How AI is Reshaping Regulatory Submissions

​Artificial intelligence is rapidly changing the medical device industry. Most conversations focus on AI-enabled products, from imaging software to diagnostic tools. But some of the most immediate opportunities are happening behind the scenes.

During a recent Square-1 Engineering Lunch & Learn, Tricia Cregger, Director of Quality/Regulatory for Coltene explored how AI is transforming the regulatory submission process itself. From literature reviews and predicate searches to document drafting and quality reviews, AI is becoming a powerful tool for helping regulatory teams work more efficiently while maintaining compliance.
The Opportunity Isn't Just AI Products
The FDA has now authorized more than 1,200 AI-enabled medical devices, a dramatic increase from just six approvals in 2015. While those products receive most of the attention, another transformation is taking place inside regulatory departments.
AI is increasingly being used to support the work required to bring devices to market. Rather than replacing regulatory professionals, it is helping teams manage growing volumes of documentation, increasingly complex requirements, and tighter timelines.
From Manual Processes to Intelligent Workflows
Regulatory submissions have always been document intensive.
Whether preparing a 510(k), PMA, Technical Documentation package, or Clinical Evaluation Report, teams often manage hundreds or even thousands of pages across multiple regulatory frameworks.
Historically, the solution to increasing complexity was simple: add more people, more reviews, and more hours.
AI offers a different path.
Modern tools can continuously monitor regulatory agencies for guidance updates, analyze large volumes of literature, identify potential predicate devices, and help organize information long before a submission reaches the drafting stage.
The result is a shift from reactive regulatory intelligence to proactive regulatory planning.
Faster Drafting, Smarter Reviews
One of the most promising applications of AI is document generation.
Tools can now create structured first drafts of executive summaries, risk assessments, clinical evaluation reports, and other submission documents in a fraction of the time traditionally required.
That does not mean the submission is finished.
A key theme throughout the discussion was that AI should be viewed as a drafting assistant, not an author. The technology can help teams move from a blank page to a working draft quickly, but subject matter experts remain responsible for validating every fact, reference, and conclusion.
The goal is not to eliminate human expertise. It is to allow experts to spend less time formatting and more time thinking.
Improving Submission Readiness
Beyond drafting, AI is creating opportunities to strengthen submission quality.
Advanced tools can:

• Identify inconsistencies across documents
• Detect broken cross-references
• Compare content against regulatory requirements
• Highlight potential gaps before submission
• Support version control and review management

These capabilities allow teams to focus their attention on strategic and technical issues rather than spending valuable time searching for formatting errors or conflicting language.
In many cases, AI can act as an additional reviewer that never gets tired, never misses a revision, and never overlooks a contradiction hidden hundreds of pages deep in a submission package.
Predicting Questions Before They Are Asked
Perhaps one of the most intriguing developments is the use of predictive analytics.
By analyzing historical regulatory feedback, AI models can identify patterns that may indicate where reviewers are likely to focus their attention.
Imagine knowing before submission that your product type frequently receives questions about biocompatibility, clinical evidence, or predicate selection. That insight allows teams to strengthen those sections proactively rather than responding after review begins.
While these tools are still evolving, they demonstrate how AI can move beyond efficiency gains and become a strategic advantage.
The Risks Are Real
The discussion also highlighted the importance of caution.
AI systems can generate content that sounds authoritative while being completely incorrect. Fabricated references, nonexistent standards, and inaccurate technical conclusions remain genuine risks.
In regulatory affairs, credibility matters.
A single unsupported claim can create questions about the integrity of an entire submission.
For that reason, human verification remains non-negotiable. Every AI-generated output must be reviewed, challenged, and validated by qualified professionals.
Governance Will Determine Success
Organizations that successfully adopt AI will not do so by simply giving employees access to new tools.
They will establish governance.
That includes:

• Defining approved AI tools
• Creating procedures for AI-assisted work
• Establishing verification requirements
• Training employees on limitations and risks
• Maintaining documentation and audit trails

The companies that move fastest while maintaining quality will be the ones that treat AI as part of their quality system rather than as a standalone technology.
The Future Still Requires People
One concern often raised whenever AI enters a conversation is whether it will replace regulatory professionals.
The answer is no.
AI can generate drafts, scan databases, and identify patterns. It cannot exercise judgment, build relationships with regulators, navigate complex strategic decisions, or defend a submission during critical discussions.
Those responsibilities remain firmly in human hands.
As AI continues to mature, the role of regulatory professionals will evolve. Less time will be spent on repetitive administrative work, and more time will be spent on strategy, critical thinking, and decision-making.
The future of regulatory affairs is not AI versus humans.
It is AI working alongside experienced professionals to create stronger, faster, and more effective submissions.
Final Thoughts
AI is no longer a future consideration for regulatory teams. It is already changing how submissions are prepared, reviewed, and managed.
The organizations that begin learning, piloting, and governing these tools today will be better positioned to adapt as regulatory expectations continue to evolve.
The question is no longer whether AI will impact regulatory submissions.
The question is how prepared your organization will be when it does.

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