AI and Machine Learning in Business Intelligence for Regulatory Systems: A Framework for Enhanced Compliance
Year: 2025
Type: article
Abstract: AI and ML are turning regulatory compliance on its head across virtually every sector. Regulations keep getting more complex, enforcement tougher, and yet most organizations are still stuck with painfully outdated manual processes that eat up resources while offering dubious reliability at best. This article digs into how AI approaches aren't just speeding up old workflows—they're enabling capabilities that simply weren't possible before. The real game-changer? Combining intelligent data integration with sophisticated natural language processing and predictive modeling to break the endless cycle of remediation. Organizations can finally look forward instead of constantly glancing in the rearview mirror. What's fascinating is how similar architectural patterns emerge across wildly different industries. Knowledge graphs and explainable AI aren't just technical buzzwords—they've become essential both for system performance and for getting regulators comfortable with algorithmic approaches.The implementation stories from financial services, healthcare, and manufacturing paint an interesting picture: quick-hit tactical applications deliver immediate wins, but it's the strategic implementations that truly transform compliance from a necessary evil to a competitive weapon. And here's the kicker—unlike almost every other technology investment, these systems actually appreciate in value over time instead of depreciating. That flies in the face of traditional ROI calculations and forces us to rethink how it value these investments entirely.
Author: Alka Soni
Language: English
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6949676835
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