Half of GenAI Users Now Deploy AI Agents in Daily Operations

Organizations rapidly adopt autonomous AI systems

More than half of companies already using generative AI have moved beyond simple chatbots to deploy AI agents that handle day-to-day business operations, according to a global survey of 3,500 senior executives conducted by Google.

Elit Ben Basat Nuriel, Head of Cloud Marketing at Google Israel, shared the findings during Google and Calcalist's AI Week, describing the shift as "the most dramatic turning point since generative artificial intelligence entered our lives."

The 52% adoption rate among GenAI users signals a fundamental change in how organizations approach automation. Rather than using AI solely for information retrieval, companies are implementing autonomous systems capable of managing entire processes independently.

Why it matters

The rapid progression from chatbots to multi-agent workflows represents a structural change in enterprise operations. Organizations that master agent orchestration will gain significant competitive advantages in speed, cost efficiency, and scale—while those that delay risk falling behind competitors operating at machine speed, particularly in areas like cybersecurity where AI-powered attacks are accelerating.

Three levels of AI maturity

Ben Basat Nuriel outlined a three-tier framework for organizational AI maturity. The first level consists of basic chatbots that retrieve information and perform simple actions. The second tier involves dedicated AI-agent applications focused on specific functions such as customer service or creative work. The third and most advanced level features multi-agent workflows where multiple AI systems communicate with each other to manage complete processes from start to finish.

Some organizations have already reached this third tier. Companies that clearly defined business problems before implementation are seeing positive returns on investment across customer service, sales and marketing, cybersecurity, and technical support.

The impact can be dramatic: sales teams that previously spent three hours preparing for customer meetings can now use AI agents to interface with organizational applications and generate customized presentations in five minutes.

Implementation roadmap for enterprises

Ben Basat Nuriel offered three recommendations for organizations beginning AI agent deployment:

First, leadership must define the business need, understand the technology, determine expected ROI, and allocate dedicated budgets. Strong security protocols are essential to allow agents secure access to enterprise systems while protecting corporate data.

Second, start with repetitive, time-consuming processes rather than attempting to build complete architecture immediately. Creating an agent that delivers immediate results generates momentum and drives adoption across the organization.

Third, establish data governance and security foundations before deployment. Organizations should organize their data infrastructure, implement robust security frameworks, and adopt zero-trust approaches to create a foundation for confident innovation.

The hybrid workforce ahead

Looking three years forward, Ben Basat Nuriel predicts managers will oversee both human employees and AI agents in hybrid workforce models. Every employee will work alongside personal AI agents or networks of agents operating on their behalf.

The most critical skill in this environment will be orchestration—the ability to define context, manage goals, set clear objectives, provide appropriate context, manage guardrails, and apply critical thinking. Human talent becomes more strategic rather than less important, with workers spending less time on manual tasks and more time orchestrating digital systems.

These details were first reported by Calcalist during AI Week.