AI is beginning to appear across the iMIS ecosystem.
Some capabilities are built directly into ASI products. Others are available through strategic partners that connect AI to iMIS data or to content stored across an association’s technology platforms.
So far, ASI appears to be taking a deliberate, incremental approach. Instead of adding an AI assistant with broad access to everything an association does, it is introducing AI in defined areas where the task and the boundaries are relatively clear.
That includes helping staff navigate iMIS, analyzing member data, making association content easier to find, creating learning assessments and processing program submissions.
So where are we now?
Here is what associations can do with AI across the iMIS ecosystem today, along with some important distinctions about what is native to iMIS, what requires another ASI product and what is available through a partner.
1. iMIS Assistant helps staff find answers about iMIS
Let’s start with the one AI capability currently built into core iMIS. iMIS Assistant can:
- Answer staff questions about using the iMIS Staff site
- Direct users to relevant help documentation
- Accept screenshots and images to provide context for questions
This is an embedded product-support assistant for iMIS users, not an chatbot that can provide member support.
The iMIS Assistant maintains firm boundaries. It is connected to the iMIS help site, not the association’s member data. It cannot analyze member records, build queries, identify trends or perform work inside iMIS. ASI also advises staff to verify critical information it provides.
2. DataScout brings AI to member data
DataScout for iMIS is an AI platform developed specifically for iMIS that helps associations turn member data into smart segments and automated outreach. It is currently the closest thing in the ecosystem to an AI assistant that can help associations understand member behavior and act on it.
Through a conversational interface, staff can use DataScout to:
- Explore member and engagement data
- Categorize and filter records without complex queries
- Identify potential next actions
- Create member segments
- Draft personalized engagement emails
- Generate visual engagement timelines
DataScout’s current platform also emphasizes identifying moments that warrant outreach, such as renewals, training completions, job changes or declining activity.
DataScout is a product from Bursting Silver, an iMIS partner, rather than a feature included in core iMIS.
3. FUSE Next helps members and staff find content
Associations often have valuable content scattered across websites, learning systems, submission platforms, journals, communities, job boards, PDFs and videos. Traditional site search may not find or interpret that content particularly well.
FUSE Next is designed to provide a unified AI-powered discovery layer across systems including iMIS, TopClass and OpenWater. Its capabilities include:
- Searching content across multiple platforms
- Indexing PDFs, videos and images
- Providing intelligent summaries
- Boosting the most relevant results
- Answering questions through a chatbot that uses the association’s private content
FUSE Next does not manage member records or association operations. It helps associations make their institutional knowledge more accessible.
Like DataScout, FUSE Next is a separate partner solution.
4. TopClass AI accelerates learning-content development
TopClass is ASI’s learning management system for associations and continuing education providers. Its new AI capabilities help reduce the work involved in creating courses and assessments. It reduces the need for manual transcription and question creation, and improves accessibility – without turning course design over to AI. Its current capabilities include:
- Transcribing videos and webinars
- Creating closed captions
- Generating tests and quizzes from videos, course materials or supplied text
- Letting administrators specify question types, difficulty and volume
- Providing a review interface before questions are used
Human review is still needed. AI can produce a draft, but learning staff and subject-matter experts still need to verify accuracy, difficulty, and alignment with the course objectives.
The AI capabilities are available as an opt-in beta. More AI features are planned, including translation, AI-assisted SEO and deeper learning insights.
5. OpenWater AI helps administrators process submissions
OpenWater is ASI’s application and review management platform for awards, grants, scholarships, abstracts and other submission programs. Its AI capabilities help administrators analyze and process large volumes of submissions.
OpenWater offers the most configurable application of AI in the current ASI product portfolio. Program administrators can write prompts that instruct AI to work with awards, grants, scholarships, abstracts and other submissions:
- Summarize submissions
- Highlight strengths
- Flag omissions or potential concerns
- Validate information against defined criteria
- Suggest scores and commentary
- Transform submission content into structured data
The results remain inside OpenWater, and can appear in judge views, reports, exports, galleries and emails.
Administrators decide what AI evaluates, how the output is used and where it appears. Judges see the relevant results but do not interact directly with the AI.
OpenWater AI is also an opt-in beta. Because its output could influence consequential decisions, associations will need clear review processes and carefully tested prompts.
The ecosystem is developing in layers
ASI is not introducing one AI system with access to everything. Instead, it is building or supporting a collection of specialized tools, each working with a particular type of information and workflow.
That can make AI adoption more manageable. It also means associations must understand which capabilities are included in their existing systems, which are in beta and which require separate partner products.
What are the governance issues?
Before adopting one of these tools, associations should ask:
- Which specific task are we trying to improve?
- What data or content will the AI be allowed to use?
- Who will verify the output?
- What decisions should always remain with staff or volunteer leaders?
- How will we test for inaccurate, inconsistent or biased results?
- Is the capability included, in beta or licensed separately?
- What will it cost once complimentary token allocations are exhausted?
The level of oversight should match the stakes. An inaccurate quiz question is a problem. An AI recommendation that influences a scholarship or grant decision may be a much more serious one.
We’re at the beginning
AI in the iMIS ecosystem is still developing, but it has moved beyond the purely theoretical. Associations can now use AI to find answers, understand member activity, uncover content, create assessments and process submissions.
This is a practical place to begin. The opportunity now is to identify where these capabilities genuinely save time or improve the member experience, while establishing the safeguards needed to use them responsibly.