In regulated industries, hardcoded logic can quickly become too complex to manage, which is why it’s essential to start simple and scale as needed. This approach involves using different tools for different stages of complexity, ultimately aiming for auditable, traceable, and reproducible decisions.
For simpler cases, JSON logic can be used for managing 10–50 rules, providing a straightforward and efficient solution. However, as the number of rules and interdependencies grows, more advanced tools such as rules engines become necessary. For the most complex cases, AI can be utilized for pattern recognition, allowing for more sophisticated decision-making. By combining these tools, businesses can ensure compliance, performance, and explainability from the outset, keeping their workflows reliable and meeting regulatory requirements.
The impact of implementing a scalable decision engine is significant, as it enables companies to maintain reliable workflows while keeping regulators satisfied. By starting simple and scaling as needed, businesses can avoid the pitfalls of unmanageable complexity and ensure that their decision-making processes are auditable, traceable, and reproducible. As companies continue to navigate the complexities of regulated industries, the use of JSON logic, rules engines, and AI is likely to become increasingly important for maintaining compliance and driving success.
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