Google’s recent artificial intelligence (AI) efforts have reportedly calmed fears it was lagging its rivals.

As the Financial Times (FT) reported Sunday (Dec. 22), the tech giant has impressed investors this month with more advanced iterations of its AI models, surpassing competition in benchmark testing. 

The company also introduced a new generation of its custom AI accelerator chip — a tensor processing unit (TPU) called Trillium — which is designed to challenge Nvidia’s market dominance, the report added.

In addition, Google’s AI model now includes the ability to act on users’ behalf and compile complex research reports — Project Mariner — and respond to real-time queries across text, video and audio — Project Astra — including using smart glasses. Lastly, it launched video and image generation models called Veo 2 and Imagen 3.

“The last month has transformed the state of AI, with the pace picking up dramatically in just the last week,” said Ethan Mollick, a professor at Wharton business school and author of a book on the technology, characterizing Google’s releases, in particular Veo 2, as “astonishing.”

“This isn’t steady progress — we’re watching AI take uneven leaps past our ability to easily gauge its implications,” Mollick said.

Writing about Google’s latest AI rollouts last week, PYMNTS argued that these developments signal that the system could transform user interactions and task automation. In the business world, these advances suggest possibilities for AI to affect operations ranging from warehouse management to customer service.

“Gemini 2.0 improves on previous AI systems by advancing the capabilities of autonomous decision-making through the integration of more sophisticated AI agents that leverage real-time data processing and adaptive learning models,” Prashant Kelker, chief strategy officer, partner and lead consulting sourcing and transformation – Americas, with global technology research and advisory firm ISG, told PYMNTS.

“As a result, enterprises will need to strengthen the cross-functional alignment between technology, business and compliance teams. As agentic AI goes into production, we are expecting cloud and edge computing capabilities to scale.”

The crucial innovation, that report added, comes from Gemini 2.0’s ability to handle multistep processes with less human oversight. Compared to traditional AI that responds to specific prompts, this system works to autonomously coordinate across platforms, with the potential to manage inventory or processing orders.

“Rather than completely redesigning their eCommerce systems, businesses will likely extend existing accessibility and structured data standards to create an ‘AI-enhanced HTML’ layer that sits between pure visual interfaces and full APIs,” Dev Nag, CEO of QueryPal, a support automation company, told PYMNTS.