Cultivating an AI-native mindset

Embracing AI for every workflow

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.

4. Collaborative partnerships with AI

High-performing teams embrace AI as an integral part of how they perform a range of tasks, from writing emails to summarizing meetings to training new employees.

When Turing CEO, Jonathan Siddharth, told his HR team that they needed to onboard 800 new people in the span of a single week, the VP of Talent said they would “AI our way out of this.” In just three hours, they designed a new role-based system that took videos of engineering leaders onboarding new employees and used them to train a proprietary LLM. They used the resulting model to generate interactive learning modules for new hires. These included work simulations, sandbox environments for hands-on practice, and knowledge assessments for both formal exams and proficiency checks.

Thinking of AI as a collaborative partner in this way can lead to real impact for the entire organization.

5. Resiliency through flexibility

When navigating change, AI-native teams rely on AI to anticipate needs and adapt quickly. Instead of choosing time-consuming, rigid workflows, team members look to AI for opportunities to see results faster.

At FinQuery, creator of a fintech platform, employees experiment using Google Workspace with Gemini for everything from writing emails to kickstarting creative brainstorming — so people don’t have to start with the fearsome “blank page.” The remote-first company closes out brainstorming sessions faster with Gemini, giving teams more time to start on the next challenge.

Flexible and resilient teams also learn and iterate quickly from their successes and missteps with AI, sharing both positive and negative outcomes with colleagues. The sharing can happen through a Google Chat space, where winning prompts or popular notebooks can be posted.

Scaling the AI-native mindset

The throughline for scaling AI benefits quickly is positioning AI as a collaborative partner. You gain buy-in for AI when it accelerates great work. Encourage growth of the AI mindset by creating your own customized learning plan with Gemini, sharing it with your teams, and asking them to do the same.

When an AI mindset takes hold, coworkers will celebrate the successful outcomes that AI delivers — like the time saved by automating tasks, or the creative brainstorming kicked off by AI prompting. Fostering an AI-native mindset creates a flywheel effect, accelerating usage, outcomes, and the motivation to keep up with the ever-evolving capabilities.