Assessing QMS Software’s AI Capabilities: 13 Key Questions to Ask
As enterprises gear up for an AI-first world, integrating AI into your Quality Management System (QMS) is no longer just a forward-thinking option—it's necessary to stay competitive.
However, choosing the right AI-enabled QMS requires a focused approach to ensure that AI/ML capabilities truly enhance, elevate, and augment your quality processes, from automating routine tasks to empowering smarter decision-making and boosting overall efficiency. This blog will guide you through thirteen essential questions to ask when evaluating AI capabilities of a QMS software.
At ComplianceQuest, we’ve developed the CQ.AI framework, which leverages cutting-edge AI, ML and Data Capabilities to enhance efficiency, decision-making, and productivity across various quality management processes. This blog will guide you through thirteen critical questions to ask when evaluating AI features in QMS software and provide additional considerations for selecting the right solution for your organization.
The Power of CQ.AI
At the heart of ComplianceQuest's approach to AI lies CQ.AI, a framework designed to implement five types of automation that are integral to enhancing quality management:
- Task Automation: Automating short-running, routine tasks for quick benefits. From a quality perspective, this could be as simple as automatically notifying a stakeholder once a CAPA is triggered or an audit is scheduled with an e-mail notification.
- Process Automation: Orchestrating and automating long-running processes to deliver higher business value. Examples include eliminating redundant complaint records by detecting duplicates and automatically merging and closing them.
- Augmentation: Empower knowledge workers with intelligent capabilities and enable self-service for customers. For instance, this could be spotting a non-conformance that is fairly similar to an earlier one that was detected and automatically recommending escalation to CAPA.
- Next Best Actions: Use intelligent analytics to suggest recommendations or next steps. For example, if there is a high volume of complaints in a particular area, the root cause of the issue could be related to a particular supplier. If a tool can suggest a recommendation to check that supplier’s quality rating, there would be several steps in between that would be saved for the quality leader responsible for it.
- Guided Workflows: One simple yet very useful use case of automation and AI is to “connect” processes and move from one step to the next with agility. Through intelligent notifications, if the EQMS system could truly connect people, processes, and systems – that in itself would be a game changer.
AI & Humans: Better Together
While AI brings significant automation and efficiency, it’s important to recognize that it does not replace human intelligence but rather augments it. AI handles repetitive tasks, processes large datasets, and offers predictive insights, allowing quality professionals to focus on more complex, strategic decision-making. The combination of AI and human ingenuity is what drives true operational excellence.
For example, AI-powered tools like ComplianceQuest’s Decision Support Agent provide recommendations based on data, but the final decision and strategy formulation remain in the hands of experienced quality managers. This collaboration between AI and humans ensures that organizations meet and exceed their quality goals.
13 Key Questions to Ask When Evaluating AI Capabilities in QMS Software
Today, quality leaders and IT decision makers are looking for a modern, next-generation EQMS Solution that’ll help them with the following capabilities:
- Streamline and automate end-to-end workflows
- Seamlessly integrate with various business systems including ERP, CRM, PLM, SRM, etc.
- Enable data-driven decision making and ensure high-levels of data visibility
- Bring together people, processes and systems
- Drive collaboration and operational efficiency across teams/departments
- Scalable, flexible and configurable - so the QMS can scale as the business grows
- Come with integrated risk management, document management and training management features
- Enhances collaboration between executive leadership, quality, supplier, manufacturing and customer teams
Additionally, with advancements in AI, ML, NLP and other emerging technologies, it has become a no-brainer to embrace an AI-infused QMS Solution. But, not all AI capabilities are the same.
How do you evaluate how valuable, effective and relevant are the AI features in the QMS Solution? Are the AI models biased? Does it have a strong data foundation? Is it needed? There’s no point having AI for the sake of it.
In this segment of the blog, we highlight 13 key questions that must be answered while choosing an AI-infused EQMS Solution.
- Are AI Features Intuitive?
- Does the AI operate intuitively and require minimal manual intervention?
- Is there flexibility for users to override AI decisions when necessary?
- Do the AI Features Deliver Real Value?
- Does AI enhance critical quality processes?
- Do the AI features help solve real-world challenges?
- Do the AI functionalities save time or improve the quality of decisions?
- Does It Improve Productivity at the End-User Level?
- How much time does the AI save on repetitive tasks?
- Do the AI features enable users to engage in higher-level decision-making?
- How Robust Is the AI’s Data Foundation?
- Are AI models built on a solid data architecture?
- How effectively does the AI use data to provide insights?
- How Is the AI Integrated into the QMS?
- Is the AI built into the platform's core architecture, or does it rely on third-party solutions that may pose integration or security risks?
- Does the QMS use basic automation for routine tasks, or does it apply hyper-automation (e.g., AI, ML, RPA) to automate complex processes like CAPA management?
- How Mature Is the Platform the QMS is Built On?
- Is the AI solution built on a leading cloud platform (e.g., AWS, Azure, Salesforce)?
- How frequently does the platform provider update its AI capabilities?
- How Mature Is the Product with Integrating AI?
- How well does the product align with the latest AI innovations from the platform?
- How experienced is the vendor in effectively applying AI capabilities?
- Can The AI Capabilities Scale with Your Needs?
- Can the AI handle growth and increased workload?
- Is the AI adaptable to evolving business requirements?
- How Accessible Is the Vendor’s Training and Support To Effectively Leverage AI Features?
- What training resources are provided?
- Can users easily integrate AI into their workflows?
- Does AI Support Regulatory Compliance?
- Does the AI help maintain regulatory compliance?
- Can the AI adapt to future regulatory changes?
- How Well Does The AI-Infused QMS Fit into Your Current Process/Workflow?
- Does the AI-powered QMS integrate smoothly with existing systems?
- Does it require significant workflow adjustments?
- What Is the ROI From Investing in An AI-Infused QMS?
- What are the total costs associated with implementing this solution?
- Do you estimate there’ll be sufficient ROI through improved processes?
- How Flexible Is the Tool for Customization And Configuration?
- Can the QMS software be configured to your specific requirements?
- How adaptable is the tool to different scenarios and processes?
Task Automation & Better Decision Support with ComplianceQuest’s 7 AI Agents
At ComplianceQuest, we have launched the following 7 AI Agents to help improve productivity and user experience:
- Complaints Agent
- Audit/Risk Agent
- Safety Agent
- Quality Agent
- Supplier Agent
- Decision Support Agent
- User Experience Agent
The first five AI Agents mentioned above would specifically use “intelligent automation” capabilities to streamline tasks, eliminate mundane human work, and allow people to focus on high-level work that requires human intelligence and context.
The Decision Support Agent will enable semi-autonomous decision-making, presenting ideas and options in front of quality leaders.
The User Experience agent will save time in terms of software/tool usage, making it easy to move from one step to another. It enables a guided workflow, complete with notifications to go to the “next step” in the process.
Conclusion
Choosing the right AI-enabled QMS involves more than just evaluating features—it requires a deep understanding of how AI can transform your quality management processes.
By asking these thirteen key questions and considering additional factors, such as the power of CQ.AI and the collaborative potential of AI and human intelligence, you can select a solution that not only meets your immediate needs but also supports your long-term quality goals.
In today’s competitive and highly regulated industries, adopting an AI-enabled QMS like ComplianceQuest can provide predictive insights, automate routine tasks, and enable proactive quality management, ultimately driving business excellence.