Opera contested the European Commission's decision, claiming it was wrong not to classify Microsoft as a gatekeeper for its Edge browser platform service under the Digital Markets Act (DMA). The legal challenge was unsuccessful, confirming Microsoft's position in the regulatory framework.

US District Court Judge Leonie Brinkema rejected the Justice Department's request to force Google to divest portions of its advertising technology business. Instead, she favored less severe measures designed to restore competition in markets where Google was found to have maintained an illegal monopoly for years. Judge Brinkema indicated she would incorporate most of the behavioral changes suggested by the involved parties, with some adjustments. Details of these changes remain confidential until the parties finalize revisions and remove any sensitive information. Proposed measures might include restrictions on Google's self-preferencing practices in ad auctions and allowing third-party participation.

The Federal Trade Commission and 22 states have filed a lawsuit against Amazon, accusing the company of imposing undisclosed extra charges on businesses for advertising services. The lawsuit claims that Amazon ran a covert surcharge scheme that increased costs for sellers without transparent communication.

OpenAI announced that ChatGPT Ads has surpassed $1 billion in annualized revenue within just 200 days. The platform now supports self-service ad buying across Europe, India, the Middle East, and North Africa. Concurrently, the European Commission has classified ChatGPT as a Very Large Online Search Engine under the new Digital Services Act, impacting its regulatory framework and responsibilities across these regions.

ChatGPT, Roblox, and Reddit must adhere to the EU's strictest Digital Services Act rules within four months or face fines amounting to up to 6% of their global revenue.

Following a two-year investigation by the U.S. Department of Justice into TikTok's handling of children's data, the company has agreed to pay $400 million to settle claims of violating the Children’s Online Privacy Protection Act.

OpenAI, which had earlier opposed California's AI safety bill SB 53, is now advocating for the state to enhance the legislation to better address AI safety concerns.

For the past two years, the prevailing belief in enterprise AI was that greater autonomy meant better performance. The idea was to build agents that could independently plan, decide, and act across multi-step workflows with minimal restrictions. However, in real-world production settings, this approach is proving problematic. Successful companies are now focusing on creating AI agents with clearly defined responsibilities that operate within strict rules.

Recent forecasts reveal that over 40% of agentic AI projects may fail by 2028, not due to AI capability but because of rising costs, unclear business value, and insufficient risk controls. Governance maturity in responsible AI remains low, with only about 30% of organizations achieving advanced control measures. This gap between AI capability and governance is reshaping the competitive landscape: the priority has shifted from deploying the most autonomous agent to building trustworthy systems that satisfy risk, compliance, and legal teams.

Full autonomy often breaks down in production because autonomous decisions are hard to trace and audit, especially in regulated environments like finance or healthcare. Integration complexity arises when legacy workflows must be rebuilt to accommodate AI agents acting without human input. Enterprises that dive into this without a comprehensive governance strategy tend to stall or cancel projects.

Leading enterprises adopt four key governance patterns: narrow-scope agents instead of broad ones, human checkpoints before critical decisions, built-in decision traceability, and active data sovereignty to limit risk exposure. This approach balances autonomy with accountability and reduces the risk of costly errors or compliance breaches.

A practical framework for evaluating AI agents involves asking whether action decisions can be reconstructed, agents have bounded responsibilities, checkpoints exist before decisions execute, and data access is properly contained. This framework helps businesses scale AI with calibrated control rather than unchecked autonomy.

Ultimately, the companies that win with agentic AI by 2027 will be those that earn the trust of legal and compliance teams through disciplined governance embedded from the start. It’s not about maximum autonomy but smart orchestration of agents with clear oversight and accountability.

AI companies are caught in an expanding debate over control of what their systems can say, spotlighted by a little-noticed Federal Trade Commission (FTC) draft policy. This proposal has sparked over 300 public comments revealing widespread concern over government oversight of AI-generated speech, particularly regarding ideological bias and equity claims. Interestingly, many comments focus on the influence of China — seen as a threat, a benchmark for regulation, and a point of contention about censorship.

Groups from various sectors warned that the FTC's policy could become a tool for controlling AI speech, with critics across the political spectrum opposing it. Meanwhile, China’s stringent AI content controls serve as a contrasting backdrop, raising questions about how U.S. policy should respond. Chinese AI regulations emphasize cultural protection and political censorship, setting a global standard that impacts international users.

The debate underscores the tension between protecting free expression and managing AI content responsibly. Experts argue that while the FTC’s approach differs fundamentally from China’s censorship model, careful policy design is needed to avoid stifling speech. The discussion also highlights how geopolitical rivalry drives U.S. AI policy, with a focus on competing with China while maintaining American values and freedoms.

In essence, the clash over AI speech regulation reflects broader concerns about power, influence, and values shaping technology globally.

With new laws emerging rapidly, creating a complex legal landscape, the IAB is working to set a clear industry standard for AI disclosures in advertising. However, the practical aspects of applying these standards are still unclear.