Building a foundation for the agentic AI era

Agentic AI is here. But with many orgs still in the early stages of fully integrating generative AI business-wide, it can be hard to know how to start building toward agentic implementation, let alone transformation.

Regardless of where you are in the AI adoption process, you can prepare to harness agentic workflows by making sure your organization prioritizes transformation in three key areas: mindset, AI fluency, and ecosystem. Laying the groundwork for agentic workflows leads to true AI transformation by moving gains from isolated tasks that boost productivity to orchestrated, organization-wide business impact.

1. Cultivate and broaden an AI-first mindset

Buy-in is vital for effective adoption — from the front line to the C-suite. Creating agent-based workflows requires a commitment to rethinking processes. As organizations embrace agentic AI and redesign processes at scale, they should reframe how they think about the human-AI interaction. Instead of employees instructing AI assistants with detailed prompts for on-demand outputs, they can now take a more proactive, outcome-oriented approach to designing end-to-end workflows.

This new mindset can be reinforced with training and tools that showcase an agent’s core capabilities:

• Context — It has a big-picture understanding of a user’s unique information, including business data, historical projects, and preferences.
• Reasoning — It plans the “how,” breaking down complex goals into steps and selecting the right tools for the job.
• Orchestration — It acts, securely invoking tools to execute work, such as synthesizing documents or updating project trackers.

2. Strengthening AI fluency

Chances are good that before your organization embraces agentic AI, your employees have already become skilled at natural-language prompting. They’ve undoubtedly used AI within the apps where they work every day — like Gemini in Docs, Sheets, Meet, and Gmail — to draft or improve content, take meeting notes, and respond to emails. Many of those same skills, like refining outcomes through iteration, are applicable to working with agents. And just like natural-language prompting relies on good inputs (defining persona, task, context, and format), setting up an effective agent relies on defining purpose, instructions, data sources, and guiding principles.

Once your teams have consolidated their productivity gains working within apps, you can deploy pre-built AI tools and agents to improve entire workflows and increase efficiency across shared tasks.

For example:

• Gemini Deep Research to transform competitive intelligence or marketing research, reducing a lengthy, manual process from weeks to hours.
• Data Insights to instantly extract business intelligence from complex datasets without any specialized syntax or coding.
• Gemini Code Assist to help developers perform coding tasks across the software development lifecycle.
• NotebookLM to accelerate team knowledge sharing by summarizing and extracting information across dense and complex sources.
• Workspace Studio to automate everyday work by orchestrating complex processes across your business apps.

And when your teams are ready to start experimenting with designing their own agents, they can set them up in tools like Gemini Enterprise, which includes our Agent Designer that turns unique team knowledge into scalable, automated processes without needing to write a single line of code. For example, your marketing team can create an agent that helps them develop on-brand content and assets, using past campaign reports, brand guidelines, and messaging docs as inputs. Or HR teams can set up an onboarding agent that helps new employees find, summarize, and explain information based on the latest approved policies.

3. Create an agent-optimized ecosystem

In many organizations, “context walls” grind AI-driven productivity to a halt, especially with agents. The data needed as inputs to agents (like purchase history, budgets, or project plans) is often fragmented across apps, forcing employees to move data between tools to synthesize a holistic knowledge base.

To truly embrace agentic AI, organizations need a unified agentic platform that connects disparate data silos via a centralized orchestration layer for building and governing agents securely. Gemini Enterprise provides a platform for the creation and management of agents, with enterprise-grade governance and security controls to help protect company data and brand trust. And because it’s integrated directly with Google Workspace, Gemini Enterprise acts as the connective tissue across the data and context that lives in your daily work apps, from Gmail and Docs to Drive and Meet. With cross-app integration, agents have the context to be most helpful and can achieve defined goals autonomously.

Crafting your agentic future

The transition to an agentic workplace doesn’t happen overnight, but with the right groundwork it begins to take shape through mindset, fluency, and the right ecosystem. When teams experiment with pre-built and custom agents, they glimpse that agentic future in a matter of minutes. Instead of using AI to streamline writing emails and documents, or crafting better decks, they are empowered to reimagine whole processes. That new perspective shifts AI gains from the adhoc and isolated to orchestrated and org-wide.

Read our Business Leader’s Guide to Agentic Work.