In Spotlight this Week: ChatGPT Agents-The Next Leap in Autonomous AI

This week, OpenAI introduced a significant upgrade inside ChatGPT: agents. These aren’t just smarter chatbots, they’re autonomous digital co-workers that can take action, not just provide answers.

So what are ChatGPT agents? Imagine assigning a task like “find the best flights under $800 and book one,” and the agent goes off to browse, fill out forms, download files, generate spreadsheets, or run code, all independently, securely, and within defined guardrails. It’s a major step beyond prompt and response.

Why does this matter? Until now, most AI systems have been reactive, you ask, it replies. With agents, we step into the realm of proactive AI. Tools that can reason, navigate real-world systems, and deliver outcomes. It’s not just an upgrade, it’s a rethink of how digital work gets done.

For digital and business leaders, this opens up new possibilities:

• Deploying agents across finance, HR, marketing, or data ops
• Freeing teams to focus on higher-order tasks like judgement, design, and decision-making
• Building modular workflows that connect apps, documents, and tools without traditional integrations or code

Are Agents different that Agentic AI? – There’s an important distinction here. “Agentic AI” is the design philosophy, AI that plans, decides, and acts to achieve goals. What OpenAI has now launched is a concrete implementation of that vision. These agents live inside ChatGPT, wired into tools, memory, APIs, and your workspace. This is no longer theory. It’s operational.

This evolution will reshape how we approach AI in the enterprise. It changes how we think about roles, delegation, and execution. We’ll soon be designing teams where agents carry out tasks just like apps once did, only now, with autonomy and context.

---

Noteworthy this week: important developments across the AI and tech landscape

OpenAI has launched a $10M+ AI consulting business, embedding engineering teams inside enterprises to accelerate custom AI deployments. It marks a shift from simply offering access to models, toward driving hands-on business transformation. OpenAI isn’t just a tech vendor anymore, it’s aiming to become a full-stack AI delivery partner.

Google paid $2.4B in licensing fees to Windsurf, an AI coding startup, while simultaneously hiring away its top talent, including the CEO. The company remains technically independent, but gutted of its core team. It’s a striking example of how Big Tech is buying talent and capability without formal acquisitions. Another startup, Cognition, picked up the remainder of the team. Urgency in the AI arms race is clearly reshaping how innovation is scaled, and acquired.

Uber is investing more than $500 million in Lucid and Nuro to deploy a fleet of 20,000 AI-powered robotaxis over the next six years. It’s their biggest move yet toward owning autonomous mobility infrastructure and integrating AI into core transport systems, rather than relying on external platforms.

Meta appointed Shengjia Zhao, co-creator of ChatGPT and former OpenAI scientist, as chief scientist of its new Meta Super-intelligence Labs. Zhao will lead foundational AI research and long-term scaling. It signals Meta’s aggressive ambition to compete at the frontier of AI, with plans to invest hundreds of billions in compute and infrastructure.

Meanwhile, news publishers are facing major disruption from Google’s AI Overviews, which summarise information above traditional search links. Studies show this has led to a 79% drop in traffic for many media outlets. There’s growing concern that the economics of independent journalism may not survive in an AI-first search experience. It’s a reminder that even technically brilliant innovations need to be matched with models that protect context, attribution, and quality.

As always, the real challenge isn’t what the tech can do, it’s what we choose to do with tech.