A recent podcast conversation with Jay Gilbert, Director of Scientific Programs and Product Development at the Institute of Food Technologists (IFT), got me thinking about something that doesn't get discussed enough: associations may be better positioned to build AI products for their industries than the startups currently racing to do so.
IFT recently launched CoDeveloper, an AI-enabled platform that helps food scientists accelerate product development by drawing on 85 years of the organization's research and publications. The tool uses retrieval augmented generation to surface trusted, science-backed information during the R&D process. It's a sophisticated product, and it came from an association, not a Silicon Valley startup.
That might surprise some people. But when you look at what associations actually have at their disposal, the surprise starts to fade.
What "Right to Win" Actually Means
"Right to win" is a strategy concept that asks a simple question: what makes your organization the natural leader in a particular space? It's the combination of assets, relationships, capabilities, and positioning that gives you an edge others can't easily replicate.
For associations considering AI initiatives, this question deserves serious attention. The answer might be more encouraging than you expect.
Trust Is Hard to Build and Easy to Lose
One of the clearest advantages associations hold is trust. Your members know you exist to serve the profession or industry, not to maximize shareholder returns. That positioning matters more than ever when AI enters the picture.
Think about what you're asking someone to do when they use an AI tool: share their questions, upload their data, reveal what they're working on. In industries where proprietary information, trade secrets, or sensitive data are involved, that's a significant ask.
IFT's members work on product formulations that companies guard fiercely. Jay shared that food scientists used to be told to go home to Google things rather than risk having a search query tied to a company IP address. That level of secrecy meant IFT had to build CoDeveloper with privacy and security as foundational elements, not afterthoughts. No training on user questions. No harvesting of formulas. The association's mission-driven positioning made those commitments credible in a way that a profit-driven startup might struggle to match.
Your association likely serves members with their own sensitivities around data and intellectual property. The trust you've built over years of serving them is a genuine competitive asset.
You Already Own What AI Needs Most
Large language models are only as useful as the information they can access. Generic AI tools pull from the broad internet, which means they deliver generic answers. The real value comes from domain-specific, high-quality content that's been vetted by experts.
Associations tend to have a lot of this. Journals, conference proceedings, research publications, technical standards, best practice guides, archived webinars, magazine articles. This content represents the accumulated knowledge of an entire profession. It's exactly what AI needs to move from "sounds plausible" to "actually useful."
IFT's 85 years of publications gave CoDeveloper a foundation that would take a startup years and significant capital to approximate. And even then, they'd be licensing or scraping content rather than owning it outright.
What does your association have in its archives? That content might feel like a static asset, something members access occasionally through a search function on your website. With AI, it becomes something more dynamic: the basis for tools that can surface relevant information in context, answer specific questions, and help members solve problems in real time.
Your Community Is Your Product Team
Startups building AI tools for a specific industry face a challenge: they need to understand what practitioners actually need, how they work, and what problems keep them up at night. That usually means hiring consultants, conducting user research, and hoping they're talking to the right people.
Associations have this feedback built into their operating model. Members submit proposals for conference sessions, revealing what topics matter to them. They join committees and volunteer groups. They attend events and tell you what they liked and what fell flat. They respond to surveys and renew (or don't renew) their memberships.
This ongoing dialogue means you can build products informed by real needs rather than assumptions. IFT used a jobs-to-be-done framework to understand why members come to the organization and what problems they're trying to solve. That research started back in 2020, well before generative AI became mainstream. When the technology caught up, IFT had a clear picture of what to build and why.
The phrase "built by food scientists for food scientists" works for IFT because it's actually true. Members were involved in shaping the product. That kind of co-creation is harder for outside companies to replicate.
The Ecosystem You've Already Built
Associations don't just have content and community. They have ecosystems: events, publications, educational programs, supplier relationships, partnerships with allied organizations. These create opportunities for AI products that standalone tools can't match.
Consider how IFT is thinking about CoDeveloper's roadmap. The most common question during demos is whether users can find ingredient suppliers through the platform. That's a natural extension because IFT already hosts a major ingredient expo where suppliers showcase their products. Connecting those relationships to an AI tool creates value that makes sense within the IFT ecosystem but would feel random coming from a startup.
What does your association's ecosystem include? Certification programs that could be enhanced with AI study tools? Events where AI-powered matchmaking could improve the attendee experience? Publications that could become the foundation for a domain-specific assistant? The pieces you already have might combine in ways you haven't fully explored.
Mission Makes Hard Decisions Clearer
Building an AI product requires a lot of decisions. What features to prioritize. How to price it. What data to collect and what to leave alone. How to handle edge cases and potential misuse.
For associations, mission provides a guide. When IFT's board evaluated CoDeveloper, they could point directly to the organization's mission: "to advance the science of food and its application." An AI platform that helps food scientists accelerate R&D by accessing trusted research is a direct expression of that mission.
This alignment also helps with internal buy-in. Staff can understand why the organization is investing in technology when the connection to mission is clear. Board members can evaluate progress against criteria that matter to the organization rather than getting lost in technical details.
If your association has been hesitant to pursue AI initiatives, revisiting your mission statement might be a useful exercise. The language you already have might support a stronger case than you realize.
The Responsibility Side of the Equation
Having the right to win carries a flip side: if your association doesn't build these tools, someone else will. And that someone may not share your commitment to the profession, your standards for accuracy, or your concern for members' privacy and professional development.
Plenty of companies are building AI products aimed at the industries and professions associations serve. Some of those products will be good. Many will be mediocre. A few may be actively problematic, training on content without permission or prioritizing engagement over accuracy.
Associations have a chance to offer an alternative grounded in expertise, trust, and genuine service to the profession. That's a meaningful opportunity. It's also a responsibility worth taking seriously.
Starting the Conversation
None of this means every association should rush to build an AI product. The right path depends on your specific situation: your content assets, your members' needs, your organizational capacity, your board's appetite for innovation.
But the conversation about "right to win" is worth having. Where does your association have advantages that would be hard for others to replicate? What problems do your members face that AI could help address? What would it take to move from idea to pilot to product?
IFT's experience shows that associations can move from concept to launch in a reasonable timeframe. Their board treated the initiative like a startup investment, providing seed funding and evaluating progress along the way. Staff stayed closely involved in development, joining daily standups and providing the domain expertise that made the product genuinely useful.
Your path will look different. But the underlying question is the same: does your association have the right to win in this space? If the answer is yes, the next question is what you're going to do about it.
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