(IBM)

However, the nature of these jobs is shifting. LaMoreaux personally revised the job descriptions to deemphasize tasks AI can automate—such as coding—and focus more on people-centric areas like customer engagement. The strategy is aimed at building a pipeline of future senior talent.

IBM has not disclosed specific hiring numbers. An MIT study suggests that 11.7% of current jobs could already be automated by AI, and investors believe 2026 may be the year when AI’s true impact on the labor market becomes evident.

Roger Luo said:Rather than fearing AI-driven displacement, IBM redefines roles to harness technological shifts—offering a forward-looking talent strategy for large enterprises.

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(Amazon)

Previously, companies like OpenAI have entered into individual licensing agreements with media organizations such as the Associated Press and News Corp, but these have not fully resolved legal risks. Numerous lawsuits regarding the use of copyrighted materials in AI models are still ongoing. Meanwhile, AI-powered summary features in search engines like Google have raised concerns among media publishers about declining website traffic.

The establishment of a licensing marketplace is seen as a viable solution to these challenges. If implemented, such a centralized platform could offer the AI industry a clearer and more sustainable pathway to accessing content while helping publishers explore new business models in the age of artificial intelligence. However, the specific operational mechanisms and market response remain to be seen.

Roger Luo said:This move transforms the copyright game into a market mechanism, which is expected to build a clearer AI data ecosystem. However, core issues such as pricing power and ownership definition still need to be resolved, and the actual effectiveness depends on the depth of multi-party cooperation.

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(workday larger)

Eschenbach joined Workday at the end of 2022, initially serving as co-CEO alongside Bhusri, and took sole responsibility for the company’s operations in February this year. Bhusri, who had held leadership roles since the company’s founding in 2009, had previously transitioned to executive chairman.

The core reason for this personnel adjustment points directly to AI transformation. Bhusri emphasized in a statement: “AI is a more significant technological shift than SaaS and will determine the next generation of market leaders. I am returning with renewed energy and will work with the management team to seize this historic opportunity.” This strategic shift was foreshadowed—in February last year, the company laid off 8.5% of its workforce (approximately 1,750 employees). Eschenbach noted at the time that “the AI era requires a completely new approach to human resource allocation.”

Analysts believe that the founder’s return at this time signals that Workday is elevating AI to a core strategic level crucial to the company’s future development.

Roger Luo said:The founder’s return directly drives the strategic upgrade towards AI, signaling that the enterprise software market has reached an inflection point of intelligent transformation. This leadership adjustment represents both a decisive move in response to technological change and underscores the industry consensus among leaders that AI is reshaping business models.

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(Google CEO)

The underlying logic is that high-end computing will become a scarce future resource, and only those who build their own supply chains will survive. However, the market has reacted strongly—every company announcing huge spending has seen its stock price drop immediately, with higher investments correlating to steeper declines.

This is not just a problem for companies without a clear AI strategy (like Meta). Even firms with mature cloud businesses and clear monetization paths, such as Microsoft and Amazon, are facing pressure. Expenditures reaching hundreds of billions of dollars are testing investor patience.

While Wall Street’s nervousness may not alter the tech giants’ strategic direction, they will increasingly need to downplay the true cost of their AI ambitions. Behind this computing power contest lies the ultimate between technological innovation and capital’s patience.

Roger Luo said:The current AI computing power race has transcended mere technology, evolving into a capital-intensive strategic game. While giants are betting that computing power equals dominance, they must guard against the potential pitfalls of heavy-asset models—capital efficiency traps and innovation stagnation.

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(Ilan_Zerbib)

As an Accel partner noted, every API call or SMS sent is essentially a payment, yet current AI agents lack a seamless way to handle these transactions. Sapiom aims to fully automate processes like authentication and micro-payments for services such as Twilio, freeing developers from manually managing tasks like credit card linking.

The company has raised $15 million in seed funding. While its initial focus is on enterprise solutions, the technology could later extend to consumer scenarios like personal AI assistants making purchases. Zerbib believes AI won’t inherently drive more spending, which is why Sapiom is prioritizing solving payment bottlenecks in business service procurement first.、

Roger Luo said:The project precisely targets the infrastructure gap in AI agent payments with a clear enterprise focus. Establishing moats in compliance and ecosystem integration could position it as a critical middleware layer for AI service transactions.

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