From bureaucratic red tape to dynamic, evidence-based systems - the regulatory revolution is here
Regulation often brings to mind thick binders of obscure rules and bureaucratic red tape. But this perception hides a more exciting reality: regulation is undergoing its own revolution, transforming from a static set of constraints into a dynamic, evidence-based system that adapts to our rapidly changing world.
From artificial intelligence to genetic engineering, new technologies are emerging at an unprecedented pace, creating both extraordinary opportunities and complex challenges. The regulatory frameworks that guide these innovations are now in the spotlight as never before.
Researchers supported by federal grants now spend more than 40% of their research time simply complying with administrative and regulatory requirements rather than doing actual science 1 .
This "wasting [of] intellectual capacity and taxpayer dollars" represents a massive drag on innovation at a time when scientific progress is crucial to addressing global challenges from climate change to pandemic preparedness.
The current system has become so burdened with redundancy and complexity that it's actually "hampering innovation," according to Alan Leshner, who has held leadership positions at the NIH and NSF 1 .
of researcher time spent on compliance
This article explores how a new scientific approach to regulation itself—embracing experimentation, technology, and evidence-based design—is creating smarter frameworks that protect the public while unleashing human ingenuity.
A framework proposed by the National Academies of Sciences, Engineering, and Medicine to transform regulatory systems 1
Creating consistent requirements across federal and state agencies and research institutions to eliminate confusion, redundancy, and extra work.
Ensuring that regulatory scrutiny matches the actual risk related to a project, avoiding unnecessary burdens for low-risk activities.
Using digital tools to make compliance processes more efficient, reducing administrative burdens while maintaining oversight.
A powerful example of regulatory disharmony can be found in animal research, where both the U.S. Department of Agriculture and the Office of Laboratory Animal Welfare regulate the same research but sometimes with conflicting requirements. This creates "confusion, redundancy, and extra work," according to a National Academies report 1 .
At the cutting edge of regulatory science lies a powerful approach: regulatory experimentation. This involves testing new regulatory approaches under controlled conditions before full implementation 3 .
The Centre for Regulatory Innovation defines regulatory experimentation as "a test or trial of a new product, service, approach or process designed to generate evidence or information that can inform the design or administration of a regulatory regime" 3 .
This evidence-based method represents a significant shift from traditional regulation, which often remains static for decades despite rapid changes in technology and society.
According to research from the Productivity Commission of New South Wales, experiments "drive better regulation by allowing regulators to respond to risks and adapt to a changing regulatory environment" and "find more cost-effective ways of regulating" 6 .
This approach builds a robust foundation for better regulation through systematic evidence collection rather than relying on assumptions or political preferences.
One of the most promising forms of regulatory experimentation is the regulatory sandbox—a controlled environment where innovators can test new products, services, or business models without immediately incurring all the normal regulatory consequences 6 .
Think of it as a safety zone where both regulators and the regulated can learn about novel approaches in real-world conditions but with appropriate safeguards.
Regulators identify an area where existing rules may be hindering beneficial innovation
Establishing clear boundaries, duration, monitoring requirements, and participant criteria
Choosing a diverse set of qualified participants to test within the sandbox
Running the experiment with ongoing data collection and supervision
Analyzing results to determine whether the innovation should be more widely permitted
The scale of the regulatory burden problem becomes clear when examining the data. The following statistics quantify both the costs of the current system and the potential benefits of reform.
| Aspect of Burden | Statistical Evidence | Impact Level |
|---|---|---|
| Researcher time spent on compliance | Over 40% of research time 1 |
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| Institutional compliance costs | $1-1.4 million annually per institution 1 |
|
| Regulatory policies adopted (1991-2024) | 62% were issued from 2014-2024 1 |
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| Compliance officers prioritizing automation | 45% focusing on automation in next 2 years 7 |
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Limited research infrastructure and staff means the burden falls on researchers themselves 1 .
Smaller administrative support systems take time away from "pursuing intellectual curiosity" 1 .
Still face significant costs but have more buffers and can redirect funds from research to compliance.
As Emanuel Waddell of North Carolina A&T State University notes, "Typically, the more underresourced institutions—regional state institutions, minority-serving institutions, HBCUs and tribal colleges—may not have as large of a research infrastructure or staff to handle some of the regulations that filter down from the federal level" 1 . This regulatory disparity exacerbates existing inequalities in the scientific ecosystem, potentially stifling diverse perspectives and innovation.
KPMG's analysis identifies 2025 as "the Year of Regulatory Shift" driven by new administration priorities, agency leadership changes, continued technology advances, and evolving risk patterns 2 .
New AI Executive Order expected, focusing on innovation and growth while addressing ethical concerns.
Continued scrutiny of data security, risk management, and incident response protocols across sectors.
Expanded regulatory coverage despite legal challenges to jurisdictions and enforcement mechanisms.
Focus on interplay between AI, cybersecurity, privacy and national security in critical infrastructure.
Balancing diverse regulations across jurisdictions and agencies creating complex compliance challenges.
Increasing requirements for environmental, social, and governance (ESG) disclosures and compliance.
These trends reflect a broader shift toward what KPMG calls "regulatory divergence"—different agencies and jurisdictions moving in potentially conflicting directions, creating complex compliance challenges for organizations operating across boundaries . This makes the need for harmonization and smart regulation even more urgent.
Just as laboratory science requires specialized equipment, regulatory science has developed its own toolkit of approaches and technologies enabling the regulatory revolution.
Provide structured environments for testing regulatory approaches before full implementation.
Automate tracking of regulatory changes across jurisdictions and assess impact 4 .
Continuously track legal and regulatory developments with automated alerts 7 .
Automate evidence collection, monitoring, and reporting tasks to reduce manual work 9 .
Use artificial intelligence to identify compliance risks and prioritize resources effectively 8 .
Analyze regulatory patterns, predict changes, and optimize compliance strategies using data.
These tools are transforming regulation from a reactive, manual process to a proactive, data-driven function. As one analysis notes, "43% of Chief Ethics and Compliance Officers (CCOs) find new regulatory requirements their greatest challenge," and 45% are prioritizing automation of compliance processes over the next two years 7 .
The state of regulation is at a pivotal moment. The traditional approach—layering rule upon rule without systematic evaluation—has created a system that burdens innovators while often failing to achieve its protective goals efficiently.
But a new scientific approach to regulation itself is emerging, centered on evidence, experimentation, and efficiency. This revolution won't happen automatically. As the National Academies report emphasizes, "There's an urgency to this. We really have to get this done," particularly given constrained budgets and growing national debt 1 .
The transformation requires both technological tools and a cultural shift among regulators toward viewing themselves as architects of systems that enable innovation while managing risk.
The goal is not simply less regulation, but better regulation—smarter frameworks that protect public interests without stifling human creativity. As we face increasingly complex challenges from emerging technologies to global health threats, building this adaptive, evidence-based regulatory system may be one of the most important innovations of our time.
The future of regulation will likely be written not in immutable stone, but in adaptable code—capable of learning, evolving, and improving as we gather more evidence about what actually works in our complex world.
References to be added manually in this section.