Google: AI agents, multimodal AI, enterprise search will dominate in 2025


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If 2024 was all about experimentation, 2025 will truly be the year enterprises scale AI, according to a new trends report from Google Cloud out today. 

Notably, sophisticated multimodal AI will support ever more complex tasks, AI agents will be embedded across enterprise, and internal search engines will unlock critical business insights. 

Interestingly, Google identified these trends by using NotebookLM to analyze data from a previous research study, pulled out the fastest-growing AI topics in Google Trends, and plugged in third-party research and insights. 

“Moving forward, you’ll see different agents talking to different agents, almost to the point where we all go to sleep at the end of the evening, and there’s a series of tasks and things and actions that are happening behind the scenes,” Oliver Parker, VP for global generative AI go-to-market at Google Cloud, told VentureBeat.

Enterprises will move from chatbots to multi-agent systems

AI agents are able to work autonomously (or semi-autonomously) and perform  multi-step processes. According to Capgemini, only about 10% of large enterprises are already using AI agents — but 82% plan to integrate them in the next three years. 

Google identifies six types of AI agents: 

  • Customer agents that understand user needs, answer questions, resolve issues and recommend products and services. They work across channels and can integrate voice and video. 
  • Employee agents that help streamline processes, manage repetitive tasks, answer questions and edit and translate. 
  • Creative agents that generate content, images and ideas to support design, marketing and writing projects and other endeavors. 
  • Data agents that can assist with research and data analysis by finding and acting on data (while ensuring factual integrity). 
  • Code agents that support code generation and provide coding assistance. 
  • Security agents that help mitigate attacks or increase the speed of investigations. 

However, Parker pointed out, having many agents taking on many processes across many functions can create a bit of chaos, which will give rise to new platforms, he predicts. 

“Being able to have a single canvas for managing and enabling your agents is where we think there’s going to be a huge opportunity,” he said. This will lead to “agentic governance,” or the need for an agentic layer that supports “different agents that are going everywhere and working across all these different systems.”

Multimodal AI will provide more context

The global multimodal AI market was estimated at $2.4 billion in 2025, and is expected to reach $98.9 billion by the end of 2037. 

Multimodal AI brings AI comprehension to the next level, allowing models to decipher and process a range of data sources including not only text, but images, video and audio. Several leading vendors and cutting-edge startups already offer highly capable multimodal tools — for instance, Google’s own Gemini 2.0 Flash, Mistral’s Pixtral 12B or Cohere’s Embed 3. 

Google predicts that the explosion of multimodal AI will support complex data analysis and lead to greater grounding and more personalized insights. 

Along with this, enterprises will be multi-model as they adopt AI. Parker pointed out that conversations have transitioned from enterprises adopting a single model to deploying many for different use cases. “It’s not just an OpenAI model,” he said. “It’s also Gemini, it’s Anthropic, it’s Mistral, it’s Cohere, it’s Llama.”

It’s been a fast evolution over the past 12 months, Parker noted. Enterprises have moved beyond just looking at models to analyzing different platforms and laying out AI and AI agent roadmaps. While much of the focus to this point has been on development, the goal in 2025 will be getting gen AI capabilities into the hands of enterprise users. 

“The first half of ’24 was heavy, heavy experimentation, but without a lot of production,” said Parker. Now, enterprises are beginning to move into production, although it’s not yet production at scale (more of that will come in 2025). 

“These are typically trends you see over several years,” he said. “We’ve just seen them very compressed over a 12-month period. It’s breathtaking.”

Enterprise search — supported by internal search engines that query specific enterprise data — will only become more intuitive with AI, Google predicts. It will no longer just be keyword-based queries; employees will be able to use images, audio, video and conversational prompts to quickly access internal data. This will allow for more advanced and intuitive searches, Parker pointed out, and gen AI can process different data formats such as documents, spreadsheets and multimedia. 

 “It’s not just search, it’s search plus conversational AI,” said Parker. “People’s jobs are really about finding information and bringing it together to be able to get insights and take actions.”

He noted that many organizations have different information siloed across different applications — whether a coding system, Jira, Confluence, Box, or platforms like SharePoint or Service Now.

AI search can quickly move across these to bring data together. “These systems of reasoning are able to search across enterprise systems,” he said. “So how do you query and find out what’s happening across your organization, across all your systems, and then start to apply agents to take action on it?”

Yes, here, too, AI agents will play a big part. “We’re seeing a confluence of conversational and agent-based capabilities combined with search inside organizations,” said Parker. 



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