The Information Asymmetry Tax Is Coming Due: How AI is Dismantling Profitable Intentional Complexity

The Information Asymmetry Tax Is Coming Due: How AI is Dismantling Profitable Intentional Complexity

For as long as I can remember, certain business models have thrived on a simple premise: make the rules so complex that customers can’t effectively challenge you.

Medical billing codes. Insurance claim procedures. Debt collection regulations. Complex B2B contract terms. These aren’t accidentally complicated. They’re strategically created that way. The complexity itself is the moat.

I recently came across a fascinating concept called “Adversarial Prompting”.  This is using LLMs to conduct institutional-grade investigations that were previously cost-prohibitive for individuals. This is using AI to systematically go through and parse technical frameworks, cross-reference multiple regulatory documents, and identify categorical violations that institutions hope you’ll never find.

The cost of professional advocacy just collapsed from thousands of dollars to a few hours of time.

The Business Model Reckoning

Here’s what makes this a watershed moment: entire industries have monetized the gap between what’s legally/contractually correct and what customers can practically verify.  (Think about “free trials” that require a credit card to proceed.)

Consider medical billing. A hospital might incorrectly bundle procedures, violating CMS regulations buried in technical documentation that would take a human days to parse. Previously, disputing a $15,000 bill meant hiring a medical billing advocate for $3,000-5,000. Most people just paid.

Now? An LLM can cross-reference CPT codes against Medicare bundling rules, fee schedules, and state regulations in minutes. It can draft correspondence that cites specific regulatory sections and signals institutional sophistication. The hospital’s billing department suddenly faces systematic, scalable auditing by patients who sound like they have legal counsel.

When your business model depends on customers not doing the math, AI just handed everyone a calculator.

Besides healthcare:

• Insurance companies relying on complex denial procedures
• Debt collectors banking on consumers not knowing FDCPA regulations
• SaaS vendors with deliberately confusing usage-based pricing
• Property management companies with opaque fee structures

The pattern is the same: profit extracted from information asymmetry is now under siege.

The Strategic Shift

At @igntia-ai where @Bruce de’medici is building AI governance and consulting practices, I’m watching companies face a choice:

1. Defensive: Try to maintain opacity (unsustainable and increasingly risky)
2. Adaptive: Rebuild business models on transparent, defensible practices before customers force the issue

The companies that built empires on confusing their customers are about to discover that their moat has drained overnight.

In Part 2, I’ll explore the risk management implications and what this means for compliance frameworks. Part 3 will cover how organizations should proactively respond.