AI Legislation Trends Shaping Due Diligence 2025
AI Legislation Trends Shaping Due Diligence 2025
Jan 21, 2025
AI laws in 2025 are reshaping due diligence practices. With over 400 AI-related bills across 41 U.S. states, along with global regulations like the EU AI Act, businesses are facing stricter compliance requirements. Here's what you need to know:
State-Level Complexity: States like California, Illinois, and Colorado are enforcing laws demanding transparency, data protection, and accountability in AI-driven decisions.
Global Standards: The EU AI Act introduces risk-based classifications, transparency mandates, and documentation requirements, influencing practices worldwide.
AI Tools in Action: Technologies like Natural Language Processing (NLP) and Explainable AI (XAI) streamline document reviews, flag risks, and ensure compliance.
Challenges: Companies must tackle privacy laws, AI liability, and governance issues while balancing risk- and harm-based approaches.
To stay compliant, businesses need robust AI governance, regular audits, and advanced tools like TRACT for real-time monitoring and risk management. The future of due diligence depends on adapting to these evolving regulations.
Major AI Laws Influencing Due Diligence in 2025
Differences Between Federal and State AI Laws
In 2025, AI legislation in the U.S. is a maze of state-specific rules, with federal involvement remaining limited. States like California, Delaware, and New Jersey are leading the charge, introducing laws that require detailed AI documentation, stronger personal data protections, and specific compliance measures [1] [3]. This patchwork of regulations forces businesses to navigate multiple, sometimes conflicting, standards, making compliance a challenge.
On top of domestic complexities, international efforts to align AI laws are reshaping how businesses handle cross-border due diligence.
Global Efforts to Align AI Regulations
Efforts to standardize AI laws globally are gaining traction, and businesses must adjust their compliance strategies to keep up. These regulations are particularly critical in cross-border investigations, where non-compliance can lead to fines or operational setbacks.
"Global regulations like the EU AI Act are driving businesses to prioritize transparency and accountability in AI systems." - Carmelo McCutcheon, VAST Data Federal's public sector CTO [2]
In 2025, a key development is the U.S. introducing new export controls on advanced computing and AI model weights [4]. These controls require businesses to maintain detailed records, adding another layer to cross-border due diligence.
Among these global efforts, the EU AI Act stands out as a major influence on compliance practices worldwide.
The EU AI Act and Its Role in Compliance
The EU AI Act has become a global reference point for AI regulation, shaping how organizations approach due diligence. Its risk-based classification system directly affects verification processes across industries.
"The EU AI Act will have profound implications on how enterprises worldwide implement identity verification technologies, particularly in heavily regulated sectors like banking and government." - Veronica Torres, Jumio worldwide privacy and regulatory counsel [2]
The Act impacts due diligence in three main areas:
| Requirement Area | Impact on Due Diligence | | --- | --- | | System Classification | Categorize systems based on risk levels | | Transparency | Clearly disclose system capabilities | | Accountability | Maintain thorough documentation
Businesses must now incorporate these requirements into their due diligence workflows while also adhering to local laws [3].
EU AI Act compliance: Key deadlines and how to prepare
How AI Improves Due Diligence Processes
AI is reshaping due diligence in 2025, making it faster, more precise, and better aligned with evolving regulations. Businesses now rely on advanced AI tools to streamline investigations and assess risks more effectively.
The Role of NLP and Explainable AI in Due Diligence
Natural Language Processing (NLP) and Explainable AI (XAI) are game changers in due diligence. They speed up document analysis while ensuring transparency in how decisions are made - crucial for meeting compliance standards. These technologies can quickly review contracts, legal papers, and regulatory filings, flagging risks and keeping detailed records of their findings.
Here’s how NLP and XAI are making an impact:
| Feature | How It Improves Due Diligence | | --- | --- | | <strong>Improved Accuracy</strong> | Minimizes errors during document reviews | | <strong>Faster Processing</strong> | Handles massive volumes of documents in minutes | | <strong>Stronger Compliance</strong> | Maintains clear, auditable decision records | | <strong>Early Risk Detection</strong> | Spots potential issues before they escalate
Real-Time Monitoring and Predictive Tools
Due diligence has shifted from periodic reviews to continuous oversight. Platforms like TRACT highlight this shift, offering instant insights through real-time tracking and predictive analytics.
Key capabilities of modern AI-driven platforms include:
Real-time tracking of legal, social, and personal data changes
Predictive analysis to identify risks before they grow
Automated alerts for critical updates or red flags
Detailed reports that meet regulatory demands
Ethical AI certifications and compliance checks have become essential to ensure responsible use of these tools. This aligns with regulations like the EU AI Act, which emphasizes transparency and accountability in AI systems.
While these advancements streamline due diligence, they also bring new challenges, especially as AI regulations become stricter.
Challenges of Using AI in Due Diligence Under New Laws
The rapid introduction of AI laws in 2025 has created hurdles for businesses trying to navigate a patchwork of regulations while keeping their due diligence processes compliant.
Comparing Risk-Based and Harm-Based Approaches
Risk-based methods focus on overall compliance but may fail to address specific AI-related issues, such as algorithmic bias. These methods are simpler to implement but less effective at tackling targeted problems. On the other hand, harm-based approaches zero in on specific risks, like privacy breaches, but require more resources. Hybrid models attempt to combine the strengths of both but can be challenging to execute. Choosing harm-based or hybrid approaches can help businesses meet stricter regulations by addressing specific concerns more thoroughly.
Privacy Laws and Their Effects on Due Diligence
Tough privacy laws in states like California, Colorado, and Illinois are pushing companies to reshape their investigation processes. These laws emphasize practices like limiting data collection, ensuring compliance across borders, and making AI decisions more transparent - all while maintaining the effectiveness of investigations [3]. This balancing act highlights the need for AI tools that support both compliance and operational goals.
AI Liability and Governance Issues
To stay compliant, companies must build strong governance structures. This includes assigning clear responsibility for AI decisions, conducting regular audits, and keeping detailed records of system behavior. At the same time, new U.S. export controls on AI technologies demand even stricter tracking and documentation [4].
Key governance priorities include:
Defining accountability for decisions made by AI systems
Performing regular audits to monitor system performance
Documenting system behavior and the rationale behind decisions
Adhering to changing state and federal rules
Tackling these challenges will require strategic planning and collaboration to adjust due diligence practices to meet the demands of new regulations.
Preparing for the Future of AI in Due Diligence
The Role of Collaboration and AI Education
Navigating the intricate world of AI regulations calls for stronger teamwork across industries. Sharing knowledge and best practices is key to keeping up with a regulatory landscape that’s constantly shifting. Companies also need to prioritize AI education programs that cover regulatory, ethical, and technical standards.
These training programs should address topics like algorithmic bias, privacy concerns, and the implementation of safeguards to ensure compliance. Building partnerships and creating knowledge-sharing networks can help organizations stay updated on regulatory changes. Together, these efforts create a solid foundation for refining due diligence processes to meet emerging demands.
Updating Due Diligence for New Regulations
Adapting due diligence processes to align with new regulations requires a structured approach to compliance and risk management. Here are some key areas to focus on:
| Requirement | Implementation Strategy | Compliance Goal | | --- | --- | --- | | Human Oversight | Form AI decision review committees | Align with <a href="https://www.klgates.com/The-Texas-Responsible-AI-Governance-Act-and-Its-Potential-Impact-on-Employers-1-13-2025" target="_blank" rel="nofollow noopener noreferrer" data-framer-link="Link:{"url":"https://www.klgates.com/The-Texas-Responsible-AI-Governance-Act-and-Its-Potential-Impact-on-Employers-1-13-2025","type":"url"}" data-framer-open-in-new-tab="">Texas Responsible AI Governance Act</a> | | Documentation | Maintain audit trails of AI systems | Fulfill state-level transparency obligations | | Risk Assessment | Assess AI tools and vendors | Avoid algorithmic discrimination | | Data Privacy | Apply state-specific controls | Meet 2025 state privacy laws
With stricter state-level enforcement expected in 2025, organizations must act now to develop proactive policies. Advanced tools like TRACT can simplify these adjustments, improving compliance and streamlining due diligence efforts.
Using TRACT for Smarter Due Diligence
TRACT offers a smarter way to handle due diligence by aggregating and analyzing data in real time. This helps organizations quickly spot potential risks while staying compliant with the new state privacy laws set to take effect in 2025. These laws will impact states like Delaware, Iowa, and Nebraska, among others [3].
Conclusion: Navigating AI Laws in Due Diligence
The AI regulatory landscape in 2025 requires businesses to rethink their due diligence processes. This is especially true for industries with strict compliance demands, where rules are changing at a rapid pace.
"Global regulations like the EU AI Act are pressuring businesses to ensure AI systems are transparent, accountable, and privacy-compliant." - Carmelo McCutcheon, VAST Data Federal's public sector CTO [2]
State-level laws are adding further complexity. For instance, Illinois has introduced strict rules for AI in employment decisions, while Maryland targets facial recognition systems [5]. These shifts highlight the need for organizations to prioritize compliance strategies.
Here are some critical focus areas and actionable steps for staying compliant:
| Focus Area | Action Plan | Outcome | | --- | --- | --- | | Data Protection | Strengthen security for both stored and moving data | Better alignment with privacy laws | | AI Transparency | Use explainable AI with clear audit trails | Easier adherence to regulations | | Risk Management | Regularly evaluate AI tools and vendor practices | Lower risk of legal issues
To tackle these challenges, advanced tools like TRACT can make a huge difference. By tapping into large datasets and offering fast, compliant solutions, platforms like this help businesses keep up with changing regulations. Pairing such technology with a commitment to data privacy and ethical AI practices ensures organizations can confidently navigate these new demands.
Related Blog Posts
AI laws in 2025 are reshaping due diligence practices. With over 400 AI-related bills across 41 U.S. states, along with global regulations like the EU AI Act, businesses are facing stricter compliance requirements. Here's what you need to know:
State-Level Complexity: States like California, Illinois, and Colorado are enforcing laws demanding transparency, data protection, and accountability in AI-driven decisions.
Global Standards: The EU AI Act introduces risk-based classifications, transparency mandates, and documentation requirements, influencing practices worldwide.
AI Tools in Action: Technologies like Natural Language Processing (NLP) and Explainable AI (XAI) streamline document reviews, flag risks, and ensure compliance.
Challenges: Companies must tackle privacy laws, AI liability, and governance issues while balancing risk- and harm-based approaches.
To stay compliant, businesses need robust AI governance, regular audits, and advanced tools like TRACT for real-time monitoring and risk management. The future of due diligence depends on adapting to these evolving regulations.
Major AI Laws Influencing Due Diligence in 2025
Differences Between Federal and State AI Laws
In 2025, AI legislation in the U.S. is a maze of state-specific rules, with federal involvement remaining limited. States like California, Delaware, and New Jersey are leading the charge, introducing laws that require detailed AI documentation, stronger personal data protections, and specific compliance measures [1] [3]. This patchwork of regulations forces businesses to navigate multiple, sometimes conflicting, standards, making compliance a challenge.
On top of domestic complexities, international efforts to align AI laws are reshaping how businesses handle cross-border due diligence.
Global Efforts to Align AI Regulations
Efforts to standardize AI laws globally are gaining traction, and businesses must adjust their compliance strategies to keep up. These regulations are particularly critical in cross-border investigations, where non-compliance can lead to fines or operational setbacks.
"Global regulations like the EU AI Act are driving businesses to prioritize transparency and accountability in AI systems." - Carmelo McCutcheon, VAST Data Federal's public sector CTO [2]
In 2025, a key development is the U.S. introducing new export controls on advanced computing and AI model weights [4]. These controls require businesses to maintain detailed records, adding another layer to cross-border due diligence.
Among these global efforts, the EU AI Act stands out as a major influence on compliance practices worldwide.
The EU AI Act and Its Role in Compliance
The EU AI Act has become a global reference point for AI regulation, shaping how organizations approach due diligence. Its risk-based classification system directly affects verification processes across industries.
"The EU AI Act will have profound implications on how enterprises worldwide implement identity verification technologies, particularly in heavily regulated sectors like banking and government." - Veronica Torres, Jumio worldwide privacy and regulatory counsel [2]
The Act impacts due diligence in three main areas:
| Requirement Area | Impact on Due Diligence | | --- | --- | | System Classification | Categorize systems based on risk levels | | Transparency | Clearly disclose system capabilities | | Accountability | Maintain thorough documentation
Businesses must now incorporate these requirements into their due diligence workflows while also adhering to local laws [3].
EU AI Act compliance: Key deadlines and how to prepare
How AI Improves Due Diligence Processes
AI is reshaping due diligence in 2025, making it faster, more precise, and better aligned with evolving regulations. Businesses now rely on advanced AI tools to streamline investigations and assess risks more effectively.
The Role of NLP and Explainable AI in Due Diligence
Natural Language Processing (NLP) and Explainable AI (XAI) are game changers in due diligence. They speed up document analysis while ensuring transparency in how decisions are made - crucial for meeting compliance standards. These technologies can quickly review contracts, legal papers, and regulatory filings, flagging risks and keeping detailed records of their findings.
Here’s how NLP and XAI are making an impact:
| Feature | How It Improves Due Diligence | | --- | --- | | <strong>Improved Accuracy</strong> | Minimizes errors during document reviews | | <strong>Faster Processing</strong> | Handles massive volumes of documents in minutes | | <strong>Stronger Compliance</strong> | Maintains clear, auditable decision records | | <strong>Early Risk Detection</strong> | Spots potential issues before they escalate
Real-Time Monitoring and Predictive Tools
Due diligence has shifted from periodic reviews to continuous oversight. Platforms like TRACT highlight this shift, offering instant insights through real-time tracking and predictive analytics.
Key capabilities of modern AI-driven platforms include:
Real-time tracking of legal, social, and personal data changes
Predictive analysis to identify risks before they grow
Automated alerts for critical updates or red flags
Detailed reports that meet regulatory demands
Ethical AI certifications and compliance checks have become essential to ensure responsible use of these tools. This aligns with regulations like the EU AI Act, which emphasizes transparency and accountability in AI systems.
While these advancements streamline due diligence, they also bring new challenges, especially as AI regulations become stricter.
Challenges of Using AI in Due Diligence Under New Laws
The rapid introduction of AI laws in 2025 has created hurdles for businesses trying to navigate a patchwork of regulations while keeping their due diligence processes compliant.
Comparing Risk-Based and Harm-Based Approaches
Risk-based methods focus on overall compliance but may fail to address specific AI-related issues, such as algorithmic bias. These methods are simpler to implement but less effective at tackling targeted problems. On the other hand, harm-based approaches zero in on specific risks, like privacy breaches, but require more resources. Hybrid models attempt to combine the strengths of both but can be challenging to execute. Choosing harm-based or hybrid approaches can help businesses meet stricter regulations by addressing specific concerns more thoroughly.
Privacy Laws and Their Effects on Due Diligence
Tough privacy laws in states like California, Colorado, and Illinois are pushing companies to reshape their investigation processes. These laws emphasize practices like limiting data collection, ensuring compliance across borders, and making AI decisions more transparent - all while maintaining the effectiveness of investigations [3]. This balancing act highlights the need for AI tools that support both compliance and operational goals.
AI Liability and Governance Issues
To stay compliant, companies must build strong governance structures. This includes assigning clear responsibility for AI decisions, conducting regular audits, and keeping detailed records of system behavior. At the same time, new U.S. export controls on AI technologies demand even stricter tracking and documentation [4].
Key governance priorities include:
Defining accountability for decisions made by AI systems
Performing regular audits to monitor system performance
Documenting system behavior and the rationale behind decisions
Adhering to changing state and federal rules
Tackling these challenges will require strategic planning and collaboration to adjust due diligence practices to meet the demands of new regulations.
Preparing for the Future of AI in Due Diligence
The Role of Collaboration and AI Education
Navigating the intricate world of AI regulations calls for stronger teamwork across industries. Sharing knowledge and best practices is key to keeping up with a regulatory landscape that’s constantly shifting. Companies also need to prioritize AI education programs that cover regulatory, ethical, and technical standards.
These training programs should address topics like algorithmic bias, privacy concerns, and the implementation of safeguards to ensure compliance. Building partnerships and creating knowledge-sharing networks can help organizations stay updated on regulatory changes. Together, these efforts create a solid foundation for refining due diligence processes to meet emerging demands.
Updating Due Diligence for New Regulations
Adapting due diligence processes to align with new regulations requires a structured approach to compliance and risk management. Here are some key areas to focus on:
| Requirement | Implementation Strategy | Compliance Goal | | --- | --- | --- | | Human Oversight | Form AI decision review committees | Align with <a href="https://www.klgates.com/The-Texas-Responsible-AI-Governance-Act-and-Its-Potential-Impact-on-Employers-1-13-2025" target="_blank" rel="nofollow noopener noreferrer" data-framer-link="Link:{"url":"https://www.klgates.com/The-Texas-Responsible-AI-Governance-Act-and-Its-Potential-Impact-on-Employers-1-13-2025","type":"url"}" data-framer-open-in-new-tab="">Texas Responsible AI Governance Act</a> | | Documentation | Maintain audit trails of AI systems | Fulfill state-level transparency obligations | | Risk Assessment | Assess AI tools and vendors | Avoid algorithmic discrimination | | Data Privacy | Apply state-specific controls | Meet 2025 state privacy laws
With stricter state-level enforcement expected in 2025, organizations must act now to develop proactive policies. Advanced tools like TRACT can simplify these adjustments, improving compliance and streamlining due diligence efforts.
Using TRACT for Smarter Due Diligence
TRACT offers a smarter way to handle due diligence by aggregating and analyzing data in real time. This helps organizations quickly spot potential risks while staying compliant with the new state privacy laws set to take effect in 2025. These laws will impact states like Delaware, Iowa, and Nebraska, among others [3].
Conclusion: Navigating AI Laws in Due Diligence
The AI regulatory landscape in 2025 requires businesses to rethink their due diligence processes. This is especially true for industries with strict compliance demands, where rules are changing at a rapid pace.
"Global regulations like the EU AI Act are pressuring businesses to ensure AI systems are transparent, accountable, and privacy-compliant." - Carmelo McCutcheon, VAST Data Federal's public sector CTO [2]
State-level laws are adding further complexity. For instance, Illinois has introduced strict rules for AI in employment decisions, while Maryland targets facial recognition systems [5]. These shifts highlight the need for organizations to prioritize compliance strategies.
Here are some critical focus areas and actionable steps for staying compliant:
| Focus Area | Action Plan | Outcome | | --- | --- | --- | | Data Protection | Strengthen security for both stored and moving data | Better alignment with privacy laws | | AI Transparency | Use explainable AI with clear audit trails | Easier adherence to regulations | | Risk Management | Regularly evaluate AI tools and vendor practices | Lower risk of legal issues
To tackle these challenges, advanced tools like TRACT can make a huge difference. By tapping into large datasets and offering fast, compliant solutions, platforms like this help businesses keep up with changing regulations. Pairing such technology with a commitment to data privacy and ethical AI practices ensures organizations can confidently navigate these new demands.
Related Blog Posts
Unlock the Power of Advanced People Research
Elevate your decision-making with real-time, comprehensive data, transforming data into your most valuable asset. Begin with TRACT today and ensure every decision is backed by unmatched precision.
Schedule a Demo
Unlock the Power of Advanced People Research
Elevate your decision-making with real-time, comprehensive data, transforming data into your most valuable asset. Begin with TRACT today and ensure every decision is backed by unmatched precision.
Schedule a Demo
Unlock the Power of Advanced People Research
Elevate your decision-making with real-time, comprehensive data, transforming data into your most valuable asset. Begin with TRACT today and ensure every decision is backed by unmatched precision.
Schedule a Demo
Unlock the Power of Advanced People Research
Elevate your decision-making with real-time, comprehensive data, transforming data into your most valuable asset. Begin with TRACT today and ensure every decision is backed by unmatched precision.
Schedule a Demo