Cultivating an AI-native mindset

There’s more to fostering an AI-native mindset than simply using AI tools. Getting the most out of AI-powered tools and workflows also requires training, increased confidence in using AI, and examples of success — in short, it requires a new way of thinking.

The goal of cultivating an AI-native mindset is to build teams that understand the value of integrating AI across all their workflows. Workers will see how they can work smarter and become more efficient with their time, and they’ll understand how AI inspires their own creative projects.

Here are the hallmarks of teams with an AI-native mindset:

1. Curiosity and experimentation

Team members who use AI confidently will see opportunities for collaboration in every task and process. Once they’ve mastered using AI to save time and improve productivity, their instinct is to match AI’s strengths to their own. They view AI as a partner in exploring fresh possibilities for project success, tapping into it for inspiration and research.

AI-native teams have moved beyond foundational prompting skills to push the boundaries of AI interactions. At MAS, an experiential marketing agency, creative teams experiment with iteration to prompt and even challenge AI to come up with new perspectives or angles. MAS creative teams keep Gemini conversations going with “plenty of curiosity and flexibility,” digging deeper for unexpected approaches.

Teams with the AI-native mindset are also curious about exploring different AI tools for different needs. For tasks that are repeated regularly, they can create Gems to help save time that’s better used for complex projects. And for developing education content, they can turn documents into podcast-style audio discussions.

Teams also recognize when it’s time to stop using processes and tools that are no longer relevant in an AI-driven workplace.  Instead of cutting and pasting sections of a research paper to summarize findings, AI-savvy teams will ask Gemini to create a summary directly from Google Docs.

2. AI fluency

Ease and confidence with AI tools come from frequent experimentation and an understanding of AI’s value. The AI-native mindset includes knowledge of how an organization’s own unique models are developed, how models are trained, and how responsibilities for AI governance and ethics are shared.

To foster this fluency, leaders can gather content into NotebookLM to build a shareable and updateable resource. Add Google Docs, PDFs, websites and YouTube videos relating to AI model training, governance, data sources, and educational resources for employees. NotebookLM uses AI to create summaries, quizzes, study guides, and even audio overviews of your organization’s AI-related content.

3. Data-driven decision making

Team members with an AI-native mindset know how to get out of their comfort zones when they’re solving problems. They’re as open-minded to AI as they are to new people on their teams.

When important decisions are in the works, these teams know AI can deliver approaches based on evidence and data. For example, with Gemini Deep Research, team members can ask Gemini to collect, analyze, and report the information they need. Deep Research can then create a plan, breaking down the tasks necessary to complete a project or make key decisions.

You've explored how curiosity and experimentation, AI fluency, and evidence-based problem solving form the core of an AI-native mindset. To see how this perspective extends to real-world applications—including collaborative partnerships with AI and fostering resiliency through flexibility—continue reading the rest of this article on the Google Workspace blog.