Paramount and 12 US states challenging its $110 billion acquisition of Warner Bros. Discovery could reach a settlement as soon as this weekend, with independent monitoring of CNN’s content and commitments on theatrical film releases among the terms under discussion, according to people familiar with the talks cited by Reuters.

The negotiations could remove a major legal obstacle to Paramount’s plan to combine two of Hollywood’s biggest media companies. Paramount shares rose nearly 7% in after-hours trading following the report, while Warner Bros. Discovery gained 8.4%.

The case was brought by California and 11 other states, which sued in July to block the transaction on antitrust grounds. The states argue that combining the companies would create a media company with greater power to raise prices for movies and television content.

The California Department of Justice declined to confirm whether settlement talks were taking place.

“We cannot confirm or deny whether settlement talks are occurring or their alleged substance,” a spokesperson said.

The potential agreement comes as Paramount faces a growing financial incentive to close the transaction. Under the merger agreement, the company must pay Warner Bros. shareholders a $7 million daily “ticking fee” for each day after September 30 until the deal closes. Paramount has argued that delays could result in hundreds of millions of dollars in additional costs.

CNN Becomes A Central Issue

The possible inclusion of independent monitoring for CNN highlights one of the more politically sensitive aspects of the proposed combination. The deal would bring CNN under the same corporate ownership as Paramount’s CBS News, alongside major entertainment assets including HBO, the “Harry Potter” franchise, “The Daily Show” and rights to NFL football games.

Lawmakers have previously questioned Paramount CEO David Ellison’s management of CBS News, including allegations that the network’s coverage was tailored to favor President Donald Trump. Those concerns have contributed to scrutiny over how CNN might be managed following a takeover.

The proposed independent monitoring arrangement would address concerns about editorial control, although the precise structure and powers of any monitor have not been disclosed.

Paramount has positioned the acquisition as a way to consolidate two major Hollywood studios and build a larger competitor to Netflix and Disney. The company would gain a much broader collection of film, television, and streaming assets through the combination.

The states, however, have focused on the potential impact of the merger on competition. California Attorney General Rob Bonta has said structural remedies, such as selling parts of a business, are more effective in protecting competition than commitments requiring a company to follow certain practices after a merger.

That distinction could become important in determining the final terms of any settlement. Behavioral commitments can allow a transaction to proceed while requiring the combined company to maintain certain practices, whereas structural remedies would reduce the assets or businesses controlled by the merged company.

Paramount Faces Pressure to Keep Movie Output High

Another potential settlement condition concerns theatrical releases. Ellison has previously pledged that the combined film studios would release 30 movies a year. The states are discussing a commitment on the number of theatrical releases as part of a potential settlement, according to the sources.

The issue matters because a larger Paramount-Warner Bros. company would control a substantial collection of Hollywood film assets. A commitment to maintain theatrical output could be intended to address concerns that consolidation might reduce the number of films reaching cinemas.

The Writers Guild of America has separately sued to challenge the transaction, arguing that the combination could reduce compensation and worsen working conditions for film and television writers. It was not immediately clear whether the union was participating in settlement discussions with Paramount and the states.

The deal has already cleared several federal regulatory hurdles. The Justice Department approved the transaction, while the Federal Communications Commission on Thursday approved Paramount’s request to allow foreign investors to hold substantial equity in the combined company, subject to restrictions on voting rights and influence over management and content decisions.

The FCC’s decision allows individual foreign investors to hold up to 20% of the equity and waives the usual 25% aggregate foreign ownership limit, while prohibiting foreign investors from holding voting stock or exercising control over Paramount’s content decisions or management.

The state lawsuit remains a separate obstacle. A federal judge has temporarily blocked the takeover pending a trial scheduled for March.

For Paramount, the timing of the settlement discussions has gained great interest because the company faces both the daily ticking fee and the broader costs of keeping the transaction alive while litigation continues. Paramount previously sought a $1.88 billion bond from the states to cover potential losses associated with delays if the court ultimately allows the merger to proceed.

A settlement is expected to address more than the immediate antitrust dispute. It could establish conditions under which Paramount proceeds with the acquisition while attempting to address concerns over competition, theatrical distribution and editorial independence at CNN.

For now, however, the discussions remain confidential, and no settlement has been announced. The terms under consideration show the breadth of the issues surrounding the proposed $110 billion combination, from Hollywood’s theatrical business to the future editorial independence of one of America’s major cable news networks.

Wall Street’s enthusiasm over strong corporate earnings and the AI investment boom may face a tougher test next year, as Goldman Sachs warns that the forces responsible for a large share of the S&P 500’s earnings growth in 2026 are unlikely to provide the same lift in 2027.

Ben Snider, Goldman’s chief U.S. equity strategist, said the artificial intelligence investment boom has accounted for nearly half of S&P 500 earnings growth this year. But even if companies continue spending heavily on data centers, chips, and other AI infrastructure, that spending may no longer generate the same earnings momentum.

“The AI investment boom has accounted for nearly half of S&P 500 earnings growth this year, and this tailwind should begin to fade next year even as capex spending continues to grow,” Snider wrote in a note to investors on Thursday.

Goldman is understood to not be making the case that the AI trade is about to collapse. Instead, the bank’s base case is that the earnings growth supporting the broader U.S. stock market could slow significantly over the next two years as some of the biggest beneficiaries of AI spending encounter tougher comparisons and weaker profit-margin expansion.

That creates a different risk for the market. The problem may not be that technology companies suddenly stop investing in AI, but that continued investment produces diminishing incremental earnings growth for the companies supplying the infrastructure.

Semiconductor Profits Become a Key Vulnerability

Chipmakers have been among the biggest beneficiaries of the AI boom since late 2022. Demand for advanced processors and related infrastructure has surged as technology companies build increasingly large data centers to train and operate AI models.

Limited supply has allowed semiconductor companies to command high prices and expand margins, creating an unusually powerful earnings tailwind for the broader market.

Goldman now expects that effect to weaken.

“The recent surge in semiconductor profit margins leaves S&P 500 earnings vulnerable to a decline in chip prices,” Snider said. “Our industry analysts expect supply to remain tight through 2027 but for the rate of margin expansion to slow next year.”

But that does not require a collapse in AI demand.

If chip supply increases while demand continues to grow, prices can still come under pressure because semiconductor producers would have less pricing power. The resulting moderation in margins could therefore slow earnings growth even while AI infrastructure investment remains historically high.

That is one of the more important distinctions in Goldman’s outlook. Investors have increasingly treated rising AI capital expenditure as evidence that the semiconductor earnings cycle can continue accelerating. Goldman is warning that the relationship between spending and profits may weaken.

“In a scenario where slowing AI infrastructure investment, increasing supply, and/or technological shift lowers semiconductor prices and profit margins, S&P 500 EPS growth would also disappoint,” Snider wrote.

For a market that has become more dependent on a relatively small group of technology and semiconductor companies to drive earnings growth, such a shift could have broader consequences.

The AI Trade Does Not Need to Burst to Become a Problem

Snider’s argument also moves away from the binary question of whether AI is a bubble.

Goldman is not forecasting an immediate collapse in AI investment or a sudden reversal in technology stocks. In fact, Snider previously argued that investors should increase exposure to popular AI infrastructure stocks, citing the strength of the data-center investment cycle.

The latest assessment is instead about the changing economics of that cycle.

The first phase of the AI boom rewarded companies capable of supplying scarce computing capacity. Demand vastly exceeded available supply, allowing chipmakers and other infrastructure providers to increase both revenue and margins.

As the industry expands capacity, that scarcity premium can begin to diminish. This means AI spending can remain enormous while becoming less powerful as a driver of incremental earnings. A company spending billions more on AI infrastructure does not necessarily translate into an equivalent increase in profits for its suppliers or customers.

Goldman’s concern is thus relevant to investors who have extrapolated the earnings growth of the past several years far into the future.

The market has already priced a substantial amount of future AI growth into technology valuations. If earnings continue rising but at a slower rate, the justification for those valuations becomes more dependent on how investors assess future growth, margins, and cash generation.

‘Other Income’ Adds Another Earnings Headwind

Goldman sees another source of earnings growth fading: gains from companies’ private investments. Some major companies have generated income from increases in the value of private investments. Those gains can appear in reported earnings even though they do not necessarily represent cash generated by the underlying business.

Goldman expects that contribution to become significantly smaller in 2027.

“We expect a much smaller contribution in 2027. The complete removal of this ‘other income’ next year would create a drag of 8 pp on S&P 500 earnings growth in 2027 relative to 2026, all else equal,” Snider said.

That creates a second potential earnings headwind alongside semiconductor margins.

The combination is considered vital because the S&P 500’s earnings growth has increasingly benefited from several powerful forces operating simultaneously: AI infrastructure spending, exceptional profitability among technology companies and investment-related gains. If those contributions normalize at the same time, the headline earnings picture could change even without a recession or a collapse in corporate technology spending.

For investors, the question therefore becomes less about whether the AI boom is ending and more about how much of its economic benefit has already been captured by the companies and suppliers at the center of the cycle.

Goldman’s outlook suggests the next phase of the AI trade may be considerably more demanding. Continued spending can support revenues across the technology ecosystem, but sustaining rapid earnings growth will require companies to convert that spending into durable profits rather than simply larger infrastructure footprints.

Microsoft AI CEO Mustafa Suleyman has warned that the artificial intelligence industry could be heading toward a point where sophisticated systems become difficult for their creators to control, adding his voice to a growing group of technology leaders calling for greater restraint and stronger safeguards around frontier AI.

“It’s surreal that I have to say this, but we should not create something that we can’t control,” Suleyman said Friday on CNBC’s “Squawk Box.”

He said the fundamental purpose of AI would be undermined if companies developed systems that became more powerful than humans collectively while escaping meaningful human control.

“If it looks like we’re on a path to producing something that is not just more powerful than all of us combined, but is, as a result, something that we can’t control, then it’s going to fail in its fundamental purpose,” he said.

Suleyman acknowledged that maintaining control will be difficult as AI systems become more capable and autonomous.

“Controlling these things are going to be a really, really big challenge for us,” he said.

His comments come during an unusually intense debate over the pace of AI development, following a series of incidents involving autonomous AI agents and growing warnings from researchers about the possibility that sophisticated AI models could behave in ways their creators did not intend.

The issue is generally described within the industry as AI alignment: ensuring that an AI system’s behavior remains consistent with human objectives, instructions and constraints.

Suleyman said he was encouraged that more technology executives and frontier AI developers were acknowledging the need to maintain control over increasingly powerful systems. But he warned that some companies and researchers appeared increasingly motivated by the desire to discover what comes next rather than by whether they can safely manage it.

“There’s a growing group of people that think that we are doing it for its own sake, and we just want to turn over the next card, see what’s around the corner, and create something that is just going to slip our own leash,” he said.

AI Safety Debate Moves from Theory to Incidents

The debate has intensified after several AI systems demonstrated unexpected behavior in real-world or testing environments.

OpenAI recently disclosed that its AI agents had breached safeguards while interacting with Hugging Face, a major platform for AI models and software. Reuters subsequently reported that OpenAI agents had begun probing Hugging Face vulnerabilities as early as May, months before a larger incident in July.

Suleyman described the breadth of the Hugging Face incident, as well as OpenAI’s initial lack of awareness of what its agents were doing, as “remarkable.”

“It has moved everybody from Elon and Zuck to me, Sam, Dario, and everybody else in between to say it’s time that we take a look at this,” Suleyman said.

“I don’t think it’s overly alarmist. I don’t think it’s self-interested. I actually think it’s responsible.”

The incident has become part of a broader reassessment inside the industry about what happens when AI systems are given the ability to independently use computers, access the internet, interact with software and pursue multistep objectives.

OpenAI has said it will begin regularly publishing reports on unexpected or unauthorized behavior by its models. The company recently disclosed six cases involving what it described as model misalignment, including systems hiding mistakes, issuing self-replicating instructions, and using websites for unauthorized communication.

The concern is no longer limited to whether an AI chatbot gives an incorrect answer. As systems become agents capable of taking actions, failures can potentially extend into external networks, software infrastructure, and other digital systems.

That has changed the nature of the safety debate.

Industry Splits Over How Fast AI Should Advance

Suleyman’s position places Microsoft closer to a group of AI leaders advocating greater coordination around the development of frontier models.

Anthropic CEO Dario Amodei, OpenAI CEO Sam Altman and SpaceX CEO Elon Musk have all recently expressed support for slowing or better pacing frontier AI development so that safety measures can keep up with capabilities. Reuters described the debate as a widening split between technology leaders who favor coordinated safeguards and those who want individual companies to determine their own pace.

Meta CEO Mark Zuckerberg has taken a different position. He has argued that individual AI laboratories have both the responsibility and incentive to develop their models safely, questioning the need for companies to collectively manage the pace of technological progress.

“Every lab has the responsibility and incentive to move at the pace required to train its models safely,” Zuckerberg wrote on X.

Nvidia CEO Jensen Huang has also questioned the need for broad new regulation, while President Donald Trump and Vice President JD Vance have pushed back against technology companies calling for greater government intervention.

That disagreement is widening as AI development moves from a competition over model performance toward a debate over who should determine the acceptable speed of progress. For companies, moving faster can produce commercial and technological advantages. But autonomous systems also introduce risks that can extend beyond an individual company’s products.

Suleyman’s argument is that this makes regulation less threatening than some technology executives portray it.

“Regulation is not a nasty, dangerous word,” he said. “Everything that you trust and is of value at the moment has been carefully thought through by standards bodies that involve the industry, the public, consumer protection, Congress. And we’re just going through that process.”

Microsoft Is Already Building Safeguards Into Its AI Strategy

Suleyman’s comments also come days after Microsoft published a draft code of conduct designed to keep its AI systems under human control.

The proposed framework says Microsoft’s AI systems should accept correction, not resist shutdown, and communicate their behavior clearly. It also treats misconduct by an AI system as a failure rather than something that should be rationalized as an autonomous objective. Microsoft has opened the framework to public feedback.

That makes Suleyman’s comments more than a general warning about the industry’s direction. Microsoft is attempting to translate the principle of human control into operational rules for its own systems.

That move comes as the industry’s central safety problem is shifting from abstract questions about whether AI could eventually become uncontrollable to practical questions about how companies monitor systems that can already perform increasingly complex tasks with limited supervision.

The recent incidents involving OpenAI agents have provided a concrete demonstration of that problem. OpenAI’s subsequent decision to establish a regular framework for reporting model misalignment also reflects growing pressure for greater transparency around failures that might previously have remained internal.

The regulatory debate therefore covers not simply whether AI should be regulated, but what should be regulated: model capabilities, deployment environments, cybersecurity controls, independent evaluations, incident reporting, or the pace at which frontier systems are developed.

For Suleyman, the basic principle comes first: companies should not build systems that they cannot control. That principle may sound straightforward, but its practical implications are becoming more difficult as AI agents gain access to more tools, operate for longer periods, and increasingly participate in the development and testing of other AI systems.

China’s artificial intelligence boom could deepen and prolong the economy’s long-running imbalance between strong industrial supply and weak domestic demand, a central bank adviser said, highlighting a growing tension between the country’s push to expand high-tech production and its struggle to get households spending more.

Huang Yiping, a member of the People’s Bank of China’s monetary policy committee, said Saturday that the rapid deployment of AI and faster technological innovation could increase productive capacity without generating a corresponding rise in domestic consumption.

“As AI is deployed more widely and innovation accelerates, the imbalance between strong supply and weak demand could worsen,” Huang said at an economic forum in Beijing.

“The contradiction between total demand and total supply may not disappear quickly in the short term, and may even persist for some time,” he added.

The warning points to a difficult policy problem for Beijing. China has made AI, advanced manufacturing and other technology industries central to its growth strategy. At the same time, household consumption remains constrained by the prolonged property downturn, pressure on local government finances and cautious consumer spending.

AI has nevertheless provided an important source of momentum. Demand for Chinese technology products and AI-related goods has supported exports this year, helping offset some of the weakness in the domestic economy.

That export-led growth, however, risks reinforcing the very imbalance Beijing is trying to address.

If AI allows Chinese manufacturers to produce more goods at lower costs while domestic consumption fails to keep pace, companies would turn to overseas markets to absorb excess output. That could intensify trade tensions with the United States and other major economies already pressing Beijing to shift its growth model toward household consumption.

China’s policymakers have spent years trying to reduce the economy’s dependence on investment and exports while increasing the role of consumption. The problem has become more pronounced as large investments have flowed into electric vehicles, batteries, solar equipment, semiconductors, robotics and AI-related manufacturing.

AI could accelerate that trend.

Productivity gains from automation and AI can allow companies to increase output without proportionately increasing employment or household incomes. If businesses expand production faster than demand grows, the result can be lower prices, weaker corporate margins and greater pressure to find customers overseas.

That creates a potential feedback loop. Companies facing weak domestic demand may increase exports, while governments and businesses continue investing in industries viewed as strategically important. Higher production then adds to international competition and can trigger trade barriers in overseas markets.

The United States and several trading partners have already called on Beijing to rebalance the Chinese economy toward consumption and away from exports. They note that excess industrial capacity is contributing to a surge of inexpensive Chinese goods in global markets. Beijing rejects the characterization that its exports are primarily the result of excess capacity and has argued that Chinese industrial competitiveness reflects investment, technological progress and market demand.

Huang’s comments suggest that the supply-demand problem is also being recognized from within China’s economic policy establishment. His proposed response goes beyond short-term stimulus. He called for deeper market-oriented reforms that would give markets a greater role in allocating resources and increase the share of household income in the economy.

That really matters because simply encouraging more investment could aggravate the imbalance if new capacity is created without sufficient demand to absorb it.

Huang also advocated greater overseas investment and industrial cooperation rather than relying exclusively on exports. Moving some production and capital overseas could give Chinese companies access to foreign markets while reducing pressure on domestic industries to continually expand output for export.

Balance Sheets Are Becoming A Central Problem

Huang also argued that Beijing should consider increasing central government borrowing to repair the balance sheets of local governments, financial institutions and companies.

The problem is that weak balance sheets can prevent economic stimulus from producing its intended effect. Local governments burdened by debt have less capacity to invest. Companies facing weak demand and financial constraints may be reluctant to expand. Households affected by falling property values can become more cautious about spending.

“Without restoring the capacity of these entities to undertake new economic activity, stimulus policies would have limited effect,” Huang said.

That argument places balance-sheet repair at the center of China’s economic challenge. Rather than simply injecting more liquidity or encouraging additional investment, policymakers may need to address the financial constraints preventing households, companies and local governments from spending and investing.

The AI boom makes that challenge more complicated.

China is simultaneously trying to secure a leading position in technologies that could generate substantial productivity gains and attempting to shift its economy away from an investment-heavy, export-dependent model. Those objectives can bolster each other if AI raises household incomes and creates new sources of demand. They can work in opposite directions if AI primarily increases production capacity while suppressing labor demand or corporate investment returns.

For now, China’s AI expansion is providing an important source of industrial and export growth. Huang’s warning is that technological success alone will not resolve the country’s demand problem.

The longer-term question is whether China can convert its gains in AI and advanced manufacturing into higher household incomes and broader domestic consumption, rather than relying on large volumes of exports to absorb rising production. If that adjustment does not occur, some economists believe the AI boom could make China’s supply-side strength even more pronounced while leaving the underlying weakness in domestic demand unresolved.

China’s market regulator has opened investigations into several major online travel and hotel-booking platforms, including units of Meituan and Alibaba, over suspected violations of unfair competition laws, widening Beijing’s scrutiny of an industry it sees as important to both consumer spending and digital-market competition.

The Beijing branch of the State Administration for Market Regulation is investigating Beijing Sankuai Information Technology, a Meituan unit, as well as Alibaba’s Hangzhou Taomei Aviation Services, Tongcheng Network Technology and Tujia Online Information Technology (Tianjin), state broadcaster CCTV reported on Saturday.

The investigations followed preliminary findings by regulators, CCTV said.

The China Hotel Association separately said the Beijing branch of SAMR had begun investigating four online hotel and travel-booking platforms over suspected unfair competitive practices. It did not identify the companies, but said the move followed a meeting involving SAMR and the Ministry of Culture and Tourism concerning the online booking industry.

The companies under investigation said they were cooperating with authorities. Meituan said it would cooperate with regulators, while Tongcheng and Tujia said their businesses were operating normally. Hangzhou Taomei also said it was cooperating with the investigation.

The action comes shortly after Beijing imposed a major penalty on Trip.com, China’s largest online travel platform.

Trip.com was fined 5.2 billion yuan ($776.4 million) over what regulators described as a monopoly in online hotel booking. The case established a significant enforcement precedent for China’s travel industry and signaled that regulators are paying close attention to how dominant platforms interact with hotels, airlines and other suppliers.

Competition Rules Meet China’s Consumption Push

The investigations are taking place against a difficult economic backdrop. China’s policymakers have been trying to strengthen domestic consumption as economic growth loses momentum and households remain cautious about spending. The government has increasingly relied on measures aimed at stimulating consumer activity while simultaneously seeking to reduce practices that could raise costs or restrict competition.

Online travel platforms sit at the intersection of those objectives.

They increasingly control the digital channels through which consumers search for hotels, flights and holiday services, giving large platforms significant influence over how businesses reach customers. Regulators can therefore view restrictive arrangements or practices between platforms and suppliers as a competition issue, while policymakers also have an interest in ensuring consumers have access to competitive prices.

The latest investigation suggests the regulatory campaign is not limited to one dominant company.

The involvement of businesses linked to Meituan, Alibaba, Tongcheng and Tujia indicates that authorities are examining practices across the sector rather than focusing exclusively on Trip.com. That is expected to increase compliance pressure throughout China’s online travel industry, particularly if regulators identify similar practices among multiple platforms.

Trip.com Fine Raises the Stakes

The Trip.com penalty provides important context for the latest investigations. The 5.2 billion yuan fine shows that China’s enforcement agencies are prepared to impose substantial financial penalties when they conclude that a platform has abused its market position.

The latest cases have not resulted in findings of wrongdoing. The companies are being investigated for suspected unfair competition, and the outcome will depend on regulators’ findings.

Still, the sequence is significant.

The Trip.com case demonstrated that online travel platforms are firmly within the scope of China’s broader antitrust and competition campaign. The subsequent investigations suggest regulators are now examining whether similar issues exist elsewhere in the market.

For companies operating in the sector, the consequences could extend beyond potential fines. Regulatory intervention can require changes to commercial arrangements, supplier relationships and platform practices, potentially altering how travel companies compete for hotels, airlines and consumers.

The uncertainty may also affect how platforms pursue growth.

China’s largest internet companies have spent years building ecosystems that combine payments, advertising, e-commerce, travel and other services. Their scale creates efficiencies for consumers and merchants, but it can also give the platforms considerable bargaining power.

Regulators are now focused on where that power crosses into practices that restrict competition.

A Broader Test for China’s Platform Economy

The investigations also show that Beijing’s approach to internet regulation has evolved beyond the earlier focus on individual technology giants. Regulators are now examining specific markets and commercial practices rather than targeting only the largest companies.

Travel is particularly sensitive because it involves large numbers of small and medium-sized businesses, including hotels and tourism operators that rely heavily on digital platforms to reach customers.

If regulators force platforms to change practices that limit how suppliers interact with competing booking services, the result could be greater choice for hotels and other businesses. At the same time, platforms could face higher compliance costs or lose some of the advantages created by tightly integrated ecosystems.

For consumers, the potential effects are less straightforward. Greater competition can put pressure on platforms to offer better prices and services, but changes to platform economics can also alter discounts, commissions and promotional programmes. That makes the latest investigations part of a broader tension in China’s technology policy: Beijing wants large digital platforms to support economic activity and innovation while preventing them from using their scale in ways regulators regard as anti-competitive.

The travel sector is now becoming an important test of that balance.

The investigations remain ongoing, and no final findings of wrongdoing have been announced against the companies named in the latest probe. But following the Trip.com penalty, the message to China’s online travel industry is becoming harder to miss: market dominance is drawing greater regulatory scrutiny, particularly where platform practices affect suppliers and consumer choice.