Do you struggle to answer the question, “is our program actually working?”
We are excited to announce that GAN Integrity AI Analytics and Dashboards is now available. It's a purpose-built intelligence layer that gives compliance and TPRM teams real-time access to their own program data: through natural language queries, self-service dashboards, and role-based views built for every stakeholder who needs them.
Why This, Why Now
We wrote recently about the infrastructure gap sitting at the center of compliance reporting; the disconnect between the data compliance teams have collected and their ability to turn that data into answers when it matters.
The short version: compliance teams are more data-rich than ever, and still frequently can't answer the most important question they're asked. Not because the data doesn't exist, but because the path from data to answer has always required too many intermediaries: spreadsheet exports, BI tickets, static decks, and a lot of time nobody actually has.
That's the problem AI Analytics and Dashboards was built to solve. Not as a reporting layer bolted on top of existing workflows, but as a fundamental change in how compliance teams interact with their own data.
The timing isn't incidental either. Regulatory expectations around compliance program effectiveness have continued to sharpen. The DOJ's guidance on evaluating compliance programs has reinforced data-driven measurement as a meaningful marker of program maturity. Boards and audit committees are asking harder questions, and expecting answers grounded in evidence, not description. The moment for this capability isn't someday. It's now.
What's New
Ask Questions in Plain Language, Get Answers Immediately
The core of AI Analytics is natural language querying: the ability to type a question as you'd actually ask it and receive a live chart, summary, or trend analysis drawn from your GAN data. No configuration. No analyst in the middle.
That means a compliance leader can ask "Show me high-risk vendors by business unit, sorted by due diligence status" and have a visual answer in seconds. Or pull up issue resolution trends ahead of a board meeting without rebuilding a deck the night before. The system understands the data it's working with (because it's built directly on GAN's structured, governed compliance and TPRM data model) which means outputs are accurate, consistent, and explainable.
Instant Insights
AI Analytics also includes enhanced self-service dashboard creation, which means compliance and TPRM teams can get the information they need without code, BI expertise, or a support ticket. Dashboards can be updated on your schedule, not IT's. They can be designed for the specific audience seeing them, and they can be updated as the audience is in the room.
Role-Based Views for Every Stakeholder
Not everyone who needs compliance data needs the same compliance data. AI Analytics can be tailored by the user to deliver role-calibrated views that give each stakeholder what's relevant to them: executives see risk posture and program health at a glance; auditors get consistent, repeatable evidence and control performance; risk owners see their third-party portfolio, current risk scores, and outstanding actions. Everyone gets what they need.
AI-Guided Field Transparency
One of the more practical features is AI-guided field prompting. When users are building queries or dashboards, the system helps them understand what data fields are available and how to use them. This keeps outputs accurate and consistent, and it means you don't need to be a data expert to trust what you're looking at.
What This Changes in Practice
The best way to understand what AI Analytics actually enables is to think through a few moments that every compliance leader has lived.
The board meeting where someone asks a follow-up question the deck can't answer. With AI Analytics, follow-up questions can be answered in the room, from a live dashboard, on demand, rather than "we'll circle back on that."
The audit that requires days of evidence-gathering prep. Pre-built, always-current dashboards mean the evidence is ready before the request arrives. Audit preparation becomes a check, not a scramble.
The regulatory inquiry that demands specific program performance data. When the data is governed, structured, and accessible, the response is fast and defensible. That speed and consistency is itself a signal of program maturity.
The executive who wants to know if the compliance investment is paying off. Showing a trend line of risk reduction, due diligence coverage, and issue resolution over time is a different conversation than describing program activities in a memo. One proves the program is working. The other asks the reader to take it on faith.
Built on GAN Data, Not Around It
It's worth being specific about one design choice that shapes everything else about AI Analytics: it's built directly on GAN's unified compliance and third-party risk data model, not on a generic data warehouse or a separate analytics layer.
That distinction matters more than it might seem. Generic BI tools require you to map your compliance data into their structures, configure field relationships, and manage version-control across exports. The burden of getting to an accurate answer falls on the user. AI Analytics inverts that, because the system already understands the data, the user can focus on the question rather than the infrastructure.
The result is compliance intelligence that's actually self-service. Not self-service in the sense of "you can theoretically do this yourself if you know how." Self-service in the sense of: you can do this, right now, without calling anyone.
Change the Compliance Conversation
Compliance has always involved a tension between the rigor of the work and the visibility of that work to the people who need to understand it. Programs get built, processes get followed, risks get identified and managed, and yet the question "is the program working?" can feel harder to answer than it should.
Part of what we're trying to do with AI Analytics and Dashboards is close that gap, not just operationally, but in terms of how compliance leaders experience their own programs. When you can walk into any stakeholder conversation with current, accurate, visual data on program performance, something shifts. The nature of the conversation changes. The relationship between compliance and the business changes.
We think that shift is long overdue. And we're glad to have built something that helps make it real.
GAN Integrity AI Analytics and Dashboards is available. Check out our interactive demo or reach out to us with any questions.
Colin Campbell is Gan Integrity's VP of Marketing with over 15 years of experience in the SaaS software and tech industry. Colin has led analyst relations and product marketing growth strategies in North America, EMEA, UK and APAC, growing revenues in multiple industries. At GAN Integrity, Colin drives market expansion, demand generation and significantly enhancing customer retention, with a talent for aligning marketing strategies with business goals to deliver results.