AI is Coming to Compliance—Here’s How It Will Help Your Team
A primer on the shift from reactive audits to AI-powered compliance, and what it means for your team.
Every year, Quality and Regulatory professionals engage in a familiar ritual: pull top performers off critical projects, dust off massive spreadsheets for clause-by-clause compliance checks, and hope nothing critical slips through the cracks before the next inspection.
This reactive, time-consuming, and tedious approach has been the status quo for decades. But what if there were a better way? What if technology could turn this resource-heavy, periodic exercise into something more efficient, thorough, and strategic? That’s the promise of a new generation of AI-powered tools—transforming compliance from a backward-looking, manual burden into a proactive, intelligent function.
Unlike typical conference presentations that dwell in hypotheticals and hyperbole, we want to talk about tools that address real, daily compliance challenges. In this feature, we explore how companies like Ryden Solutions and The FDA Group are applying artificial intelligence to unlock huge efficiencies in your compliance workflow.
We’ll quickly cover what’s possible today, what’s on the horizon, and how AI will change your team’s approach to compliance work. The goal here isn't to replace human expertise—it's to augment it. To let AI handle the heavy lifting of documentation analysis so your Quality experts can focus on what really matters: ensuring product safety, advancing innovation, and getting life-changing therapies to the patients who need them.
The compliance burden we’ve (sadly) normalized
For decades now, Quality and Regulatory compliance has followed a predictable rhythm: set up a QMS, run annual internal audits, prep for inspections, then respond to findings. In practice, each of these steps is a costly, resource-draining endeavor that most teams have simply accepted as a necessary evil—the way it’s always been done.
As one Quality leader we recently spoke to put it, “Once a year or more, we have to pull people away from their work to check our systems manually. It’s frustrating, it’s costly, and we’ve all just gotten used to it being a fact of life.”
This “legacy” approach creates challenges that we’ve normalized in the absence of viable alternatives:
It diverts valuable resources and attention. Teams of 10+ employees get pulled from critical work, sometimes for an entire week, to conduct internal audits.
It creates blind spots between reviews. The months between audits quietly create compliance gaps as regulations evolve. These gaps linger until the next audit, forcing companies into an uncomfortable state of vulnerability.
It requires teams to track compliance across frameworks and standards manually. Most teams manage a sprawling series of spreadsheets to track clause-by-clause compliance against multiple regulations.
It incurs high training costs. Companies have to continuously train internal auditors on new frameworks and standards, even when auditing isn't their primary role. This training is expensive, time-consuming, and often ineffective in the long run, as auditors quickly forget specialized knowledge they don't use regularly.
It invites inconsistency across sites. For organizations with multiple facilities, manually tracking uniform compliance across sites can be exceedingly difficult and time-consuming—a task that only gets harder and more taxing as companies expand.
It makes supplier qualification inefficient at best. Similar resource-intensive processes have to be duplicated across supplier networks. Applying a woefully inefficient qualification process across multiple suppliers can be exasperatingly tedious and frustrating.
The true cost isn’t just the lost week—it’s the innovation that never happens, the products delayed, and the persistent anxiety of “what are we missing?”
Beyond the hype: practical AI applications emerging now
We’ve all heard the buzz around AI in life sciences, but most discussions remain philosophical or narrowly focused. Adam Foresman, Ryden’s co-founder and CEO, observes, “All these conferences either talk abstractly about AI or showcase one-trick tools that do just one niche task.”
Companies like Ryden Solutions (for medical device compliance) and The FDA Group (for pharmaceutical and biotech) are breaking that mold. Together, we’re building AI tools that address real, daily pain points.
Here’s a glimpse at what both of our teams are working toward right now:
Document analysis that goes beyond keywords. Our systems don’t just scan for keywords—they analyze SOPs, work instructions, and other documents against FDA and EU regs, ISO standards, and ICH guidelines. Built with decades of domain expertise, these tools understand the complex relationships between documentation and regulation. Both systems are trained by industry experts with decades of regulatory compliance experience to understand the complex relationships between regulations and documentation.
Automated gap analysis. When gaps are found, the system generates detailed reports pinpointing issues and offering remediation guidance. This shifts Quality teams from manual drudgery to strategic prioritization—humans save time doing manual reporting so they can get to prioritizing their efforts and focusing on actually addressing the areas that need the most attention. It's not just about identifying where you're out of compliance—our tools also surface best practices and provide specific recommendations for remediation.
Managing knowledge across different regulatory frameworks. These tools integrate regulatory knowledge bases, offering immense value for global companies juggling multiple jurisdictions and evolving standards. This is particularly valuable for global organizations that have to comply with regulations in multiple markets, each with its own requirements and update cadence—a currently massive undertaking for companies.
Under the hood: how these AI compliance tools actually work
If you’re interested in the technical underpinnings of the tools we’re building alongside Ryden Solutions, let’s take a brief tangent to see what’s actually happening behind the user interface.
Expert-guided AI training
Unlike consumer AI systems that are trained on public data (think ChatGPT or Gemini), what we’re building is specifically developed with regulatory expertise baked in. The Ryden team has been training its AI for almost a year with nine FDA experts who understand both the FDA and EU frameworks. This human-guided approach makes sure the AI understands nuances that general-purpose language models would miss.
Rather than simply performing keyword searches, these systems are trained to comprehend the relationships between regulatory requirements and documentation. The AI “learns” to recognize patterns in compliant documentation and identify potential gaps based on its understanding of regulations—not just matching terms.
Document processing architecture
When a document is submitted for analysis, the AI processes it in multiple stages:
Document classification: The system identifies what type of document it's examining (SOP, work instruction, policy, etc.).
Regulatory mapping: It determines which regulatory requirements apply to that document type.
Gap identification: The AI analyzes the content against those requirements.
Best practice assessment: Beyond compliance requirements, it evaluates against industry best practices.
A multi-stage analysis produces more nuanced, context-aware results than simple compliance checklists.
Output and reporting
The analysis generates comprehensive reports—typically 25-50 pages for a full assessment—that detail:
A traceability matrix showing how documents map to regulatory requirements
Identified gaps with detailed explanations
Recommendations for remediation
Lists of documents reviewed
These reports can be used directly or serve as appendices to formal audit reports, providing a complete record of the assessment.
Of course, data security is a primary concern for life sciences companies evaluating these tools. Both companies have addressed this through several approaches, including options to delete documents immediately after processing, tiered permission systems that restrict who can view or download sensitive information, and comprehensive logging of all system activities for compliance purposes.
How these tools will transform your workflow
Several use cases demonstrate how these AI tools may reshape your team’s compliance activities day-to-day to automate or at least augment some of the most taxing and tedious activities.
Let’s break them down:
Internal audit support: Rather than dedicating a team to conduct internal audits, these tools employ highly trained AI to help analyze documentation before the audit begins. This allows human auditors to focus their time on the parts of an audit that lend themselves best to a human running them: interviewing personnel and reviewing specific records where potential gaps have been identified. Auditors should spend most of their time on people and processes—not paperwork.
Accelerating market expansions and regulatory updates: Instead of weeks of manual research, AI can assess your current documentation against the regulations of new markets within hours. One Quality Director we talked to recalled needing weeks to answer a CEO's question about market entry timelines—AI can now deliver that in a fraction of the time. This same capability applies to updated regulation assessments for markets you already sell into. Rather than waiting for the annual audit cycle, these tools can quickly evaluate your documentation against regulatory changes as they occur, helping you stay compliant in all your existing markets throughout the year.
Enabling enterprise-wide compliance visibility: For companies with multiple facilities, these tools provide a unified view of compliance. Leaders can respond strategically to issues, whether isolated or systemic—something that was nearly impossible until now.
Assisted supplier management: AI-driven assessments can be tailored to your supplier checklists, streamlining qualification and reducing reliance on third-party audits. This saves time from doing a supplier audit yourself and saves cost from requiring the supplier to complete third-party consultant audits.
A few practical considerations to think about now
For organizations interested in these technologies, a few preparatory steps can help ensure successful implementation. First, set realistic expectations. Despite what you hear at conferences, these tools are powerful, but not magical. They augment human expertise, not replace it.
Second, start thinking about how you manage documents right now and how well you’ll be able to invite AI into that environment. Whether you use an eQMS or not, ensure your file naming and structure are consistent. As Foresman notes, “We recommend your documents have a specific file name structure—including document number and revision—so it’s clear what’s been assessed.”
Third, think about secure access in your IT environment. AI tools need access to your documentation. Your IT team will need to determine whether cloud or on-prem solutions best fit your security needs.
Lastly, plan to focus the initial implementation on your most relevant standards and markets. This allows for a smoother rollout and faster wins.
The road ahead—a measured vision of AI in the near future
Looking beyond current capabilities, we can expect significant evolution: In the next 1-2 years, we might see more sophisticated integration with existing eQMS systems, even more powerful ways to track regulatory changes, and extremely impressive reporting tools that surface a ton of actionable information about your documentation.
Looking 3-5 years ahead, the potential becomes even more interesting:
AI systems that could provide preliminary validation during QMS development.
Enhanced predictive capabilities that identify potential compliance issues before they arise.
More comprehensive audit support capabilities beyond documentation review.
The central shift? Moving from reactive to proactive compliance. AI takes on the heavy lifting, freeing humans to do high-value, strategic work before regulators ever knock on the door. These tools will step in to manage many parts of compliance so the human experts are freed to focus on more meaningful (and frankly more exciting) work.
A few final thoughts
For too long, life sciences companies have engaged in something akin to compliance theatre—the regular ritual of frantic preparation, exhaustive audits, and temporary fixes that create the appearance of compliance without truly embedding it in daily operations.
AI, when deployed thoughtfully, offers a better path: one that’s efficient, actually data-driven, and empowering. It enables your best people to focus on what they do best—innovation and impact, not documentation.
Companies that adopt these tools with realistic expectations and thoughtful execution will enjoy faster time to market, lower compliance costs, and reduced regulatory risk. The future of compliance isn’t about working harder—it’s about working smarter. We hope you’ll join us in that new paradigm.
This feature was informed by conversations with experts at Ryden Solutions and The FDA Group, leaders in developing AI-driven regulatory solutions. It reflects a current snapshot of an evolving technology. Stay tuned for updates in this space, and explore more at thefdagroup.com and ryden.ai.
Who is The FDA Group?
The FDA Group helps life science organizations rapidly access the industry's best consultants, contractors, and candidates. Our resources assist in every stage of the product lifecycle, from clinical development to commercialization, with a focus on Quality Assurance, Regulatory Affairs, and Clinical Operations.
With thousands of resources worldwide, hundreds of whom are former FDA, we meet your precise resourcing needs through a fast, convenient talent selection process supported by a Total Quality Guarantee. Learn more and schedule a call with us to see if we’re a fit to help you access specialized professionals and execute your projects on time and on budget.