their websites. Younger members are doing everything on their phones and they’re the members of the future. All of this means:

    • Mobile design needs to be more comprehensive
    • Voice navigation and voice search are increasingly relevant

    If it’s not easy to find or access your content via mobile or voice, you’re invisible to a big part of your audience.

    Jessica made a critical point: it will be harder than ever for associations to be seen as the authority in their industry. AI answer engines like ChatGPT and Gemini are giving users quick answers without attribution. That means your content might not be recognized as coming from your organizations. So how do associations stay relevant?

    One important answer: Double down on community.

    Associations will need to:

    • Create spaces (in-person and virtual) for connection and expertise-sharing
    • Offer value that can’t be replicated by an AI bot
    • Make membership the gateway to the best insights, not just the publicly available ones
    • Create smaller events, cohorts, and niche groups to create intimacy within the membership

    As we closed out the podcast, I shared a final hope: that the new wave of AI tools will level the playing field for smaller associations. These tools let even the smallest team:

    • Create great content
    • Design beautiful experiences
    • Offer personalized, member-driven services

    You don’t need a giant staff or massive budget to be effective in 2026. But you do need to be smart, strategic, and open to using AI tools to make your organization more high-performing and authoritative.

    So what do you think? What trends did YOUR organization see in 2025? What are you preparing for in 2026? Let’s keep the conversation going!

  • Are AEO and GEO More Important Than SEO?

    Are AEO and GEO More Important Than SEO?

    A client recently came to us because traffic to their site had dropped significantly. This organization relies on traffic from organic search to bring in prospective members and prospective course attendees. Looking at their analytics, we learned that it’s specifically traffic from Google that had dropped significantly. What was going on?

    If your site is experiencing a drop in referrals from Google, it’s probably because, as of the end of 2024, 60% of Google searches are zero-click. A zero-click search is when someone conducts a Google search, gets the answer they’re looking for without clicking, and calls it a day because they’ve gotten the answer(s) they need. Google used to refer us to the sites that had the answers we were looking for. Now Google gives us the answers.

    So what’s the answer? Today, the answer is AEO or Answer Engine Optimization and GEO or Generative Engine Optimization. AEO and GEO are the art and science of optimizing your website content for the AI answer engines like Google, ChatGPT, CoPilot, Claude, Bing, etc. We used to focus on SEO and search ranking, but today, it’s about providing Google and ChatGPT with the answers to visitors’ questions, and providing the content that the AI engines can consume and include as part of their reasoning.

    Does this mean SEO, or search engine optimization, is no longer important? Absolutely not! Sites that have deep, quality content, are quick to load, formatted well for search engine indexing, have lots of incoming links, and have high page rank are the sites that the AI engines are more likely to reference and cite. In other words, AEO and GEO are additional layers to your SEO strategy and today, they’re no longer optional.

    But will optimizing your site for the AI answer engines bring back the Google traffic? Sadly, I think not. As long as the answer engines provide quality responses to our queries (and the answers are getting better every day), we consumers will increasingly rely on the answer engines and NOT click on the site that was the source of the content in the first place.

    The challenge then for associations is to be THE SOURCE for the deep, hyper-specialized content that exists within the association’s content archive, among the subject matter experts within the staff and community, and in the heads of the community, the members themselves. 

    In other words, if I’m looking for general, consumer grade content to a question, I will likely get a high quality and accurate response from ChatGPT. But if I want the latest research, best practices, or obscure references, I need to go to the community where this deep knowledge exists – associations! Under this scenario, associations must double down on being found as the community where the deep knowledge exists, and educating members and prospective members on how and why the community and specialized knowledge cannot be gotten from an AI engine.

    I know, this is easier said than done, but this is the existential challenge for associations today. 

    So, is your association ready for the AEO and GEO wave? How are you distinguishing your association from the AI engines as the place for specialized knowledge AND community?

  • You Don’t Need an AI Strategy — You Need a Business Strategy Supported By AI

    You Don’t Need an AI Strategy — You Need a Business Strategy Supported By AI

    Everywhere I turn, someone is talking about their “AI strategy.” But here’s the truth: you don’t need an AI strategy. You need a business strategy, and AI should support it.

    Too many organizations start with technology. They chase tools, trends, and buzzwords before they’ve clearly defined the problems they’re trying to solve. That’s backward.

    Here’s how we believe you should think about AI:

    Start With the Problem, Not the Tool

    Don’t start by asking, “What can AI do for us?” Start by asking, “What problems are we trying to solve?” Every Thursday morning at 9am, there is an open meeting that anyone from the Matrix Group staff can attend. At first, we focused on AI learning, but we have shifted to talking about:

    • Where are the inefficiencies in our operations?
    • What repetitive tasks eat up staff time?
    • Where are members, customers, or employees frustrated by friction in their experience?
    • What tools or processes need re-engineering?

    Then, we solve! 

    I highly recommend holding regular meetings like this, where you discuss pain points, inefficiencies and missed opportunities. Once you’ve identified the pain points, prioritize them. Make a list of the top five challenges you need to address this year. Then, and only then, start exploring how to optimize and automate.

    AI Might Be the Solution—or It Might Not

    AI is powerful, but it’s not magic. Sometimes the solution involves AI. But sometimes the solution is a better database search, a better process for collecting data, better processes, new integrations, or clearer communication.

    Be open and curious about what’s possible with AI, but stay grounded in your goals. The right question isn’t, “How can we use AI?” It’s, “How can we work smarter, faster, and better?”

    And don’t forget to ask your vendors what they’re doing with AI. Many are already building AI into their systems — CRMs, AMSs, CMSs, and marketing tools — so you may already have AI capabilities available to you that solve some of your pain points.

    Successful AI Adoption Is More Than Tools

    Even if AI is part of the solution, success depends on people and process just as much as, if not more than, the technology at play. Successful AI adoption requires:

    • Executive buy-in. Leaders need to be curious about AI, understand what it can do, and use it themselves.
    • Process ownership. Who owns innovation in your organization? Who will manage these projects and ensure they actually move forward?
    • Ongoing support. AI isn’t “set it and forget it.” You’ll need to maintain, refine, and evolve your solutions over time. 

    In my experience, it takes at least six months for a new initiative or process to stick. If you lose focus after just a few months, you’ll be amazed by how quickly your organization drifts back to the old way of doing things. Keep following up, stay curious, and insist on ongoing tweaks and adjustments to the execution plan.

    The Bottom Line

    AI is an incredible tool, but it’s not a strategy. Your business strategy needs to come first.

    When you start with your goals, your pain points, and your priorities, you’ll identify the right opportunities to automate, streamline, and enhance what you already do best.

    And when AI supports that strategy rather than driving it, you’ll see real results.

  • Why Every Association Needs an AI Policy

    Why Every Association Needs an AI Policy

    Last month, Kevin Ordonez and I presented at .orgCommunity’s Solutions Day in Schaumburg, IL. Our session was focused on the AI journeys of associations. We asked attendees—mostly association CEOs, CIOs, and COOs—a series of questions about how their organizations are approaching AI.

    One statistic really stuck out: only 57% of respondents said their organization has an AI policy.

    Only 57%! That means that, for more than half of all associations in the room, it’s the wild west when it comes to staff usage of AI tools.

    And, believe me, your staff are using AI. Whether it’s ChatGPT, Microsoft Copilot, Grammarly, Canva, or one of a hundred other tools, your team is tapping into artificial intelligence to write, summarize, code, design, and more, whether or not you have an AI policy in place.

    So, Why Is an AI Policy Critical?

    1. Your Staff Are Already Using AI

    AI use is already happening in your organization, with or without your knowledge. Without a policy, that usage is likely unmonitored and inconsistent. Worse, it’s happening without any constraints or ethical guardrails.

    2. A Policy Sets Guardrails for Responsible Use

    At Matrix Group, we have a clear rule: confidential data must not be used with AI tools unless explicitly approved. This includes staff, member, and client data.

    An AI policy outlines which tools can be used, how they should be used, and what’s off-limits, especially when it comes to security, confidentiality, and compliance.

    3. It Reinforces Accountability

    AI tools are just that—tools. They can assist, accelerate, and even inspire, but at the end of the day we are still responsible for the final outputs. Whether it’s a blog post, a report, a financial analysis, or even code, the person using the tool must own the final result, and an AI policy can help keep your staff accountable.

    4. It Encourages a Healthy Culture of Innovation

    When staff know that leadership supports smart AI adoption, and has established boundaries for how to use it, they’re more likely to experiment in meaningful, responsible ways. A policy encourages discussion and learning, instead of shadow use of AI.

    What Should Be in a Basic AI Policy?

    An AI policy doesn’t have to be long, or perfect, to be effective. Even having a simple, one-page policy can make a big difference for your association. If you don’t have one, make one FAST that at least states:

    • No confidential data to be used in AI tools, unless specifically authorized.
    • Staff must take responsibility for the accuracy, legality, and appropriateness of all AI-generated content.

    Once you have a basic AI policy approved and in place, you can work on expanding it. Here are a few areas to consider:  

    • Responsible Use: What can AI be used for? What can’t it be used for?
    • Approved Tools: Which AI platforms are sanctioned by your organization, and why?
    • Confidential Data Protocols: How should employees request permission to use AI tools with sensitive data?
    • Storage and Retention: Where will AI-generated outputs be stored? Are records policies for AI work the same as human-generated work? Or are they different?
    • Meeting Use: Is it okay to use AI notetakers in staff or board meetings? What about client meetings?
    • Ethical Standards: What does “ethical AI use” look like in your profession or industry?

    Don’t wait for a crisis or data leak to spark this conversation in your organization.

    Instead, start simple. Invite your team to discuss the tools they’re using, learn from their experiments, and then use that knowledge to build an AI policy that protects your organization and supports innovation.

    Does your organization have an AI policy? If so, what does it cover? If not, what’s holding you back?

  • Can AI Create Your Website?

    Can AI Create Your Website?

    AI tools like Canva and ChatGPT promise fast, DIY website creation, but are they good enough for organizations with complex needs? This post explores what AI can (and can’t) do when it comes to website design, development, and content. From the convenience of AI-generated layouts to the irreplaceable value of human expertise, discover when AI might be “good enough” and when it’s just not the right fit.


    I recently saw an ad about how Canva can create a website with AI minutes. Canva allows customers to select a template, create images, and have AI create the content.

    I am a big Canva fan, so I got curious. Is this really possible? I went to Canva.com and decided to try and create a website for the book I’m writing about associations. Canva has some impressive options, but let me tell you, I still didn’t have a website after 45 minutes. Why? Because the choices were too overwhelming, I couldn’t find something that looked unique enough for my taste and I don’t know the Canva controls enough to create something that matches my personal brand or the Matrix Group brand.

    What about someone who IS really good at Canva? Could they create a website in minutes? Maybe not minutes, but maybe a few hours? Today, the answer is probably yes.

    BUT, will it be any good? 

    Today, the answer might be, it depends. It’s possible that AI can create a website for you or your organization that is good enough. But here are some things to think about:

    DIY (do it yourself) tools have always been great options for people and organizations that know exactly what they want. I used blogger.com to create a website for my personal podcast, KDramaChat.com. Is it amazing and unique? No, but it’s good enough. We’ve helped clients select a pre-built theme in WordPress for a conference and with a little setup, they were off to the races!

    But what if you need something more than a simple blog site or one-pager about something you’re fighting in Congress? Or a website that represents your entire organization, its values, its initiatives, and its impact?

    In my experience, our clients come to us because they have a vision or an inkling of what they want, but they don’t know how to get there.

    Often, a website redesign is a proxy for a conversation about who or what the organization wishes to become. So we use tools like interviews, analytics, mood boards, wireframes and design to help clients explore and ultimately decide what their end goal actually looks like. And many times, the conversations about what the website should look like, what content should get priority, and what the website should look like, have to be moderated by people who know how to achieve agreement between people of differing opinions. (My Project Managers excel at this.)

    I’m more and more impressed by what AI can do with images, videos and logos these days. BUT, more often than not, what AI creates needs to be massaged to make it better, to give the output authenticity, to make the designs have depth and personality.

    THIS depth and personality comes from skilled designers. At least for now, nothing beats the experience and eye of someone trained in design and branding. My designers absolutely use AI tools but they don’t rely on them exclusively. Sometimes they just need a little inspiration, sometimes AI gives them a base they can tweak into something fabulous, and sometimes they have to just do the work entirely on their own.

    My front-end and back-end developers are increasingly using AI code generators to help them build out website functionality. Whether it’s a custom post type, a directory, or an integration with a membership database, the code generators have come a long way. We’ve seen great productivity gains in this area. The catch here is that we’ve had to train the code generators on OUR coding standards and our code repository, AND every developer is still responsible for reviewing their work and having others test it.

    We joke at Matrix Group that we can often tell when content is AI-generated. AI loves to embark on things, or delve into things. Yeesh. Who talks or writes like that? I also find that AI content is often full of extraneous adjectives. The content might sound good, but it’s sometimes off brand, or way too flowery for my taste. Even worse, those adjectives can get us in trouble because they just aren’t true.

    Again, don’t get me wrong. I use AI tools for brainstorming and drafting, but what Gemini or chatGPT generates is never good enough, not for a writer like me, and, I suspect, not for my discerning and extremely professional clients. 

    By the way, I tried really hard to get AI to draft this blog post and it just couldn’t do it. I’ve had luck with other topics, but even when I provided detailed prompts and guidance, the end result sounded off. I guess some topics are still too nuanced for AI.

    I don’t think so, and I hope not. I think we still need trained and experienced professionals to develop the strategy, create the design, build the site, and write the content that will compel people to read more, join, register, purchase, or otherwise engage. 

    AI is a great companion for creating the designs, programs and content that make up our websites today, but we should still be the leaders of these web development journeys.

  • What is Answer Engine Optimization (AEO)? 

    What is Answer Engine Optimization (AEO)? 

    Summary: Answer Engine Optimization (AEO) is the strategy of structuring your content so it becomes the direct answer to specific questions people ask through Google and voice assistants like Siri or Alexa. It builds on strong SEO practices and helps your content show up when there’s only room for one answer. For associations, AEO is a powerful way to get your expertise in front of the right people—especially as zero-click searches and AI-generated summaries become the norm. This post breaks down what AEO is, how it’s different from SEO, and how to start optimizing your content today.


    How we search, and how we get our answers, has fundamentally changed in the last few years. Heck, even in the last few months, thanks to Google’s AI Overviews. 

    We’ve all been trained to stop typing vague keyword combos and start asking real, specific questions into our favorite search engine. For example, instead of searching for “nursing license CE requirements,” you’re more likely to type (or say): “How many CE credits do you need to renew your nursing license in Virginia?” or “What are the continuing ed requirements for an RN in VA?”

    And what happens when you do that?

    Before late 2024, you’d see a list of links: sponsored ones first, followed by organic results. Now, more often than not, you’re served a single answer right at the top. Sometimes, the answer is just a snippet, sometimes it’s an AI-generated summary, sometimes it’s read out loud by a smart speaker while you’re elbow-deep in dinner prep.

    And most of us? We take the answer and move on. That’s why, by the end of 2024, nearly 60% of searches were zero-click, meaning people got what they needed without ever clicking through. And that’s after AI Overviews had only been fully rolled out for a few months!

    So what can you do to stay visible and relevant in this new, zero-click world? That’s where Answer Engine Optimization (AEO) comes in.

    Answer Engine Optimization, or AEO, is the practice of structuring and optimizing your content so it becomes the answer when someone asks a question in a search engine like Google or to voice assistants like Siri or Alexa.

    Unlike traditional SEO, which aims to get you onto page one of search results, AEO helps you land the single, direct answer that shows up first, whether it’s a featured snippet, an AI Overview, or a voice assistant reading it aloud.

    In short, AEO is what helps you show up as THE answer, or the top answer to a user’s query.

    Not at all. Following SEO best practices is still incredibly important; search engines haven’t gone away, the results are just shifting. Search engines still rely on the same solid foundation you’ve (hopefully) been building all along: a fast, well-structured website, relevant backlinks, and high-quality content that’s written by people who know what they’re talking about. Google’s E-E-A-T framework (Experience, Expertise, Authoritativeness, and Trustworthiness) is still the gold standard for what “good” content looks like.

    AEO adds a new layer to SEO. It compliments and enhances the good work you’ve been doing for SEO, with an added focus of helping AI-powered tools pull the right answers from your content. This means writing clearly, anticipating questions, and structuring and organizing content in a way that makes sense to both humans and machines. 

    Think of it this way: SEO gets you invited to the party; AEO hands you the microphone.

    Good news: this doesn’t require starting from scratch or mastering some new technical magic. AEO is really about adjusting how you structure and present the content you already have, so it works for real people and the machines scanning for answers. 

    • Start with real questions. Your members aren’t typing in vague phrases. They’re asking complete, specific questions, so your content should reflect that. Use tools like Google Analytics, Search Console, or even the “People Also Ask” section in search results to find the actual queries people are using.
    • Match those queries in your headings. Use those natural-language queries as your H2s and H3s, just like the subheadings in this post. It helps search engines and AI tools understand what you’re answering, and it makes your content easier to scan.
    • Lead with the answer. Give the short, direct response first, ideally at the top of the page and within the first sentence or two under each question. Think of it as the takeaway upfront. Then, once you’ve answered it clearly, go ahead and expand with context and details.
    • Add FAQs to high-impact pages. Pages like membership, certification, and events are where your members have questions and are looking for answers. Adding a short FAQ section at the bottom is a great way to surface that info in an answer-friendly format.
    • Use schema markup. This step may require help from your web team, but it’s worth it. Schema helps search engines understand your content structure – especially FAQs, definitions, and how-to content – and makes it more likely you’ll show up in AI Overviews and voice results.
    • Think about how you write and structure your content. Use natural, conversational language, break up content into short paragraphs, bullet points, or numbered steps where appropriate, and always answer before you elaborate.
    • Surface your authority. Associations have deep, authoritative content that’s often buried in PDFs or behind logins, and AI can’t access that. Creating public-facing landing pages that summarize key insights and link to your gated resources is a great way to give search engines and AI models content they can index and cite without feeding your precious, protected content to the LLMs. 

    Answer Engine Optimization isn’t just a buzzword. It’s a response to how real people are searching today, and how AI is changing the way content gets found, surfaced, and quoted.

    For associations, it’s a huge opportunity. You already have the expertise, the credibility, and the authoritative content. AEO helps you make that knowledge more accessible – not just to search engines, but to the people asking specific, timely questions about your industry. 

    This is your chance to take what you already do well – education, advocacy, standards, guidance – and position your organization as THE authority in search and AI results. 

    Want to learn more about AEO and get your team up to speed? Matrix Group offers an AEO + GEO training tailored specifically for associations. You’ll walk away with a clear understanding of how this shift impacts your content strategy and exactly how to adapt your existing content to help you show up in voice and AI-driven search results.

    Get in touch to learn more and schedule a training! 

  • AI Note-Taking Part 2: Lessons from Five Months of Testing and Refining

    AI Note-Taking Part 2: Lessons from Five Months of Testing and Refining

    After five months of testing AI note-taking tools, Matrix Group discovered that the right tool is only part of the solution. Fathom worked well but didn’t match our workflows, so we built a custom GPT that better fit our needs. Still, adoption lagged until we refined the process, simplified formatting, and gathered ongoing feedback. Real value came when AI was aligned with behavior, not just technology. This blog post explains what we learned and how others can avoid common pitfalls.


    A few months ago, we shared how Matrix Group chose Fathom as our AI-powered note-taking app after testing multiple options. It was an exciting step in our AI journey—one that promised to make note taking more accurate and efficient, ensuring that key takeaways didn’t get lost in the shuffle.

    But as we started using Fathom more regularly, we ran into some challenges. Not because the tool wasn’t working—it was!—but because it wasn’t working for us in the way we needed it to.

    When we first implemented Fathom, we were excited about how well it captured and summarized our meetings. The AI did exactly what it was designed to do—generate summaries, highlight key points, and pull out action items. 

    But as we started using it regularly, we realized that Fathom wasn’t quite working for us. Here’s where things got tricky: 

    • The way Fathom labeled action items didn’t quite align with how our team structures follow-ups. The AI was tagging both “to-dos” and “next actions,” but in a way that didn’t match our workflow, which meant our project managers had to do additional editing to make the notes truly actionable.
    • The formatting of the notes wasn’t translating well into our client extranet. This meant extra steps to clean things up before sharing them out with our clients.
    • We weren’t experiencing the time savings we expected. Instead of eliminating work, we found ourselves reworking AI-generated notes to fit our processes.

    These issues didn’t mean Fathom was a bad tool—just that it wasn’t the perfect fit for how we work. So, we started exploring ways to tailor AI-generated meeting notes more precisely to our needs.

    We asked the big question: What if we wrote a custom GPT for note taking?

    Since we already used custom GPTs for other tasks and workflows, we were confident that a custom GPT could help us process meeting transcripts and generate notes formatted exactly how we wanted. And, it did! 

    We created a custom GPT that would take transcripts from Zoom, Teams and Google Meet and generate meeting notes that:

    • Listed the meeting attendees, grouped by organization
    • Organized the notes by topic; the notes were appropriately detailed (Fathom sometimes summarized discussions too much)
    • Listed the To Do items at the top and bottom of the notes
    • Used limited formatting so the notes could be sent through our company intranet

    This new custom notetaker was amazing. We rolled it out to the project managers and cheered when they said this notetaker was better than Fathom.

    A few weeks later, we discovered a problem: No one was using our new custom notetaker

    Why? The process required extra steps—logging into Zoom, downloading the transcript, uploading it to our custom GPT, and retrieving the notes. It was an extra layer of work that most people weren’t willing to take on.

    To make adoption easier, we assigned a team member to handle the AI note-taking process for everyone. The idea was simple: instead of expecting project managers to run the process, we’d do it for them and distribute the notes.

    Yet when we followed up, we realized something surprising: PMs still weren’t using the notes.

    Why?

    • The formatting was still too complex for our extranet.
    • The AI was summarizing too aggressively, stripping out details that were important for context.
    • Even with automation, there was no real buy-in.

    It took five months of testing, tweaking, and getting feedback before we finally got the process right. We adjusted our custom GPT to balance summaries with key details, stripped out unnecessary markup, and made sure the process was as seamless as possible.

    But the biggest lesson? Tools alone don’t change behavior.

    For AI adoption to stick, there needs to be:

    • Ongoing feedback: We had to regularly check in to see what was working and what wasn’t.
    • Follow-through: Just setting up a tool isn’t enough. We had to make sure people were actually using it.
    • Authority to drive change: Someone with authority over the process needs to champion the change.
    • Iteration: Refinement takes time. Expect to make several changes along the way.

    After months of refining, our AI note-taking process finally works the way we need it to. We’re getting the right level of detail, in the right format, and without creating extra work.

    But if there’s one thing we’ve learned, it’s this: AI tools (or any technology for that matter!) are never “set it and forget it.” They require tuning, testing, and continuous feedback to actually deliver value.

    We’d love to hear from you. Have you experimented with AI for note-taking? What worked and what didn’t? Let’s compare notes!

  • How to Customize ChatGPT to Avoid Overused AI Words

    How to Customize ChatGPT to Avoid Overused AI Words

    CEO Joanna Pineda and I have a running joke that whenever we see “delve” and “embark” used in the same paragraph (even better if it’s the same sentence) we wager a lot that AI was involved in the drafting.

    If you’ve been using AI tools like ChatGPT for content creation, you’ve probably noticed this, too. AI definitely favors certain words – tapestry, synergy, foster, beacon, treasure trove. And while there’s nothing wrong with these words, overuse of them (whether AI generated or not) can make people think your content is AI-generated, which can impact credibility.

    So how do you make sure ChatGPT avoids these words, or other words that don’t sound like you, when helping you to draft or edit content? We’ve been experimenting with this a lot at Matrix Group, and one of the most helpful techniques I’ve found is building and refining a personal word exclusion list. Here’s how to do it:

    The first step is to figure out which words don’t work for you and make a list of them. This can include words that are common in AI outputs AND words your organization likes to avoid—maybe they’re too corporate, too cliché, or just don’t match your brand’s voice. 

    A few ways to pinpoint words to avoid:

    • Look at past content. Compare AI-generated text to your own writing. Do you naturally avoid words like leverage or paramount? If so, add them to the exclusion list. 
    • Watch for AI patterns. If you keep seeing the same phrases pop up in AI responses, they’re probably overused.
    • Do some research. There are also many blog posts and Reddit threads that list overused AI words, some of which are industry-specific; these blog posts can be very helpful. 
    • Gut check. If a word makes you cringe every time you see it, it’s worth cutting, whether it’s commonly used by AI or not. 

    Way before AI, Matrix Group had a list of words that, while commonly used in our industry, didn’t match our brand voice, so we agreed to strike from our communications and marketing. Identify words like that, too!

    Here is a list of words that I personally exclude because they show up too often in AI-generated content AND are words I wouldn’t commonly use in my own writing:

    Delve, Embark, Synergy, Underscore, Foster, Groundbreaking, Game changer, Endeavor, Enlighten, Esteemed, Shed light, Tapestry, Treasure trove, Testament, Peril, Amplify, Beacon, Convey, Resonate, Interplay, Adhere, Paramount, Furthermore, Profound, Indelible, Bespoke, Cognizant, Encompass, Hitherto, Leverage, Realm, Utilize.

    Keep a running list of your “exclude” words in an easy to access place like a Google doc. 

    Once you’ve got your list, you have two ways to guide ChatGPT (or any AI tool) to avoid these words:

    You can instruct your AI tool with every prompt:

    “Write a blog post about AI customization. Do not use the following words or derivatives of the words: delve, embark, synergy, utilize, leverage, foster….”.

    This method is great for flexibility, but it requires extra effort every time you prompt the AI.

    Some AI tools allow you to set global preferences, which is a huge help. While ChatGPT doesn’t have a built-in “ban list” for words (yet), there IS a way to customize your account so that it avoids your list of words. Here’s how:

    Navigate to your account, and click on “Customize ChatGPT.”

    Scroll down to “Anything else ChatGPT should know about you?” and enter the following: 

    Avoid the following words and derivatives of these words:
    [Your Word List Goes Here]

    Save, and you’re done! 

    Once you’ve built your exclusion list, the next step is staying flexible. It’s easy to get carried away and try to cut every word that feels even remotely “AI-generated,” but overcorrecting can be just as limiting as not correcting at all.

    Your list of banned words should be a living document, not a permanent rulebook. Check your list regularly. If your writing starts feeling too stripped down or bland, it might be because your exclusions list is too long. Or, if new patterns start creeping into your AI drafts, consider adding those words or phrases to the list.

    Here’s the balance we’ve found that works best:

    • Keep your global exclusions minimal. Save the big offenders (like delve and embark) for your always-off list.
    • Use prompt-level exclusions for everything else. When you want to avoid specific words in a particular piece of content, include those directions in the prompt instead of your default settings.

    Also keep in mind that even the best AI outputs will never sound perfectly you, because they’re not! Sometimes the best thing to do is simply edit words here and there to make them sound more like you, without having to ban certain words and phrases entirely. ChatGPT should help you draft your content, not write it in its entirety. In my experience, ChatGPT can get me started, but then I edit heavily to put heart back into my writing, and make it sound authentically me or authentically Matrix Group. 

    Remember, AI can be an amazing tool, but it works best when it reflects your brand’s unique voice. By identifying overused words and guiding ChatGPT to avoid them, you’ll get results that sound more natural, more original, and more you.

    Give it a try! Next time you generate content, test out a prompt that includes exclusions, and see how it changes the output.

    What words do you avoid in writing? Let’s compare notes!

  • 5 Critical Facts You Need to Know About AI

    5 Critical Facts You Need to Know About AI

    Artificial Intelligence (AI) is not just a buzzword—it’s a technological revolution transforming how we live, work, and innovate. From automating routine tasks to delivering groundbreaking insights, AI is becoming indispensable in today’s world. 

    But with so much hype and noise, it’s easy to feel lost in the excitement. What’s truly important, and what’s just marketing speak? Whether you’re exploring AI for the first time or looking to expand its use in your organization, understanding the key facts is crucial to making informed decisions.

    Let’s explore five critical insights that will help you harness AI’s potential with clarity and confidence.

    One of the most important things to understand about AI is that the term itself is not regulated or validated in any way. Essentially, anyone can slap the label “AI-enabled” onto their product, even if it’s not using any true AI technologies. For example, a simple chatbot that follows pre-programmed scripts (“if A then B…”) may be marketed as AI but without true machine learning or natural language processing capabilities. A more sophisticated AI chatbot might employ generative AI to produce more natural sounding answers, access all the information the model was trained on, and use its prompts and specific documents to generate a response specific to the field chatbot is designed for. 

    It’s critical to ask the right questions when evaluating products or services marketed as AI-powered. What kind of AI are they using? Is it machine learning, natural language processing, or something else? Which core AI technology is it built upon? If you’re investing in AI, you want to make sure you’re getting access to the full power and potential that true AI systems provide.

    Generative AI, the type of AI used to create text, images, and even code (such as ChatGPT), is currently getting the lion’s share of the attention. However, it’s important to know that generative AI is just one subset of a much broader AI ecosystem. “AI” is an incredibly broad term, encompassing everything from how Netflix recommends TV shows, to how a Roomba figures out where to vacuum, to the technology that powers self-driving cars. 

    The most common applications of AI are:

    • Machine learning, which helps systems learn from data
    • Natural language processing, which helps machines understand and generate human language
    • Computer vision, which enables machines to interpret and process visual data.

    While generative AI may be the most accessible for everyday use right now, it’s only a chunk of the iceberg. 

    Although many companies claim to be revolutionizing generative AI, the reality is that just a handful of major players are truly leading the charge. Tech giants like OpenAI, Google DeepMind, and Anthropic are responsible for much of the core AI technology that drives today’s innovations. These companies are at the forefront of AI research and development, creating the foundational tools that countless others build upon

    While these big players provide the critical building blocks, a growing number of companies across various industries are using these technologies to create unique and specialized solutions. These smaller players may not be developing the core AI algorithms, but they are applying AI in innovative ways to solve real-world challenges in fields like healthcare, marketing, finance, and more. By customizing and adapting AI to meet specific needs, they bring even more value to the table, pushing AI into new and exciting directions.

    So when you’re evaluating genAI solutions, don’t be surprised or discouraged if the product is built on technology from these big players. In fact, that often means the solution is grounded in cutting-edge, reliable advancements. What matters is how that technology is being adapted and enhanced to deliver value to your organization. With that being said, you should absolutely ask what core AI technology is being used to power their systems. It matters!

    It’s been said many times about many things that your outputs are only as good as your inputs. The same is true for generative AI: the prompt, i.e., what you input into the AI system, determines the quality and relevance of the output you get back. This is why “prompt engineering” has become a new skill that’s highly valued in the AI space.

    For example, if you ask a generic question, you’ll likely get a generic answer. However, a well-crafted, detailed prompt can lead to more nuanced, sophisticated, and useful results. Experimenting with different ways to phrase your prompts and providing specific context can help you get the most accurate and helpful responses from generative AI. For a deeper dive into AI prompting, check out our recent blog post on Creating a Custom GPT (the same concepts from the post apply to standard prompting!)

    AI is a powerful tool, but even the most advanced systems can make mistakes. Whether it’s generating inaccurate information, misinterpreting data patterns, or offering biased results, AI is not infallible. That’s why verification is key. The best practice isn’t to assume AI’s outputs are always right—it’s to treat them as one step in your decision-making process.

    Generative AI tools like ChatGPT, for instance, can aggregate vast amounts of information, but they sometimes pull together half-truths or inaccuracies from multiple sources. Machine learning systems can misread data trends, and autonomous technologies, such as self-driving cars, have demonstrated their limitations. Whether you’re using AI for content creation, data analysis, or decision-making, always cross-check the results and ensure accuracy before acting upon them.

    AI has the potential to revolutionize industries and transform how we work, but understanding its strengths, limitations, and how to use it effectively is key. Take the time to ask the right questions, experiment with different AI tools, and always verify your results. The future of AI is bright, and with the right approach, you can harness its power to drive innovation and efficiency in your organization. So dive in, experiment, and see how AI can enhance your workflows!

    To learn more about the ways that Matrix Group is leveraging AI, check out some of our other recent blog posts, and if you are curious about the custom AI solutions we are developing, contact our solutions team at solutions@matrixgroup.net