Contracts

Greg Brockman's personal diary emerged this week as central evidence in Elon Musk's lawsuit against OpenAI, with the co-founder and president testifying about his internal deliberations over converting the organization from nonprofit to for-profit status. The diary directly addresses Musk's core claim that OpenAI deceived him by abandoning its original mission to develop artificial intelligence for humanity's benefit. Testimony also revealed inflammatory communications: text messages in which Musk threatened to make Brockman and CEO Sam Altman "the most hated men in America" if no settlement was reached, and a 2017 meeting where Musk tore a painting from the wall after cofounders rejected his demand for majority equity.

Palantir CEO Alex Karp has publicly attacked low-quality AI outputs as "slop," positioning the company's AI Platform (AIP) as a secure, enterprise-grade alternative built on its Foundry data infrastructure. The criticism comes as Palantir faces investor concerns that it may lose market share to cheaper, faster standalone large language models from OpenAI and Anthropic—competitors that don't require Palantir's ontology-based data backbone.

Organizations across all sectors are facing a wave of litigation over their data practices and AI systems. According to a Baker Donelson report, these legal challenges now extend well beyond technology companies and data brokers to affect organizations of every size that rely on data for operations, network security, regulatory compliance, and contractual obligations. The disputes involve civil liberties groups, workers' advocates, and privacy organizations pursuing claims centered on data privacy violations, algorithmic bias, unauthorized data use, AI system liability, and worker surveillance.

Anthropic has asked a California federal judge to rule that its use of copyrighted materials to train Claude qualifies as transformative fair use, comparing the AI's training process to how humans learn by reading and absorbing themes. The filing stands apart from the $1.5 billion class-action settlement in Bartz v. Anthropic, where the claims deadline passed on March 30, 2026, and a fairness hearing is scheduled for May 14, 2026, in San Francisco federal court.

Anthropic's CFO Krishna Rao is managing an unprecedented scaling challenge. In early 2026, CEO Dario Amodei disclosed that the company's growth trajectory had exploded far beyond projections—Anthropic is on track to expand roughly 80 times in a single year, compared to the originally planned 10–15 times. This surge has forced the company to renegotiate major cloud and infrastructure agreements with AWS and other hyperscalers while simultaneously managing service outages and capacity constraints.

The Federal Circuit reversed a jury verdict in International Medical Devices, Inc. v. Cornell, holding that cosmetic penile implant designs alleged as trade secrets were not protectable under California law because they had been disclosed in publicly available patents. The court found the designs "generally known" and therefore ineligible for trade secret status. A fourth alleged secret—a list of surgical instruments sent via email without confidentiality markings—also failed protection due to insufficient secrecy measures. The panel reversed findings of trade secret misappropriation, breach of contract under the parties' nondisclosure agreement, and improper inventorship claims related to two Penuma patents. The court affirmed $1 million in statutory damages for trademark counterfeiting.

Major AI software vendors are abandoning per-seat licensing in favor of consumption-based pricing tied to work output. Salesforce now charges for "agentic work units," while Workday bills based on "units of work" completed. OpenAI CEO Sam Altman has signaled the industry will shift toward "selling tokens"—the computational units underlying AI processing—positioning artificial intelligence as a utility priced like electricity or water.

Legal AI tools are reshaping law firm economics. Document review, drafting, and research are now 60–70% faster, with individual attorneys expected to save 190–240 billable hours annually. Thomson Reuters' 2025 Future of Professionals Report quantifies this as $20–32 billion in time savings across the U.S. market. Major clients—Meta, Zscaler, UBS—are already demanding "AI discounts" and refusing to pay for work automatable by machine. The pressure is immediate and client-driven.

Microsoft released Legal Agent on April 30, 2026, a specialized AI tool embedded directly into Microsoft Word for contract analysis and drafting. The platform performs clause-by-clause reviews against customizable playbooks, generates negotiation-ready redlines with transparent tracked changes, compares document versions to surface risks, and produces precise edits—all while preserving Word's native formatting and change-tracking features. Legal Agent uses structured workflows and deterministic resolution rather than general-purpose AI models, reducing processing time and cost. The tool operates within Microsoft 365 security controls and is immediately available through the Frontier program for Windows desktop users in the US. Microsoft explicitly states the tool does not provide legal advice and requires attorney verification of all outputs.

Jury selection began April 28 in Elon Musk's lawsuit against OpenAI, Sam Altman, Greg Brockman, and Microsoft in U.S. District Court for the Northern District of California in Oakland. Opening statements occurred April 29. Musk alleges OpenAI breached its 2015 nonprofit founding agreement by converting to a for-profit model in 2019 with Microsoft backing, abandoning its stated mission to develop AI for humanity's benefit. He invested $38–45 million in the company. Musk seeks OpenAI's return to nonprofit status, removal of Altman and Brockman from leadership, and $134–150 billion in damages to be redirected to OpenAI's charitable arm.

Elon Musk testified April 28 in a California courtroom that OpenAI breached a foundational promise by converting from nonprofit to for-profit status. Now valued at $852 billion, OpenAI made the shift despite Musk's 2017 warning that the company should either remain nonprofit or operate independently. "It is not OK to steal a charity," Musk told the court, referencing email exchanges with Sam Altman in which Altman expressed support for the nonprofit model but acknowledged no legal obligation bound the company to it permanently.

On May 1, 2026, the Pentagon announced classified military network access agreements with eight technology companies: SpaceX, OpenAI, Google, NVIDIA, Reflection, Microsoft, Amazon Web Services, and Oracle. The integrations will support planning, logistics, targeting, and operations on networks classified at Secret and Top Secret levels. The accelerated onboarding process—compressed to under three months from the prior 18-month standard—reflects Pentagon leadership's push under Secretary Pete Hegseth to diversify defense technology suppliers and reduce reliance on traditional prime contractors.

Venable LLP has published a legal analysis identifying a critical gap in U.S. law: traditional agency doctrine does not clearly govern autonomous AI systems, leaving liability allocation ambiguous when these systems act beyond their intended scope. Unlike human agents, AI systems lack independent legal status, forcing courts to apply existing doctrines—attribution, apparent authority, negligence, and product liability—in unprecedented ways. At least one jurisdiction has already moved forward. In Moffatt v. Air Canada, British Columbia courts held a company liable for inaccurate statements made through an AI chatbot, signaling that courts are beginning to assign responsibility despite the legal framework's uncertainty.

A National Law Review contributor published practical guidance on April 28, 2026, for managing AI-assisted contract negotiations with counterparties. The article recommends four core strategies: asking counterparties directly whether they are using AI tools, providing detailed context to improve AI-generated outputs, anticipating how AI systems will respond to specific proposals, and reframing negotiations around shared objectives rather than adversarial positioning. The piece reflects a market shift toward AI-powered contract platforms—including tools from Clio, Ironclad, Bind, and GC.ai—that automate redlining, clause comparison, and deviation tracking. These systems have reduced contract review cycles from 30 to 90 minutes per round to seconds, with firms reporting 30 to 50 percent faster negotiations overall.