The strength of Agentspace is helping employees make sense of the digital pile of information within their organization, said Paul Baier, CEO and co-founder of GAI Insights, a GenAI analyst firm.

Google seeks to accomplish two goals with Agentspace: bring better reasoning capabilities and include multimodal capabilities, said Gartner analyst Arun Chandrasekaran.

"[AI] agents need better reasoning," Chandrasekaran said. "Agents need better memory, which is the ability to remember things and contextualize the responses."

Google accomplishes the goal of better reasoning through Gemini and its history with search.

"Search can take advantage of the planning, the reasoning and the memory that agents provide to answer complex questions," Pai said. "Agents are able to ensure that all generated content is grounded in complex enterprise data."

Google establishes multimodality by including built-in multimodal search capabilities across text, video, images and audio in Agentspace. It also allows users to generate audio summaries through the NotebookLM audio feature.

Google's inclusion of a built-in translation feature is also beneficial for users, Chandrasekaran said.

"Google being Google, they're able to support so many more languages than others can," he said. "Thanks to the Android ecosystem, they're also able to train these models well using a lot of that data."

The use cases Google mentioned for Agentspace include a marketer generating content for a new product release or an HR department helping employees onboard faster.

"It's always good to start with kind of more inward, focused use cases," Chandrasekaran said. "Given that agents are super new, and people are concerned about things like 'Oh, I don't want the agents to make a decision without consulting me.'"

Compared with Salesforce Agentforce and Microsoft Agents, Google's Agentspace seeks to help developers create their agents while integrating agents into Google Cloud services, Chandrasekaran continued.