Priorities for AI in Professional Associations

I was recently invited to participate on a panel on AI in continuing education and training. One of the questions the moderator asked me was what priorities need to be part of a minimum viable AI strategy for professional associations. I offered three tips, but now that you're here, I'll give you five.

At this point having an AI policy in place guiding ethical and judicious use, protecting time for your team to explore AI-enabled capabilities for learning (new tools and features are released frequently), and prompt engineering are old news. If you aren't already on top of these, you're behind. Don't despair, just get moving on it.

Here's where we are now.

LLM Optimized Websites

In a world driven by web browsing and searching, SEO helps us find what we need. It also helps organizations present themselves effectively. In a generative AI world, where behavior is shifting from web searches to AI answer engines, optimizing for LLMs is essential. This ensures they can find and recommend you (AEO or GEO).

The tipping point has tipped. OpenAI added shopping to ChatGPT, and Wired Magazine reported that ChatGPT is already running a billion (BILLION) web searches per week. And that's just one LLM. Soon, AI agents will be the ones searching the web on our behalf, synthesizing results, and prioritizing content.

This is particularly important for professional associations that serve as clearinghouses for industry expertise. But is that expertise visible? Can an LLM find it and recommend you as the answer to a prospective learner's question about their career development goals?

Associations often place the richest and most specialized education-related content behind a member paywall. This is part of the member value proposition business model. However, AI has changed how people use the internet. LLMs don't care about keywords or gated content. We need them to find our content. We must at least provide summaries or teasers that are discoverable and highlight our content leadership.

Don't abandon SEO; instead, embrace Answer Engine Optimization (AEO). While best practices are evolving, consider these points: long-tail keywords, quotable expertise, FAQ and How-to schema, and consensus via mentions across the web.

SME Collaboration

Industry professional subject matter experts (SMEs) are a primary source for content in association training through their speaking, publications, and content writing with us. Big shifts are unfolding in how we develop content and work with subject experts.

AI offers us opportunities to collaborate with SMEs in new ways. It streamlines workflows, automates content review processes, and shifts the role of SMEs from writers to editors. No more blank page syndrome derailing timelines and launch dates.

The engine behind this is what I call Atomic Learning Design. Think of your content as data (AI does). Your body of knowledge needs to be freed from locked formats like books, PDFs, and PowerPoint decks. It should live in a proprietary LLM that you can query. SMEs will be your collaborative partners, verifying content outlines, prioritizing concepts, and editing content. We will train them to validate source material, correct bias, and help us keep our AI-enabled knowledge base accurate and up to date.

This is where we are now, but it's not the end game. The end game we can predict at this point is dynamic AI learning assembly, which will shift the SME role again as agents will be tasked with validation in many content domains.

Accessibility and Inclusion

One barrier to creating uniformly accessible and inclusive learning is cost—both time and money. We can set aside my personal feelings about maintaining access barriers, even though we know some learners are excluded. AI offers fresh opportunities to upgrade learning experiences at scale.

It's not perfect yet, but it's time to apply captioning, transcription, learning materials testing, accessibility-first tools for content development, language translation drafts (human-validated, of course), screen modification, and more.

We can also ask our favorite LLM to assess for WCAG standards and recommend multiple means strategies (Universal Design for Learning). Basically, there are no longer excuses for offering content that isn't accessible and neuroinclusive.

Media Production

Where I see significant cost savings in design budgets is in learning media. AI course narration is improving daily and can open the door to multilingual course development, which was previously cost-prohibitive. We're seeing more avatar video production in courses—selecting an avatar that is AI-narrated and animated based on the narrative script you submit. Now, with apps like HeyGen, you can upload a subject expert's photo, gestures, and voice samples along with your presentation script, and AI will generate a video. No retakes. No webcam quality issues. No studio setup. Almost no time at all.

Back to how we work with SMEs: Utilizing this technology will require us to specify new levels of permissions and image licensing in contracts with our experts.

Skills-First Learning

All of this should have you thinking—if AI is going to partner with us to co-create courses, what's left for us to do?

Well, AI doesn't understand instructional design yet. LLMs are answer engines that create knowledge hierarchies. Practically, this means the value of knowledge-based learning is plummeting. Very soon, anyone will be able to open a GPT window and produce it with a well-crafted prompt.

Consider how much of your learning portfolio is knowledge-based and how much focuses on skill development. If your learner-members turn to AI for their point-of-need knowledge base instead of purchasing your courses, webinars, and conferences, how much does that wipe out in your portfolio?

Now pair that realization with the fact that the workforce is now skill-first. The differentiator in getting a job and advancing a career is skills. Our record of skills and capabilities is our passport to new and better opportunities.

If you don't believe me, believe David Blake, CEO of Degreed and author of Expertise Economy:

• Skills-based hiring is 3.5 times more predictive of on-the-job success.

• Skills-based hiring is more than twice as effective as hiring based on work experience.

• Skills are the most predictive way of hiring people for the right positions and advancing them within an organization.

• AI tools shift our norms toward a skill bias in the workforce.

  
  

Capability. Proficiency. Competency. Mastery. Performance.

These outcomes—the meat and potatoes of assessment-based certificate programs and stackable digital badging—demonstrate skill capability and mastery aligned with this new priority.

All of this makes it imperative to rethink the knowledge base to skill ratio within our learning portfolio and deliver on skill development. Become the expertise engine for your industry.

Conclusion

This is just a taste of what's unfolding. If you're eager to learn more about our AI Readiness Assessment and AI-Enablement consulting, as well as skill-based learning design, reach out to me. We're here to partner with you!

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