If you’ve been around the legal tech block a time or two, you’ve probably noticed a familiar pattern: We deploy technology to better understand and streamline the law as we know it. Legal analytics platforms sift through case law, AI-driven tools tackle contract review and due diligence, and blockchain-driven “smart contracts” hold the promise of self-executing agreements. But here’s a shift you might not have considered: It’s not just about making sense of the legal texts we already have. It’s about the laws themselves evolving to fit the tools we’re building.

Most of us think of legal technology as something that reacts to what Congress and courts produce. But what if tomorrow’s legislative drafters start structuring statutes—right from the get-go—in a code-like, machine-friendly manner? Over time, lawmakers might take their cues from how AI and automated reasoning systems process text. They could craft statutes with hyper-structured logic, standardized definitions, and reduced interpretive leeway. This would be more than just a stylistic choice: it could fundamentally reshape the balance of power among the branches of government and the role of agencies.

Courts and the Waning Ambiguity
Traditionally, the courts have a big job: interpret ambiguous statutes, reconcile conflicting provisions, and apply legal canons to unpack what Congress might have meant. If laws read more like neatly organized code—complete with precisely defined triggers, conditions, and outcomes—the courts’ interpretive heavy lifting could be significantly reduced. Judges would still have their constitutional role: to say what the law is and to apply it to specific facts. But if there’s less wiggle room, their work might look more like verifying whether the facts meet the clearly stated criteria, rather than engaging in lengthy interpretive gymnastics. While that doesn’t strip the courts of their authority, it does streamline their function. They become less about discovering meaning and more about confirming that a given scenario fits the predetermined parameters.

Agencies and the Loss of Regulatory Latitude
This shift could also ripple through the administrative state. Right now, agencies benefit from statutory ambiguity to interpret and fill in the gaps. They set rules and policy through their regulatory authority, often receiving deference from courts in recognition of their expertise. But if statutes are drafted with fewer interpretive grey areas—each statutory provision carefully defined and logically consistent—agencies may find themselves with less room to maneuver. The “we’ll fill in the details” model of agency rulemaking loses steam when Congress provides the details up front.

With less ambiguity, agencies shift from interpretive policymaking to more straightforward execution. Instead of spending months or years issuing nuanced regulations or “guidance” documents to shape how a vague provision should be applied, they might simply implement what’s already specified. Compliance systems, potentially automated themselves, would test facts against bright-line rules. Agencies would still exist and play vital roles in enforcement, oversight, and auditing compliance. But the discretionary space that has often allowed them to act as quasi-legislators within their domains would shrink.

So Is This a Constitutional Problem?
You might ask: Does this new style of legislating infringe on the separation of powers? After all, the courts are supposed to interpret the laws, and agencies—part of the executive branch—are supposed to enforce them. But clarity itself doesn’t violate the Constitution. Congress has every right to reduce uncertainty. The judiciary still interprets the law, but if Congress chooses to leave less to interpretation, that’s their prerogative. The courts don’t lose their constitutional authority; they just face clearer parameters. Likewise, the executive branch agencies aren’t being denied their role—they’re just being given a narrower script to follow.

In fact, from a governance standpoint, this could enhance transparency and accountability. Citizens, lawyers, and businesses could rely on laws that are more predictable and less subject to shifting interpretations as administrations change. But we also risk losing some of the nuance and flexibility that can be beneficial in complex policy areas, and we’ll have to navigate whether hyper-clarity inadvertently creates new complexities. Sometimes what looks simple in code form can still create corner cases the legislature never envisioned.

The Bottom Line
This direction—where legal text evolves to meet technology on its own terms—isn’t happening overnight. It may occur slowly and quietly, like how statutes went from flowing narrative to bullet points and subparagraphs over time. But if and when it happens, it will mark a fundamental shift. Instead of technology merely responding to the law, the law will respond to technology. That means courts might spend less time acting as oracles of meaning, and agencies might find less policy-making space in the penumbra of legislative intent.

For those of us at the intersection of law, technology, and knowledge management, it’s both exciting and unnerving. The legal information ecosystem we’ve built—of research platforms, case analysis tools, and regulatory trackers—might need to be rethought as laws come pre-baked with machine-readable frameworks. Whether that future is better or worse will be up for debate, but it’s a debate worth having now. The day may soon come when laws and legal tech start writing each other’s code, and we’ll need to understand the new roles each branch of government and each legal profession stakeholder will play in this transformed landscape.

What Does Code as Code Look Like?

Consider, for instance, a rule from the anti-money laundering (AML) domain—an area where today’s legal language remains inherently interpretive and relies heavily on human judgment.

Existing Legal Language (Traditional Format):
A typical AML regulation might read something like:

Financial institutions shall report to the appropriate regulatory authority any transaction that appears suspicious. A transaction may be considered suspicious if it is unusually large relative to the customer’s typical activity, lacks an apparent lawful purpose, or exhibits patterns of structuring intended to evade reporting thresholds.

In this formulation, terms like “suspicious,” “unusually large,” and “apparent lawful purpose” are deliberately vague. The law expects compliance officers to apply their professional judgment and consider context. While this flexibility can be valuable, it complicates automated compliance, as a machine cannot easily parse or reason about such inherently subjective criteria.

Evolved, Machine-Readable “Code” Format:
As laws evolve with technology in mind, the regulation might be reframed as a more granular and algorithm-friendly specification. For example:

  1. Definition of Variables:
    • Customer_Historical_Average (CHA): The average monthly transaction amount for the given account over the previous 12 months.
    • High-Risk_Jurisdiction_List: A standardized list of country codes designated by regulators as high-risk, accessible at a known machine-readable endpoint (e.g., a JSON file published by the regulatory authority).
    • Lawful_Purpose_Indicators: A set of standardized transaction metadata fields (e.g., transaction purpose codes, verified invoice references) that can be matched against a compliance registry.
    • Structuring_Pattern_Threshold: A numeric limit defining “structuring” as more than 3 transactions within 48 hours that sum to over a regulatory reporting threshold (e.g., $10,000), none of which individually exceed the reporting threshold.
  2. Logical Conditions for Suspicion: A transaction T is flagged as suspicious if it meets any of the following Boolean conditions:
    • (T.amount > (2 * CHA)) AND (T has no matching Lawful_Purpose_Indicators)
    • (T.amount > 10,000) AND (T.destination_country IN High-Risk_Jurisdiction_List)
    • (Number_of_Transactions_by_Account_Last_48h >= 3) AND (Sum_of_Those_Transactions > 10,000)
  3. Machine-Actionable Instructions: If any of these conditions evaluate to TRUE, the institution’s compliance system must:
    • Automatically label the transaction record with SUSPICIOUS = TRUE.
    • Trigger a secure API call to the regulatory authority’s reporting system, sending structured data (transaction metadata, account details, and relevant flags) in a predefined JSON schema.
    • Log the event in an immutable ledger for audit purposes.

How This Represents the Evolution:

  • Codified Structure: Instead of open-ended terms, the suspiciousness criteria are broken down into quantifiable and machine-checkable components.
  • Interoperability: Reference lists (like high-risk jurisdictions) and schemas (for reporting) are pulled from standardized, machine-readable repositories.
  • Reduced Ambiguity: Instead of “appears suspicious,” the law now specifies precisely defined thresholds and patterns that signal suspicion.

In this future scenario, the law has metamorphosed into something akin to a decision tree or a rules engine script—still set by human policymakers but now natively compatible with automated compliance tools. Legislators drafting new AML rules would write them so that machines can implement them directly, ushering in a seamless interplay between “legal code” and software code.

Where Can This Go?

As legal technology advances, we may witness a transformation where laws are drafted to align seamlessly with machine-readable logic. This shift toward hyper-structured, algorithm-friendly statutes has the potential to streamline judicial interpretation, reduce ambiguity for agencies, and enhance transparency for citizens and businesses. Courts could find themselves verifying facts against clearer statutory parameters, while agencies might shift from policymaking to straightforward execution. This evolution doesn’t violate the separation of powers but redefines the roles of each branch within a more deterministic legal framework. The challenge will be balancing precision with the flexibility needed for complex, real-world scenarios. Whether this future simplifies or complicates legal practice remains to be seen, but one thing is clear: as laws and technology begin writing each other’s code, the legal ecosystem must prepare for a fundamental change in how rules are created, interpreted, and enforced.