From Observer, January 26:
A.I. models are becoming operating systems, agents and economic infrastructure, says Goldman Sachs CIO Marco Argenti. 2026 will be pivotal.
A.I. models are becoming more than just chatbots—an important step in their evolution that will have repercussions for the global economy in 2026 and beyond, says Marco Argenti, Goldman Sachs’ chief information officer.
“In my 40 years in technology, 2025 saw the biggest changes I have seen in my career,” Argenti says. “And what’s crazy is we haven’t seen anything yet—in fact, I predict 2026 will be an even bigger year for change.”
A.I. has emerged as a critical driver for financial markets and potentially for the broader economy. Wall Street analysts, who have consistently underestimated the amount of investment going into A.I., expect the largest hyperscale cloud computing companies to pour more than half a trillion dollars into capital expenditures in 2026. The seven biggest tech companies now account for more than 30 percent of the S&P 500’s market capitalization and roughly one quarter of the index’s earnings, according to Goldman Sachs Research.
Argenti, the former vice president of technology of Amazon Web Services (AWS), says A.I. is rewiring everything from the traditional workforce to the traditional software stack.
He makes seven predictions about how A.I. could evolve in the near future:
A.I. models will be the new operating system
The traditional paradigm for software engineering is changing: Rather than functioning as one-dimensional applications, A.I. models are becoming operating systems that independently access tools in order to perform tasks.In turn, computing is evolving from static, hard-coded logic to outcome-based assistants that reprogram themselves. This makes A.I. agents much more capable of handling complex problems. As a result, those who own the models will own the new operating systems that power A.I. agents.
Context is the new frontier
The rise of the personal agent
A.I. engineers’ focus will shift from building “larger models” to “better memory.” Think of it this way: The models have been built from vast pools of data—they’ve scoured essentially the entire internet and then some in the form of synthetic data for model-training purposes. However, the immediate context available to models—what they remember from previous discussions and tasks—is relatively tiny. Already, some newer models are able to reason and inject much larger contexts into processes to provide far more bespoke, customized responses.
A.I. personal agents will arrive, which is something companies have been chasing with varying degrees of success. What we do now with apps—manually, and in piecemeal fashion—will be done automatically soon. For example, if a flight is cancelled because of the weather, an AI agent will know to rebook the flight, reschedule meetings, and order food for afterwards (since restaurants will be closed). This is very possible with AI with agentic capabilities.
The agent-as-a-service economy.......MUCH MORE
