Should AI Capabilities Be Part of Your AMS Requirements?

The short answer is yes.

It's hard to know what you should reasonably expect from any software solution and the opportunity to find tools on the cutting edge of AI technologies has made that much harder. Boards want to know if they're about to buy something that's already behind. Staff want to know if "AI-ready" is real or just the newest word on the RFP checklist. And vendors are happy to tell you whatever gets them to the next round.

So, what should you be asking your vendors so you can answer the questions of the board, your staff, and even other vendors. Here's how I break it down in three tiers: what you should expect from your AMS today, what belongs on the vendors’ roadmaps, and what belongs on your own long-range, blue-sky list.

What to Require Today

Right now, the requirement isn't "does the AMS have AI built in." The requirement is "can the platform connect and share data with the AI tools your staff are already reaching for."

That distinction matters more than it sounds like it does. Association staff are already using AI for member communications, for data analysis, and for drafting board materials, whether or not the AMS (or your organization) sanctions it. Example: someone on your membership team is exporting a renewal list to a spreadsheet, dropping it into ChatGPT to spot patterns, and nobody on your leadership team knows that's happening. That's not a hypothetical. That has happened at most associations based on our conversations.

Two capabilities should be non-negotiable in your requirements today:

• Ability to connect the platform to AI tools for data analysis, without committing to a proprietary tool. You want an open door, not a walled garden. If the only way to get AI-assisted analysis out of your data is the vendor's single, bundled tool, you've traded flexibility for a feature, and you'll be renegotiating that trade in eighteen months when a better tool comes along.
• Ability to connect the platform to a service agent that helps respond to customer service queries. Your members are asking simple questions at 11 p.m.: how do I reset my password, when does my membership renew, where's my CE certificate. That's not a staffing problem to solve with headcount. That's a connection your AMS should support without a six-month development project.

Ask yourself: if a staff member wanted to plug an AI analysis tool into our member data next month, could they do it through the platform? Does your vendor offer support or services to make that connection?

Tips & Tricks: Add both of these as scored requirements in your AMS RFP, not as "nice to haves" in the notes section. Ask the vendor to demonstrate the connection live, not describe it in a slide. If they can't show it, it doesn't exist yet.

The Roadmap: What Should Be Scheduled, Not Just Promised

This is where I see the most vendor storytelling: the vague "we're investing heavily in AI" answer with no dates attached. That's not a roadmap. That's a hope. A real roadmap has named capabilities and a rollout window, the same way you'd expect for any other major platform investment. That roadmap should also include dependencies on things like custom development, feature dependences, versions/plans, etc.

Two capabilities you should expect to see with a real timeline attached:

• An AMS that ships with a customer service agent, or has a third-party tool embedded, not bolted on. There's a real difference between "we integrate with a chatbot vendor" and "there's a functioning agent inside the platform your team can configure." Ask which one you're getting and ask to see it configured against your own data, not a demo environment.
• AI capabilities that expose findings based on natural language queries, with natural language results. This is the "ask a question, get an answer" capability: not a search with results you have to wade through for answers, but something that lets a non-technical staff member type a real question and get a real answer back in plain language.

There's a simple filter here: if the vendor's roadmap answer takes more than two sentences to explain what the capability actually does, it's probably not real yet.

Tips & Tricks: When you ask a vendor for their AI roadmap, ask for three things in writing: the specific capability, the target release quarter, and will my implementation support this funcationality.  

The Blue Sky: What You Should Be Watching, Not Yet Buying

This is the long-range list: the capabilities that aren't ready for a requirements document today but that should shape how you think about your data strategy now. None of this works without clean, well-governed data underneath it. Spend your time focusing on understanding and preparing your data. You don't get blue-sky AI on top of a shaky foundation. You get expensive disappointment.

Three capabilities worth watching:

• Ability to determine pricing based on a combination of past data points and other financial inputs, like expenses. Dynamic, data-informed pricing for membership, education, or exhibits, grounded in your actual cost structure, not a static number someone picked five years ago and never revisited.
• Ability to inquire about the value of a membership or the retention risk on a record-by-record basis, without curating extensive data first. Example: you're on a member's record and you ask, "what are the main risk factors in this person renewing?" and you get a real answer, not a dashboard, a report request, or a data science project.
• Ability to extend that same question to full data sets. Example: "what are the most common months student members drop their membership?" That's the same capability as the record-level question, just aimed at the whole population instead of one person.

None of these are AI AMS requirements yet. But they should be the reason your data governance work is happening now, not later. Your system performs based on what you put into it. An AI tool asked to explain retention risk against incomplete or inconsistent member data will give you a confident, wrong answer, and a confident, wrong answer is worse than no answer at all.

Ask yourself: if we had record-level, natural-language retention insight tomorrow, would our membership data actually support a trustworthy answer?

Bring It All Together

Should AI capabilities be part of your AMS requirements? Yes, but be precise about which capabilities belong where. Today, require open connection to the AI and service tools your team is already using. On the roadmap, hold vendors to named capabilities and real dates, not investment language. On the long-range list, let the blue-sky capabilities inform your data strategy now, even though you're not buying them yet.

The biggest win here isn't landing on the most AI-forward platform in the room. It's writing requirements precise enough that you can actually tell the difference between a platform that's ready and one that's just talking about being ready.