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Decoding AI Regulation: What Employers Need to Know in 2025

Are you ready to navigate the uncharted waters of AI regulation in 2025, where innovation races ahead, but the rules are still being written?
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The increased use of AI in the workplace has redesigned jobs, reshaped business processes, and raised some tough questions about ethics and oversight. 

Today, employers face the challenge of decoding AI regulations that differ widely across jurisdictions while balancing innovation with compliance. Some guidance exists, but much remains unclear.

So, how can companies stay ahead when the rules are still being written?

What’s the Regulatory Landscape in 2025 Considering All Ethical Concerns and Risks?

Since taking office in January, President Trump has changed the direction of America’s AI policy. 

Essentially, the new administration hopes to secure the United States’ position as a global AI leader – by reducing barriers to AI development.

One of Trump’s first executive actions was replacing Biden’s “Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence“ order with “Removing Barriers to American Leadership in Artificial Intelligence“ – a clear signal of a federal shift toward deregulation.

Yet, this federal pullback may have inadvertently created a more complex landscape for businesses.

The Urgency for Employers to Prepare for Compliance

The AI revolution is already here – with investments reaching $1 trillion and an explosion of AI-driven workplace tools that are transforming how we do business. 

However, companies rushing to adopt these tools must be mindful of changing AI compliance laws and regulations.  

In 2024, lawmakers in 45 US states introduced nearly 700 bills related to artificial intelligence. 

Out of those, 99 bills became law. 

Across the country, 33 states have set up AI committees and task forces to examine AI’s impact, with their findings likely to guide future legislation.

In other words, with the recent removal of federal guardrails, many states are introducing their own regulations.

The Current Regulatory Landscape

As federal oversight of AI loosens, state and local governments are filling the gap with regulations to protect fairness and ethics in the workplace.

Here’s a look at some recent developments in the regulatory landscape:

The first algorithmic discrimination law targets high-risk AI systems that influence “consequential decisions,” such as employment outcomes. Employers in Colorado using AI will need to:

  • Proactively prevent algorithmic discrimination through “reasonable care” protocols
  • Adopt risk management policies 
  • Conduct yearly impact assessments
  • Notify employees when AI is involved in decisions like hiring or promotions

It also gives workers the right to challenge unfavorable AI-generated outcomes, such as firings or demotions. 

A similar bill targeting high-risk decisions was recently passed in Virginia and may potentially be effective July 1, 2026. 

Employers will be forbidden from using AI in ways that discriminate based on protected classes under the Illinois Human Rights Act. Companies must alert employees if AI is used in hiring, promotions, or layoffs and are banned from using zip codes as proxies for protected characteristics.

Already in effect, this law requires employers to disclose if AI analyzes video job interviews, obtain candidate consent, delete recordings upon request, and report data to state agencies.

Employers using automated employment decision tools must provide advance notice to employees or job candidates, conduct annual independent bias audits, and publicly share audit results.

Key Regulatory Requirements for Employers

Despite the relaxed federal stance, employers must remain cautious in decoding and complying with AI regulations. 

The lack of federal guidance does not change core anti-discrimination laws, such as Title VII of the Civil Rights Act and the Americans with Disabilities Act (ADA).  

These laws and their state equivalents still apply.

Even though the EEOC and the Department of Labor have pulled back on AI guidance, existing laws still regulate AI use in hiring and workplace decisions.

Employers must be cautious with the following uses:

  • If AI tools unintentionally exclude or disadvantage protected groups, they could violate Title VII.
  • AI that filters out candidates based on disability-related characteristics could result in ADA violations. 
  • Employers must protect AI-processed data to meet broader privacy laws.
  • Employers can still be held responsible for discrimination caused by third-party AI vendors.

There is a growing recognition that employers must regularly monitor all their AI tools, especially those considered high-risk. 

And as part of decoding AI regulation, it’s important to understand what qualifies as a high-risk AI system.

High-Risk AI Systems in the Workplace

While AI has existed in some form for nearly 70 years, its role in everyday life, especially in business operations, is more frequent than ever.

When AI starts making decisions about who gets hired, promoted, or receives a pay raise, the stakes are high.

These are what experts call “high-risk AI systems” (HRAIS), where algorithms have the power to shape careers and livelihoods. When left unchecked, these systems can unintentionally perpetuate bias and lead to unfair hiring practices or discriminatory promotions.

That’s why regulations like Colorado’s AI Act are appearing, with similar bills targeting HRAIS being considered in ten other states, including Texas, Nebraska, and Oklahoma. 

Overall, these HRAIS frameworks aim to define the responsibilities of AI developers and deployers while protecting consumers—or, in the workplace, employees—from algorithmic discrimination.

Building Your AI Compliance Framework

The reality is that businesses can’t afford to ignore AI. 

It is a powerful tool that’s changing industries, but it can also become a liability without supervision.

Simply put, companies that overlook AI compliance today risk legal trouble and reputational damage in the future. 

Yet, recent studies reveal that 57% of workplaces lack an AI use policy or are still in the process of creating one, while 17% of employees are unsure if such a policy even exists.

So, to stay ahead, employers need to evaluate their AI systems, adjust workforce strategies, and build a solid framework.

1) Governance Structures

Who is responsible for AI? 

Answering this and having lines of accountability is the foundation for managing AI responsibly. Companies, especially those that operate in multiple states, can work with experts and compliance services to create policies that guide how AI is developed and used. 

The goal is simple: make sure AI decisions follow the law and reflect company values.

2) Responsible AI Principles

Organizations need codified principles – such as fairness, transparency, and accountability – to guide AI use. 

In addition, companies building AI policies must proactively address bias in algorithms, ensure explainability for high-stakes decisions (like hiring or lending), and include human oversight in their systems.

3) Documentation and Disclosure

As mentioned, thorough documentation is not just good for transparency; it’s becoming a legal requirement in many states. 

For these reasons, employers should maintain detailed records of their own or their vendors’ AI model origins, training data sources, and intended use cases with the same precision they would apply to their tax records.  

Forward-thinking companies are developing “model cards” and “datasheets” that document an AI model’s characteristics, limitations, and risks in language accessible to both technical and non-technical stakeholders.

4) Risk Management Programs and Impact Assessments

While risk is an inherent part of innovation, it doesn’t have to be a blind spot.

Regular risk audits and “stress tests” for high-impact applications can help identify vulnerabilities before they escalate. 

No matter how advanced your predictive analytics are, it’s difficult to predict the real-world challenges that can happen after deploying AI systems. 

For this reason, it’s important to get feedback from internal teams, job candidates, and other third parties about their experiences with your AI processes.

5) Monitoring and Testing Protocols

Ultimately, AI systems should be treated as dynamic, evolving tools that require constant monitoring. Establish protocols to periodically review and test AI models to catch biases, inaccuracies, or unintended consequences. 

In other words, employers should do both pre-deployment checks and, more importantly, post-deployment audits.

Worker Rights and Protections

While AI can streamline work processes, it’s the skills that AI can’t replace – like empathy, critical thinking, and ethical judgment – that are at the center of fair and human-centered workplaces.

As new technology continues to shape our world, corporations are responsible for making sure it uplifts rather than undermines people.

Yet, as the number of companies adopting AI rises, so do lawsuits related to AI-driven discrimination.

For these reasons, businesses must ask the tough questions and address some core worker’s right challenges:

  • Privacy: How do we protect personal data when AI systems collect increasing amounts of information?
  • Responsibility: When AI systems cause harm, who is held accountable?
  • Bias: What steps can be taken to prevent AI from reinforcing biases or discriminating against certain groups?
  • Clarity: How can we make AI processes understandable so people know how decisions are made?
  • Consent: How can people clearly understand and agree with how their data is used?
  • Security: What measures ensure that AI systems are safe and reliable? 
  • Appeals: What systems are in place for people to challenge or question decisions made by AI?

The role of AI in HR, and more broadly the workplace, requires thoughtful integration because true success shouldn’t come at the expense of workers.

What’s the Competitive Advantage of Ethical AI Adoption?

In 2025, decoding AI regulation is more than a compliance exercise – it’s a commitment to ethical innovation.

In this new era of emerging regulatory standards, companies that build AI frameworks rooted in transparency, fairness, and accountability will be better positioned to avoid legal risks and protect their workforce.  

Beyond compliance, ethical AI use is a competitive advantage. 

It cultivates trust, strengthens company culture, and showcases leadership in a world where responsible AI practices define the future of work.

Embracing AI is no longer optional for companies, but adopting it responsibly and ethically is imperative for success.

Written by Ivana Radevska

Senior Content Writer at Shortlister

Sources

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