How Automation & AI Can Ease the Compliance Burden
Artificial intelligence tools can monitor the latest regulatory changes, updated laws, and revised requirements, keeping engineers up to date on the latest rules and giving companies a competitive edge.
At a Glance
- AI can keep design & engineering teams apprised of any changes in regulatory requirements.
- AI can even make suggestions about design changes that could reduce costs while maintaining compliance.
- AI could help engineers make changes early in the design cycle before it becomes an expensive, complex problem to fix.
Tracking regulatory compliance is not an easy task. In fact, it is becoming increasingly complex to understand what is required for each industry and geography in which a product is sold. Failure to accurately comply with regulations increases the risk of overdesign or results in failure to get a product approved. By incorporating artificial intelligence (AI) into the regulatory process, organizations can significantly streamline and enhance their compliance efforts. However, it’s not as simple as pointing AI in the right direction and letting it manage your compliance.
The challenges of regulatory compliance
Compliance involves navigating a vast array of requirements that vary by industry, region, and even for specific products. Every industry has its own rules. On top of those are requirements imposed by governments and regulators across the globe. It is rare that these requirements are totally aligned. As a result, designing a product to meet one set of requirements has little to do with whether it will be approved elsewhere.
Traditional approaches to compliance in the product design space often rely on manual processes and static checklists. This is not only time-consuming but also very error prone. As regulations evolve and businesses expand to new regions and industries, these manual methods will not suffice. Companies will be left vulnerable to compliance gaps, leading to potentially serious consequences.
AI to the rescue
AI offers a transformative solution to the challenges of regulatory compliance. By automating the extraction of regulatory requirements from technical documents, AI can streamline the flow of critical information directly into the tools used to manage product and design data, including product lifecycle management (PLM). This seamless integration allows for the effortless incorporation of compliance data into the development process. This ensures that all necessary requirements are identified without overburdening the design team.
AI tools can monitor the latest regulatory changes, updated laws, and revised requirements. This provides a dynamic and continuously updated compliance framework. This is critically important as regulations continue to change—especially on a global scale. As companies expand into other product lines and geographies, it can become a separate full-time job for a team to remain up to date. AI can be trained to help solve this problem, updating in real-time and making compliance efforts more efficient and less error prone.
Compliance as a business process
While integrating AI can help solve many of the compliance consistency issues organizations experience, it should also go hand-in-hand with re-thinking how you approach compliance in the first place. Compliance needs to become an ongoing business process integrated throughout the product design and engineering lifecycle.
In the past, compliance was treated like a checklist. It was reviewed at the end of a product design cycle. Those doing the checking kept their fingers crossed that everything was done correctly. But now, with the growing complexity involved with approving each product, organizations should approach compliance from a systems perspective vs rushing to fulfill one off compliance regulations as they arise.
Integrating an AI-driven compliance tool into the design and engineering process makes it easier to be proactive about how a product will comply with regulations. This removes manual, error-prone activities from the mix. It lets design and engineering teams know that they need to re-work or update a design earlier in the process—before it becomes an expensive, complex problem to fix. AI can even be leveraged to make suggestions about design changes that could reduce costs while maintaining compliance.
The need for a digital thread
To properly manage compliance in a dynamic environment, teams must connect their product data like never before. This is where the concept of a digital thread comes into the picture—linking product data gathered from across the product lifecycle and its associated manufacturing systems. By pulling real-time knowledge on each product’s manufacturing steps, requirements, materials, and other key data, teams can better understand their current compliance status and quickly adjust to future changes.
The combination of a digital thread and AI can also help in other ways. In some cases, it is important to narrow down the vast array of requirements to those that are truly relevant to the organization's industry and products. AI can be trained to review numerous overlapping or complementary requirements and highlight the ones that matter the most. It can also eliminate those that are unnecessary. This can prevent design teams from being overwhelmed or focusing on the wrong thing.
Collaborating with partners and key stakeholders
Organizations must also consider data interoperability to achieve a more agile approach to compliance. Key stakeholders such as supply chain partners will need a deeper understanding of compliance targets and reporting requirements to be active participants. It’s important to document the process details in a way that is easily shareable with outside resources.
Using AI to simplify compliance
The capabilities of AI-driven compliance tools will only continue to grow, and the organizations that can adopt them first will see a significant competitive advantage. However, the first step to embracing this type of technology is to consolidate and operationalize product and process data across the product lifecycle into a digital thread that can fuel innovation with AI.
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