What Google Is Building With AI Agents for Business
If you hear the phrase “AI agents,” you might picture something straight out of The Matrix.
Back in 1999, the movie introduced us to Agent Smith ,a digital program designed to move through systems, enforce rules, and execute tasks inside a simulated world.
Thankfully, the AI agents businesses are building today are a little less dramatic.
They’re not chasing anyone across rooftops.
But the comparison isn’t entirely wrong.
Just like the fictional agents in The Matrix, modern AI agents for business are designed to operate inside complex systems and perform tasks automatically.
And that’s exactly what Google is working on.
I recently traveled to Google’s Atlanta campus to attend their SMB Boost event, where engineers and product leaders discussed how AI agents are being built to automate real business workflows.
After spending the day there, one thing became very clear:
AI is quickly moving from experimentation to execution.
This article is Part 2 of a four-part series where I’m sharing what I learned from visiting Google and what it could mean for businesses over the next few years.
The Shift From AI Experiments to AI That Executes Work
For the past couple of years, most businesses have been experimenting with AI.
Trying tools like ChatGPT.
Using AI to summarize documents.
Generating marketing copy.
But that’s only the beginning.
What Google emphasized during the event is that we’re entering the next stage:
AI that actually performs work inside businesses.
Industry experts increasingly believe this shift will have massive economic impact.
Research cited during the event suggested that AI-driven transformation could create more than $4 trillion in global economic value.
And adoption is accelerating quickly.
According to data shared at the event:
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More than half of organizations are already deploying AI in some form
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By 2026, around 40% of business software applications are expected to include AI agents
In other words, this isn’t theoretical anymore.
It’s already happening.
What Is an AI Agent for Business?
An AI agent for business is software that can:
• Understand a task
• Access business data
• Use multiple systems
• Execute steps automatically
• Deliver a completed result
That last part is the big difference.
Most AI tools today generate information.
AI agents actually take action.
For example, an AI agent might:
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collect information from several systems
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process a document
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update a database
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trigger a workflow
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send a report to a team
Instead of just answering questions, the AI is helping complete work.
That’s a major shift.
Google’s Strategy: Building an AI Infrastructure Layer
One of the biggest takeaways from the event is that Google isn’t just building AI tools.
They’re building an AI infrastructure layer for businesses.
Their approach revolves around three core components.
1. Gemini AI Models
At the center of Google’s AI ecosystem is Gemini, its family of AI models.
Gemini can:
• understand text, images, and documents
• analyze large amounts of information
• reason through complex instructions
• generate responses and actions
But unlike early AI tools, Gemini is designed to integrate directly with business platforms and workflows.
This allows AI agents to operate inside real systems rather than just generating standalone responses.
How Google Is Bringing AI Agents to Businesses Through Gemini Enterprise
One of the most important platforms discussed at the event is Gemini Enterprise, which Google is positioning as a core layer for deploying AI across organizations.
In a previous article, I discussed why I attended Google’s AI event and what I hoped to learn.
You can learn more about it here:
https://cloud.google.com/gemini-enterprise
Gemini Enterprise is designed to bring AI directly into business environments, allowing teams to use AI securely with their internal data, documents, and workflows.
Instead of AI being a separate tool, Google is building it so AI can operate inside everyday business platforms.
That means AI can assist with tasks like:
• analyzing internal documents
• summarizing large datasets
• generating reports
• assisting with workflows
• coordinating tasks across multiple systems
And importantly, the system is designed with enterprise-level security, governance, and data protection, which is critical for organizations that manage sensitive information.
Whether you currently use Google Workspace or not, platforms like Gemini Enterprise are designed to integrate with many existing systems businesses already rely on.
That means organizations don’t necessarily need to rebuild their technology stack to begin using AI-driven automation.
Instead, AI can start enhancing the tools they already use.
AI Agents: The Next Layer of Business Automation
Beyond the core AI models themselves, Google is also building frameworks that allow businesses to create AI agents that perform tasks autonomously.
Google provides an overview of this approach here:
https://cloud.google.com/gemini-enterprise/agents
These agents are designed to move beyond simple prompts and responses.
Instead, they are intended to execute workflows and interact with multiple systems on behalf of users.
For example, an AI agent might:
• retrieve information from multiple systems
• analyze documents or datasets
• generate a summary or recommendation
• trigger follow-up actions automatically
This concept of AI agents collaborating with each other was a major theme of the event.
In many cases, multiple agents can work together as part of a coordinated workflow, something Google refers to as agent orchestration.
This allows complex business processes to be broken down into smaller automated tasks handled by different AI agents.
2. AI Agent Orchestration
The second major concept Google discussed is something called agent orchestration.
This is where multiple AI agents work together to complete complex tasks.
For example:
One agent might gather customer data.
Another might analyze patterns.
A third might generate outreach or recommendations.
Instead of relying on one system to do everything, multiple agents collaborate across tasks and tools.
It starts to resemble a digital workforce coordinating behind the scenes.
3. Data Connectivity
The third component is arguably the most important.
AI agents are only useful if they can interact with real business data.
Google demonstrated how agents can connect to:
• internal documents
• cloud storage
• databases
• CRM systems
• marketing platforms
• analytics tools
Once AI agents can access real data, they can start automating real workflows.
And that’s when the technology becomes truly valuable.
Why AI Agents Matter for Small and Mid-Sized Businesses
At first glance, you might assume this technology is built mainly for large enterprises.
But the event I attended was specifically focused on small and mid-sized businesses.
And that’s intentional.
Most SMBs face the same operational challenges:
• limited staff
• disconnected software systems
• repetitive administrative work
• manual processes that slow things down
AI agents are designed to address exactly those problems.
Instead of hiring more people to manage repetitive tasks, businesses can deploy AI agents to handle things like:
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data entry
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workflow coordination
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reporting
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document processing
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customer communication
That’s where businesses start to see real productivity gains.
The Breakthrough: Low-Code AI Automation
Another important takeaway from the event is that businesses won’t need huge development teams to implement these systems.
Google emphasized low-code and no-code AI tools.
This means businesses can build AI workflows visually.
For example, a workflow might look like this:
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Capture information from a document
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Extract important data fields
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Store the information in a system
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Trigger follow-up actions automatically
For organizations that rely heavily on documents and information flow, this opens the door to significant efficiency improvements.
Why This Matters for Document Workflows
This is where the conversation becomes especially relevant for the industries we work with at ClearView.
Many everyday business processes still revolve around documents:
• invoices
• contracts
• purchase orders
• forms
• medical records
• applications
In many organizations, those workflows are still manual.
But AI agents can change that.
They can:
• read documents
• extract key data
• classify files
• route documents automatically
• trigger approvals or notifications
And they can do it across systems that weren’t originally designed to work together.
That’s where AI begins to deliver real operational efficiency.
What I’ll Cover Next
This article focused on what Google is building with AI agents for business.
In the next post in this series, I’ll take a closer look at something even more practical:
How AI agents will transform document workflow automation.
We’ll explore:
• how documents become structured data
• how workflows can run automatically
• how businesses can remove operational bottlenecks
While the technology itself is impressive, I think the real value comes from how businesses apply it.
Final Thoughts
AI agents aren’t quite the agents from The Matrix.
But the concept isn’t that far off.
They’re digital systems designed to move through software environments, gather information, and execute tasks.
And companies like Google are investing heavily in making them part of everyday business operations.
The organizations that learn how to deploy AI agents for business workflows will gain major advantages in productivity, efficiency, and scalability.
That’s exactly why I made the trip to Google’s Atlanta campus, to understand what’s real, what’s practical, and what business leaders should actually be paying attention to.
AI is quickly becoming part of how modern businesses operate.
If you’re exploring AI automation or document workflow improvements, you can always contact our team here: https://www.cvbusinesssolutions.com/contact/
