OpenAI: US Must Take the Lead in AI
AI development has transformed from a product feature to a strategic location decision. This is evident in briefings, energy papers, and government documents. On January 3, 2026, The Economic Times reported that OpenAI is urging the US to lead in AI development, while Google Cloud sees 2026 as the year of "AI Agents." These developments are closely linked: when agents take over work steps, the use of AI quickly becomes its operation, which in turn requires infrastructure policy.
Source: Own Representation
Greg Brockman writes in his look back at 2025 how "vital" it is for the US to lead in AI. Quelle
AI Leadership and Infrastructure
OpenAI is calling for US leadership in AI development. The Economic Times summarizes Brockman's year-end review from January 1, emphasizing that the US "must" lead in AI. According to Brockman, AI can scale healthcare and make it more affordable, promote scientific thinking, and expand access to education. He highlights that "pro-AI" does not mean "anti-regulation" and that safety issues are included. This aligns with OpenAI's official policy line, which proposes a freedom-oriented policy in its "proposals for the U.S. AI Action Plan" to secure American leadership, promote growth, and protect national security. Quelle, Quelle
The US government explicitly views AI as part of its national strategy. "America's AI Action Plan" frames AI as a global competition and links the claim to leadership with security and prosperity. The Executive Order "Removing Barriers to American Leadership in Artificial Intelligence" directly puts "American leadership" in the title and aims for acceleration rather than hurdles. AI.gov describes the Action Plan as a "roadmap" along innovation, infrastructure, and international security/diplomacy. Quelle, Quelle, Quelle
Source: gruender-mv.de
The development and deployment of advanced AI technologies and platforms are crucial for the global leadership position of the US.
The bottleneck in AI development is not just in models, but also in data center capacity, chips, and energy. In its OSTP submission, OpenAI urges that the US must close an "electron gap" and provide 100 gigawatts of new energy capacity per year. This shifts the debate from a software upgrade to industrial policy. Operating agents at scale requires continuous electricity, hardware, and operational security. Quelle, Quelle
AI Agents: Definition and Potential
Google Cloud predicts that "AI agents will transform the way we work in 2026," linked to productivity, "five-star experiences," security automation, and training. The "2026 AI Agent Trends Report" positions agents as the next stage, moving from point-in-time assistance to workflows that traverse task chains. Google mentions interoperability and the collaboration between Salesforce and Google Cloud on "cross-platform AI agents" with an Agent2Agent protocol. This suggests a potential ecosystem with standards, interfaces, and platform power. Quelle, Quelle
At its core, OpenAI defines agents through "workflows" that connect agents, tools, and control flow (planning, execution, feedback). OpenAI's overview page emphasizes the design of such workflows and the assembly of platform building blocks to reliably achieve goals. Google Cloud describes AI Agents as systems that pursue goals and perform tasks on behalf of users, including planning, reasoning, and tool usage. "Agentic AI" is framed as AI that not only reacts but actively plans and executes steps. A chatbot answers questions, an agent performs work steps and therefore needs to be more closely connected to data, permissions, and processes. Quelle, Quelle, Quelle, Quelle
Source: getahead.de
The integration of AI Agents into work processes promises enormous efficiency gains, but also poses new challenges for leadership and management.
Google Cloud shows concrete effects in its 2026 report: Telus achieves approximately 40 minutes of time savings per AI interaction with over 57,000 employees using AI. Suzano reduced query time by 95% for about 50,000 employees using a Gemini Pro agent that translates natural language questions into SQL. This addresses a bottleneck in many companies by allowing business departments to answer data questions without tickets to data engineering. Danfoss automates email-based ordering processes, reducing response times from 42 hours to "near real time." Macquarie Bank uses AI-based fraud protection for more self-service and fewer false positives. Quelle, Quelle
Providers show where the development is heading: OpenAI describes "ChatGPT agent" as a mode that not only "thinks" but also acts with a toolset, including an "own computer" approach. The help doc for ChatGPT agent mentions capabilities such as website navigation, filling out forms, editing files, and connecting to data sources, with users remaining "in control." Microsoft outlines "autonomous agents" in Copilot Studio as a building block for automating processes. A reference pattern is Microsoft's "document processing agent," which combines extraction, validation, human monitoring, and export. Salesforce frames Agentforce via "data, reasoning, actions," i.e., enterprise data plus actionability through workflows/APIs. Oracle positions "AI Agent Studio" as a tool for creating, deploying, and managing agent (teams) within Fusion Applications. Quelle, Quelle, Quelle, Quelle, Quelle, Quelle
Challenges and Risks
Gartner predicts that over 40% of agentic AI projects could be abandoned by the end of 2027, due to factors including rising costs, unclear business value, or lack of risk controls. Reuters picks up on this forecast and describes "agent washing" – renaming without genuine agentic capabilities – and names Salesforce and Oracle as drivers. Quelle, Quelle
Source: user-added
Donald Trump looks to the right with a serious expression, a red tie in the foreground.
With increasing autonomy, the attack surface grows. Reuters explicitly describes additional risks with AI Agents such as data privacy and security issues, as well as new vectors for misuse. OpenAI itself warns of prompt injection as a persistent problem area in agentic browser/web interactions, especially where agents process unvetted content. Quelle, Quelle
Technologies and Platforms
For technical insights into Google's approach, Vertex is relevant: Agent Builder is the entry point to enterprise agents, and Agent Engine is described as the production layer. OpenAI offers AgentKit and the "agent platform" for orchestration, UI, and evaluation. OpenAI's PDF "A practical guide to building agents" covers use-case selection, orchestration patterns, and security practices. Quelle, Quelle, Quelle, Quelle, Quelle
Further information and demonstrations are available in various YouTube videos:
Source: YouTube
Source: YouTube
Further videos include:
Conclusion and Outlook
OpenAI's demand for US leadership in AI is more than a competitive appeal; it is in the context of a government and industry that view AI as an infrastructure and security project. The narrative of agents for 2026 is not purely product marketing, but rather targets workflows that connect decisions, permissions, and systems. This raises questions about costs, control, and risk. Whether "AI Agents 2026" will truly be a breakthrough depends on governance and ROI, as well as whether agents remain reliable in operation when they not only help but act. Quelle, Quelle, Quelle, Quelle, Quelle, Quelle