Five Cases Brief

LinkedIn Live Session Notes & Brief

When AI goes wrong — and who gets the call

Five cases. One common thread. The accountability gap that courts and regulators are now requiring organizations to close.

Jay Hawkinson, NACD.DC LinkedIn Live · June 23, 2026 AI governance and liability

The common thread across all five cases: None of these are technology failures. Every one is an accountability failure. An authority failure. A governance failure. Someone built or deployed a capable AI system without establishing, in writing, with named owners, who is responsible for its outputs, who can override it, and who is accountable when it is wrong. That gap is what the courts are finding. That gap is what Colorado and the EU are now requiring organizations to close.

The accountability failures that changed the law

1
Air Canada v. Moffatt
Chatbot liability — deployer owns the output

Air Canada argued its chatbot was a separate legal entity responsible for its own statements. The tribunal rejected that defense completely. Air Canada is responsible for all information on its website, including information provided by a chatbot. No named owner for chatbot outputs. No override protocol. No human review layer for consequential customer decisions.

Governance question
For every AI system you use in a customer or employee-facing context — who is named accountable for what it says?
2
Mobley v. Workday
AI hiring discrimination — vendor liability is not a defense

Workday argued it was a software vendor, not an employer. The court rejected that defense. Workday can be held liable as an agent because its customers delegated candidate screening to Workday’s AI. Workday’s own filings disclosed 1.1 billion applications were rejected through its AI tools during the relevant period. Preliminary collective certification granted May 2025 — potentially hundreds of millions of applicants. Complete absence of human oversight. No named person accountable for the screening function.

Governance question
Who reviews your AI-assisted hiring or workforce decisions against protected class outcomes? Not the vendor’s algorithm — a named human with documented authority.
3
Estate of Lokken v. UnitedHealth Group
90% alleged error rate — the system kept running

nH Predict carried an alleged 90% error rate on Medicare Advantage coverage denials — meaning nine out of ten denied claims that were appealed were ultimately reversed. Only 0.2% of patients filed appeals. In March 2026, the court ordered UnitedHealth to disclose the algorithm. The algorithm was allegedly wrong at high rates. The organization allegedly knew. It continued running because the economics worked. No named governance owner with authority to halt the system.

Governance question
What is the override rate on your AI systems? Who tracks it? Who owns it? If no one has that number, that is the gap.
4
Chaac Pizza Northeast v. Pizza Hut
$100M lawsuit — mandatory AI, no halt authority

A franchisee operating approximately 110 New York locations filed a $100 million lawsuit alleging a mandated AI delivery optimization system collapsed on-time delivery from above 90% to nearly half of orders taking 45 minutes or more. Alleged sales in New York dropped close to 20 percentage points. Filed May 2026. Mandatory system. No halt authority. No named owner of the system’s performance outcomes. No documented escalation path when outputs began destroying the business.

Governance question
If your most consequential AI system began producing wrong outputs today — who has the named, documented authority to halt it? Not pause it for review. Halt it.
5
Two regulatory deadlines — same governance requirement
EU AI Act August 2 · Fannie Mae August 6

EU AI Act Article 26 deployer obligations are currently scheduled for August 2, 2026. A pending Digital Omnibus agreement may shift high-risk system obligations to December 2027, but August 2 remains the binding enacted date as of today. Article 50 transparency obligations apply August 2 regardless of the Omnibus outcome. Fannie Mae Lender Letter LL-2026-04, effective August 6, requires a designated AI/ML governance policy owner who reviews the policy at least annually. Colorado SB 26-189, signed May 14, takes effect January 1, 2027. The convergent requirement across all three: a named, accountable owner for each AI system in production, with documented oversight and annual review.

Governance question
Can you name, today, the person accountable for each AI system your organization has in production — and produce that documentation on 30 days’ notice?
The three questions every organization needs to answer today
1
Do you know where you are using AI? You cannot govern what you have not mapped. This is the first question every regulator, insurer, and buyer asks. The answer is an AI inventory. Not a technology inventory. A decision inventory.
2
Is there a named person accountable for each significant AI system? Named. Not a team. Not a department. A person. With their name, their title, and their documented accountability in writing. This is the gap in every one of the five cases above.
3
Does that person know they have that authority? The authority-to-stop is not a technical configuration. It is an organizational decision. Someone has to be named. That name has to be written down. That person has to know they have the authority. And there has to be a protocol for when and how they exercise it.
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  • Complete case summaries including rulings and governance failure analysis
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  • Regulatory deadlines and what each one requires by name
  • A pointer to the VTCDO AI Governance Readiness Assessment sample output
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Jay Hawkinson, NACD.DC · VTCDO by Hawksroost · Your information is not shared or sold. You will receive the PDF and occasional session notifications. Unsubscribe at any time.

About Jay Hawkinson

25 years building data and AI organizations inside industrial manufacturers, CPG companies, and PE-backed enterprises. First functional CDAO at Valmont Industries. Built the 60-person data and AI function at Lamb Weston. Interim CIO at AFL Global. Director of Technology at a PwC operating unit.

NACD Directorship Certified NACD AI Oversight · CMU Heinz NACD Cybersecurity · CERT Forbes Technology Council
If your board is asking — your operating team needs this too

The five cases above are what happens at the board and regulatory level when governance fails. The companion VTCDO document maps the same governance gaps against ten specific operating scenarios: quality inspection, demand forecasting, workforce scheduling, predictive maintenance, pricing, supplier assessment, and more.

VTCDO by Hawksroost
Governance Suite and Fractional CDO Advisory for PE-backed industrials

This document is informational only and does not constitute legal advice. Case characterizations reflect publicly reported facts and allegations; not all matters have been fully adjudicated. Regulatory descriptions reflect the author’s professional assessment as of June 2026. Organizations should consult qualified legal counsel regarding compliance obligations specific to their operations.