AI has officially made its way into nearly every conversation in life sciences, and quality is no exception.
But while the potential of AI is exciting, Quality teams (thankfully) remain focused on a risk based approach to adopting new technologies that may compromise IP or cause regulatory problems downstream.
In a recent survey we conducted with 100 quality leaders, only 10% said they’re currently using AI in their workflows, while roughly 50% said they’re open to it if it’s the right tooling, with the right controls, in the right context.
And this makes sense! The questions Quality teams have about AI are valid. What happens to your data? How do you validate AI-powered software? Are you creating more risk than you’re preventing?
It’s these concerns – and the drive to mollify them – that has defined our approach to AI at ZenQMS: compliant AI that is simple, safe, optional, and validated.
In short, as stewards of your data and GxP quality records, we’re focused on integrating AI into our platform in a way that balances innovation and control, efficiency and compliance. Keep reading to see exactly what this means for your workflows.
Why AI in Quality Management Actually Matters
In an industry where speed is critical, R&D is still too slow.
- There are ~7,000 known rare diseases. Only about 5% have an available treatment today.
- Getting a single medicine to market can take up to 10 years and cost around $2.6B.
- Only about 12% of molecules that enter clinical trials make it to FDA approval.
A lot of the bottleneck isn’t just science. It’s process.
Clinical phases can stretch for years and consume as much as 70% of R&D budgets. And compliance gaps are part of the delay. In fact, many FDA findings still center on things like:
- Deficiencies in manufacturing processes
- Failed facility inspections
- Incomplete or poorly controlled documentation
- Gaps in training and process execution
That’s where AI-supported quality management can help by identifying and eliminating friction. For example:
- Catch issues before inspection
- Highlight training and process gaps sooner
- Guide operators in real time
- Reduce the work of maintaining a healthy QMS by automating repetitive tasks, automating investigations/responses, checking for gaps and excursions from KPIs, etc.
But in a regulated environment, compliance trumps all. That’s why ZenQMS is taking a controlled approach to AI.
What We Mean by “Compliant AI” in ZenQMS
As we continue to develop compliant AI-powered features within ZenQMS, we’re sticking to some non-negotiable principles:
1. Optional and under your control
AI in ZenQMS is opt-in, not switched on by default.
- You choose if and when to enable AI functionality.
- You decide where it makes sense in your quality system and governance.
- You can incorporate AI features into your existing validation approach with support from ZenQMS validation materials, just like our other configurable features.
2. Your data is not used to train third-party models
Quality professionals aren’t replaceable and never will be. Every AI interaction is designed to be used in tandem with human oversight. AI suggests; humans review, accept, or edit.
- No customer data is used to train underlying third-party LLMs (Large Language Models or AI programs trained to understand and generate human language).
- Your data is kept in a controlled, isolated environment.
3. Human in the loop, always
Quality professionals aren’t replaceable and never will be. Every AI interaction is designed to be used in tandem with human oversight. AI suggests; humans review, accept, or edit.
4. Audit-ready traceability
Every AI transaction is:
- Time-stamped
- Logged in your audit trail to delineate AI Agent actions versus human edits
- Available for review
If an auditor asks, “How did this question get here? What was contributed by AI versus edited by humans?” you have clear answers.
5. Validatable and explainable
We’re aligning AI features with the same lean, risk-based validation approach you already use for ZenQMS:
- Clear requirements and intended use
- Documented test cases and results
- Guardrails to prevent hallucinations and bias
- User interfaces that show how AI reached a result (e.g., visible filters instead of opaque code)
ZenQMS AI Features: Now and Next
We’re starting where impact is high and risk is minimal: automating the tediousness of quality upkeep.
Available Now | AI Smart Search: Natural-Language Filtering for Quality Data
When you need a specific document for compliance, you need it now. But in growing organizations with multiple product lines, sites, and versions, the time spent searching can add up. In fact, according to a recent survey of Quality professionals we conducted, it takes teams relying on manual quality management anywhere from 5 to 34 minutes to locate a document.
Here’s how the ZenQMS AI Smart Search makes a difference:
- Type exactly what you’re looking for in plain language (Example: “I need documents written by Jane effective after January 1, 2025.”).
- AI suggests the right combination of filters across columns.
- Apply the filters to immediately see matching documents.
A few important nuances:
- Suggested filters are visible so you know exactly why certain documents are appearing or not.
- You can refine, remove, or add criteria like you normally would.
From a compliance lens, this matters. You’re using AI to get to the right filtered view faster, then applying your own expert, human judgment.
Coming Soon | AI-Suggested Training Test Questions from SOPs
Soon, we’ll be launching AI-assisted training question generation for your SOPs and other documents. With this feature:
- AI reads the document and proposes questions aligned to the content.
- You’re able to accept, edit or remove AI-generated questions.
- You’re able to add questions manually like you do today.
Behind the scenes, ZenQMS logs:
- That AI was used
- Which suggestions were ultimately accepted or modified
- The document context the suggestions came from
That’s real time saved and better content training coverage, all while retaining full control and traceability.
Looking Ahead | The ZenQMS AI Roadmap
We’re building our AI roadmap around three core pillars:
- Automating the tedious manual work tied to quality upkeep
- Guided operator workflows and better data capture
- Continuous control and compliance intelligence
Future AI capabilities in ZenQMS are aimed at helping organizations better create, understand, and evolve their documentation, gain clearer insight into changes and expectations, and surface potential risks earlier – all while keeping human control at the center.
If you’re interested in learning more about our approach to compliant AI, the current AI-powered features available for users, and the AI capabilities on the horizon, just reach out!