AI Highlights — the whole picture — 2026-09-24 (Thu) Evening News

Within half a day, AI was infiltrating everything from power grid blueprints to corporate bond issuance conditions and access privileges to internal systems, all at the same time. Illinois has created a new Cabinet post dedicated to AI, and in the corporate bond market, AI models are beginning to design the terms of bond issuance itself. Rather than whether or not it will be introduced, the question in every situation is who is monitoring the movement and to what extent.

Safety debates are progressing simultaneously beyond one country and one company

At the United Nations General Assembly, AI experts warned of the security risks associated with increasingly sophisticated systems (Reuters). On the same stage at the United Nations, the CEOs of OpenAI and Anthropic appealed for international cooperation, as Trump reportedly dismissed AI control as a "globalist conspiracy," CNBC reports. Companies' sense of crisis is also reflected in their concrete measures, with OpenAI requesting that its security measures be tested by an independent third party, TradingView reported. Discussions about safety can no longer be based solely on the stance of one company or one government, and we have entered the stage where development companies themselves want external verification.

Institutional developments proceed in parallel at the state and national levels. Illinois has created a new AI-related cabinet-level position to prepare for new risks, The State Journal-Register reports, and New York state's AI safety law is testing how banks rethink their plans for contracting with vendors, PYMNTS.com reports. In terms of cross-border alignment, Canada's AI minister said the country is working "in partnership" with partner countries on AI safety, CityNews Toronto reported. The premise that the safety of AI cannot be guaranteed by one country's regulatory authority or one law alone is being shared by multiple jurisdictions almost simultaneously.

On the other hand, real risks have already materialized before the system can catch up. Ropes & Gray LLP has summarized the lessons learned from Spain's first case of agent-based AI data breach. This is a concrete example of how the more authority an agent-type AI has to autonomously make and execute decisions, the more complex the scope of damage and where responsibility lies in the event of a breach. Researchers also discussed apocalyptic scenarios in which AI could be dangerous to humanity, nbcsandiego.com reported, with discussions ranging from immediate operational risks to long-term existential risks.

The simultaneous accumulation of warnings from the United Nations, institutional arrangements at the state and national level, actual cases of violations, and even apocalyptic considerations shows that safety issues are no longer of a scale that can be resolved at the discretion of specific companies or governments. Uncertainty surrounding this control is beginning to cast a shadow over the calculations of those making the next investment and introduction decisions.

Data center expansion and trade friction run parallel

In the United States, data center plans with a total capacity of 330 GW are being promoted due to the AI boom, and Review Energy reports that this is opening up new investment opportunities in the battery storage field. While the strain on the power grid has been pointed out, Fierce Network argues that AI data centers can achieve more computing without increasing power, and the future focus will be on the extent to which improvements in computational efficiency can offset growth in power demand. Broadband Breakfast reports that climate week discussions also focused on how to balance hopes for clean energy with uncertainties surrounding AI, leaving investors and local governments with no choice but to simultaneously attract data centers and secure renewable energy sources. Data Center Frontier introduces ways to involve local communities in planning AI data centers before the project actually arrives, with advance coordination around power, land, and employment becoming a prerequisite for breaking ground.

Meanwhile, a reader submission published in the Los Angeles Times argues that the only way to slow the expansion of AI is to stop building power plants and data centers, highlighting the fact that environmental concerns are emerging as an argument against infrastructure expansion itself. As construction and power sources continue to advance, trade frictions are also increasing. According to WSJ, President Trump raised tariffs, AI, and energy as major issues in his UN speech and talks with China. New tariffs and export bans based on Section 338 of the Trade Expansion Act and Russia sanctions are being accelerated as customs authorities step up AI-enabled enforcement, according to an analysis by EXPD and TradingView.

Additionally, The Hill reported that senior Senate Democrats said President Trump had failed to prevent China from accessing U.S. AI technology. While billions of dollars in investments in data centers and storage batteries are moving toward construction after consensus-building with local communities, criticism is being raised that the technology infrastructure itself is leaking out of the region, bypassing tariffs and export controls. The gap between the speed of infrastructure construction and the effectiveness of border control of technology and capital leads to the question of which actors are in control of AI.

Competition in model functionality is directly linked to investors' pricing

In September, Amazon announced that it had enhanced its Seller Assistant for merchants and added new plugins for Amazon Quick and Anthropic's Claude (About Amazon). In the same month, Yahoo Finance featured two notable stocks as the "Claude AI September Portfolio," showing that the spread of Anthropic collaboration is becoming a factor in investment decisions (Yahoo Finance). Meanwhile, Airbnb Newsroom reports that OpenAI has extended access to its cutting-edge models, including GPT-6 Astra, to Airbnb, suggesting that the main battleground for model deployment is shifting to actual operation of individual apps. OpenAI is developing new capabilities to counter Elon Musk's Grok bot and is considering support for Meta's Muse, according to The Information. In terms of capabilities, Futurism reports that an OpenAI agent has solved one of mathematics' most difficult problems, but its "proof" remains largely arcane and incomprehensible to mathematicians, an example of how performance gains are leaving verifiability behind.

Each of these functional competitions is not simply seen as positive news in the stock market. WSJ reported that U.S. stocks have fallen due to concerns about AI companies, and the focus is on whether the Federal Reserve will slam on the brakes (WSJ). MarketWatch op-ed points out that Wall Street and AI have ruined investors' "diversified" portfolios and warns of the risks of concentrated investing (MarketWatch). Benzinga reported that Intuit's stock price fell due to uncertainty surrounding its AI collaboration with Meta, providing an example of how a partnership announcement itself is not a sure-fire driver for a rally.(Benzinga)

In other words, Amazon's new plug-in, GPT-6's rollout of GPT-6 on Airbnb, functionality to counter Grok and Muse, mathematical proofs that should have been solved -- these are a series of advances in terms of functionality, but investors are starting to price each of them based on who is in control and how verifiable they are. This tension, which began to diverge between the flashy functions and market evaluations, led to questions about how security and trade controls should be factored into investment decisions.

Funds and rails are concentrated in the agent economic zone

AI has begun to enter the center of issuance in the corporate bond market. It is reported that the information asymmetry between issuers and underwriters is fading as AI models are increasingly used to design bond issuance conditions and match investors with investors (ai-cio.com). In the same trend, movements on the payment side also overlapped. PayPal announced its participation in the ``Muse Checkout'' ecosystem operated by Meta, and indicated that it plans to expand ``agent-style shopping,'' in which AI completes the process from selection to purchase, to its entire merchant network (Yahoo Finance). Business process automation company Creatio has reportedly raised $300 million in funding to expand the adoption of agent-based AI (fintechfutures.com), and AI startup Heidi has doubled its valuation to $900 million with a new funding round (bloomberg.com). From corporate bond issuance to payment network restructuring to startup valuations, capital movements of different sizes and characteristics are concentrated in the same few weeks.

Although these seem to be separate funding news, what they have in common is that the infrastructure has been reconfigured on the premise that ``the agent will become the main body of the transaction.'' Webajans.com reports that AI agents themselves are becoming the "first visitors" to websites as payment giants rush to create new payment rails for agent commerce (USA Today). We are already beginning to see a trend in retail settings where agents access pages before human viewers, read price, inventory, and payment terms, and then place orders. The Coastland Times has sorted out the lineup of major platforms and providers responsible for agent payments by 2026, and envisions a situation in which established players such as PayPal and Creatio and emerging startups will compete on the same playing field.

Automatic issuance of corporate bonds, integration of payments into member store networks, hundreds of millions of dollars in procurement, and the proliferation of specialized platforms—all of these things are accumulating at the same time, and the agent economy is moving beyond the experimental stage and into a platform that moves actual capital and transactions. The next question to be asked is who controls these rails and to what extent.

Reorganization of authority and evaluation axis within the implementing company

In September, MeshIQ announced a new product called AgentIQ (Pulse 2.0) that provides real-time governance and control for AI agents running within enterprises. As the number of situations in which agents access internal systems and proceed with processing without human approval is increasing, a platform that visualizes who has given what authority and to what extent and detects deviations is starting to take on independent meaning as a product. At the same time, HPCwire points out that as the promise of automation comes closer to reality, the question of how much human oversight should remain is emerging as a design challenge for adopters. Cybersecurity Insiders also argues that AI agents can play a role in raising the level of an organization's cybersecurity system itself, creating a dual position in which agents who were once the subject of control also become the bearers of control.

As implementation progresses, companies' internal operations themselves are being reorganized. inc.com reports that the introduction of AI agents will make it possible to restructure employee allocation, and that management decisions are becoming focused on how to reallocate personnel after transferring some of the work that was previously performed by humans to agents. In retail, Logile has added agent-based AI to its products to help retailers predict employee demand months in advance, citybiz reported. By involving agents in the on-site work of personnel planning, the decision-making cycle for staffing and hiring may be sped up.

Similar movements are taking shape in the financial field. Kastle has raised $24 million to build AI agents for credit decisions, according to Finextra Research. The move to incorporate agents into loan screening, an area with heavy regulations and accountability, shows that the design of authority and the delineation of supervisory responsibilities are directly linked to investment decisions themselves. In light of these trends, InfotechLead reports that AI, automation, and data-driven investments will be prioritized as technologies that will provide the highest ROI for CIOs in 2026, and BizTech Magazine provides examples of how some companies are creating AI advantages for themselves.

In this way, companies that have adopted AI are working on establishing new governance infrastructure, reallocating personnel, designing oversight, and prioritizing investments at the same time, and the center of decision-making is shifting from ``what to let AI do'' to ``who should manage its authority and evaluation axis, and how.''

Power, capital, payments, internal authority—even though the stages were different, the same line was moving. AI is taking over the role of implementing it, and humans are being pushed to the side of monitoring it. The reason why the debate over safety has spread beyond the boundaries of a single company or country is precisely because the difference in speed between control and implementation has become visible to everyone. Funds and trust will only flow to places where it is clear who is in control.

Q1: Is it possible to verify AI decisions made without approval later? Q2: Who knows at this moment the scope of authority granted to agents? Q3: Is it okay to allocate more capital to implementation plans that cannot be accounted for?

Finally, three questions

- Is it possible to verify AI decisions made without approval later? Q2: Who knows at this moment the scope of authority granted to agents? Q3: Is it okay to allocate more capital to implementation plans that cannot be accounted for? - Who knows at this moment the scope of authority granted to the agent? Q3: Is it okay to allocate more capital to implementation plans that cannot be accounted for? - Can we allocate more capital to implementation projects that cannot be accounted for?