Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now
Here’s an analogy: Freeways didn’t exist in the U.S. until after 1956, when envisioned by President Dwight D. Eisenhower’s administration — yet super fast, powerful cars like Porsche, BMW, Jaguars, Ferrari and others had been around for decades.
You could say AI is at that same pivot point: While models are becoming increasingly more capable, performant and sophisticated, the critical infrastructure they need to bring about true, real-world innovation has yet to be fully built out.
“All we have done is create some very good engines for a car, and we are getting super excited, as if we have this fully functional highway system in place,” Arun Chandrasekaran, Gartner distinguished VP analyst, told VentureBeat.
This is leading to a plateauing, of sorts, in model capabilities such as OpenAI’s GPT-5: While an important step forward, it only features faint glimmers of truly agentic AI.
AI Scaling Hits Its Limits
Power caps, rising token costs, and inference delays are reshaping enterprise AI. Join our exclusive salon to discover how top teams are:
Turning energy into a strategic advantage
Architecting efficient inference for real throughput gains
Unlocking competitive ROI with sustainable AI systems
Secure your spot to stay ahead: https://bit.ly/4mwGngO
“It is a very capable model, it is a very versatile model, it has made some very good progress in specific domains,” said Chandrasekaran. “But my view is it’s more of an incremental progress, rather than a radical progress or a radical improvement, given all of the high expectations OpenAI has set in the past.”
GPT-5 improves in three key areas
To be clear, OpenAI has made strides with GPT-5, according to Gartner, including in coding tasks and multi-modal capabilities.
Chandrasekaran pointed out that OpenAI has pivoted to make GPT-5 “very good” at coding, clearly sensing gen AI’s enormous opportunity in enterprise software engineering and taking aim at competitor Anthropic’s leadership in that area.
Meanwhile, GPT-5’s progress in modalities beyond text, particularly in speech and images, provides new integration opportunities for enterprises, Chandrasekaran noted.
GPT-5 also does, if subtly, advance AI agent and orchestration design, thanks to improved tool use; the model can call third-party APIs and tools and perform parallel tool calling (handle multiple tasks simultaneously). However, this means enterprise systems must have the capacity to handle concurrent API requests in a single session, Chandrasekaran points out.
Multistep planning in GPT-5 allows more business logic to reside within the model itself, reducing the need for external workflow engines, and its larger context windows (8K for free users, 32K for Plus at $20 per month and 128K for Pro at $200 per month) can “ …