M&A And Investment Advisory On AI Risk, Compliance, And Governance

AI is one of the biggest value creation opportunities but it also comes with risk. Understand AI-driven risks, and work to mitigate them pre or post-close.
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Note: Very few companies are in compliance with all of these regulations, many of which go into effect in 2026

Preparing for Compliance

Emerging Regulatory Requirements Specific To AI

As AI adoption grows, new laws are being introduced to ensure fairness, transparency, and accountability across industries.
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Colorado AI Act
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EU AI Act
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Illinois HB 3773
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New York City Local Law 144
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Texas Responsible Artificial Intelligence Governance Act
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Various California laws and regulations
Legal Risk Awareness

Non‑AI Regulatory Risks in AI‑Driven Organizations

In addition to AI-specific regulation, other issues may substantially affect the value of a potential target.
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Data privacy issues

Including compliance with GDPR, HIPAA, and various state privacy laws.
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Bias in AI systems

Risks related to ownership, usage rights, and patentability.
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Intellectual property protection

Especially “algorithmic bias” in hiring and people operations.
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Reputational risk

Public trust impact tied to AI misuse or data handling.
Trusted AI Expertise

Leadership in AI Governance & Diligence

With deep experience in auditing AI systems and advising on regulatory compliance, this expert brings proven leadership in risk, governance, and M&A diligence across global organizations.
ISO 42001 Certified Lead Auditor
Extensive experience auditing AI systems (startup to Global 50)
Deep experience in M&A diligence (sellside and buyside)
John Rood
President, Proceptual

“An international consensus has emerged through a tapestry of regulation:
nearly every company who develops or deploys AI will be required to establish a
robust system of AI governance.”

John Rood

President, Proceptual

What We Do

Key Steps in AI Risk Management

A clear, structured process to assess, reduce, and govern
AI-related risk.

Risk Assessment:
What are current and potential post-close liabilities?

Regulatory exposure

Compliance with current and forthcoming regulations.

Risk-based assessment for likely classification and regulatory burden under EU AI Act and Colorado AI Act.
Governance gaps
Examine policies for procurement, deployment, and monitoring.
Review internal control and accountability structure.
Estimate forward-looking compliance costs.
Review data use and privacy policies.
Assess risks due to intellectual property or privacy violations
Model risk
Evaluate model transparency and explainability (“black boxes”)
Shadow systems – unapproved use of AI tools
Third party tool evaluation
Review procurement process
Summarize current and post-close liability
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Risk Mitigation:
Address gaps and reduce risk

AI governance implementation: deploy NIST AI RMF and/or evaluate ISO 42001 certification
Evaluation for additional regulations by jurisdiction, e.g. NYC Local Law 144 Automated Tool audit
Implement model monitoring systems and reporting
Where appropriate, conduct model bias audit
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Ongoing Governance Programs:
Support long-term AI accountability

Install software-based go-forward governance system
Create AI risk reporting structure – “what does the board need to know?”
Organization-wide training on AI literacy, compliance, and safety
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Evaluation of AI

Past governance, we have extensive experience identifying potential
AI-driven value-creation levers on both revenue and cost sides.

Yes, we do the fun stuff too!

Note: Proceptual, Inc. is not a law firm and does not provide legal advice.
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