Most people are still debating AI regulation. While New York has introduced, voted on, and signed an AI Regulatory Bill into law Have other States missed the shift? The Rise of Pro-human AI laws is no longer theoretical—it's happening right now. While others hesitate, New York has already moved the needle! NY State Assembly Bill 2025-A6453A In December 2025 alone, three major signals dropped: The RAISE Act was introduced and is forcing accountability for high-risk AI model

It is time for an AI-RCM Transparency Reset! It's 2026, and Artificial Intelligence (AI) in Revenue Cycle Management (RCM) is shifting from experimental tools to a foundational AI-powered infrastructure, significantly transforming the workforce by automating routine, rules-based tasks like clinical documentation integrity (CDI), medical coding, denial management, and eligibility verification. While these moves are supposed to cause some job displacement in manual, entry-lev

Yesterday, we asked: Is AI Coding Correctly? Today, we follow up with, if AI is Coding Incorrectly, what does one do in this Supercharged AI environment? When patient services are coded incorrectly, and organizational leadership is challenged to believe you. The situation shifts from a technical issue to a compliance and ethical crisis. Incorrect coding—whether upcoding ( billing for higher services ) or downcoding ( missed revenue ) —violates False Claims Act (FCA) regu

Is AI Coding Correctly? AI in Healthcare RCM is Failing Despite Heavy Investment The core problem is that AI tools are being built on flawed foundations — trained only on historical claims data without clinical context — and can't keep up with constantly changing payer rules Becker Hospital Review . We focus on Three Key Failure Points here: Denials are getting worse, not better. Denial rates jumped from 30% (2022) to 41% (2025), even as AI adoption increased. AI essentially

The Dark Side of AI We see the same mistakes over and over again in Artificial Intelligence (AI) and Revenue Cycle Management (RCM) projects: data drift, misaligned KPIs, and weak governance. An example of issues that shrink projected revenue and create quality and compliance risks on implementation projects is provided below: Drift and Decay: The AI Model Gets Worse Silently The Pitfalls: Teams launch new AI models and forget about them. The environments begin to change ov

The AI Algorithm Drift Grift Is the AI Algorithms Drift issue a Grift? No. Artificial Intelligence (AI) Algorithmic Drift itself is NOT a grift — but the way some vendors handle the issues associated with AI Drift, (or hide it) absolutely can be . Algorithm drift is a real, well-documented technical phenomenon in machine learning. Drift itself is a legitimate science. For those who might be pondering what a Grift is? An AI in RCM Grift refers to a kind of hustle that exa