Creating the Conditions for Workplace-Wide AI Fluency

Discover how to build the right workplace environments to drive AI fluency across individuals, teams, and your entire organization. Grammarly Chief Information Security Officer Giles Douglas shares how to guide safe adoption through approved use cases, champion-led onboarding, clear policies, and visible leadership.

Your security posture should make you feel safe and empowered to work with AI. You shouldn’t feel weird about using it or need to hide that you’ve done work with an AI-augmented agent.”

Meet the expert behind the insights

Giles Douglas, CISO and Director of Engineering, Grammarly

Giles Douglas is Grammarly’s Chief Information Security Officer and Director of Engineering. With deep experience at the intersection of technology, security, and enablement, Giles leads both the protection of Grammarly’s systems and the cultivation of internal AI fluency. He believes that security should empower—not limit—innovation, and he’s helping shape a workplace where AI is safe to use, easy to trust, and central to how teams solve problems.

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Beyond Aspirations: Building the AI-Fluent Workplace

As the next step in our AI learning series, our experts return for a live, dynamic conversation that dives into the nuances of scaling AI fluency across your organization. Save your seat to get real-world perspectives on the personal, technical, and cultural shifts that can turn AI curiosity into workforce capability.

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Understand the key takeaways

1. Demystify AI by celebrating real examples

The fastest way to build AI fluency across an organization is to make AI feel visible, approachable, and worth sharing. When leaders and teams openly showcase how they’re using AI—what tools they’ve used, what’s worked, and how it’s made their work lives easier—it removes ambiguity and inspires others to explore. Whether it’s through Slack threads, project retros, or casual team meetings, every shared example helps normalize AI use across functions. Highlighting tangible wins doesn’t just celebrate progress—it creates visible proof that AI is valuable, safe, and accessible to everyone.

2. Make new-tool onboarding social, not siloed

Successful onboarding isn’t about perfection—it’s about participation. It should be inclusive and low friction, and it should be designed to reduce uncertainty, especially around what’s allowed and secure. Start by identifying power users who can test new tools, learn their quirks, and share practical tips with the team. Small-group demos and team-meeting walkthroughs are often more effective than formal trainings because they normalize AI use in trusted environments. This kind of social onboarding fosters open discussion, builds trust, and removes the “am I supposed to be using this?” hesitation.

Having someone prototype a tool and share results in a team meeting really lowers the barrier for everyone else. It brings it out of the shadows and gives it a clear stamp of approval.”

3. Guide safe adoption with approved use cases

Clear, sanctioned use cases are one of the fastest ways to encourage responsible AI adoption. When teams know what is allowed—not just what’s prohibited—they’re more likely to engage with confidence. Documenting and promoting a few well-defined, high-value scenarios for different teams and roles helps minimize confusion, reduce shadow IT risks, and align experimentation with business goals. This clarity is especially important for data-sensitive work where contractual and legal obligations apply.

4. Choose tools that are both reliable and evolving

In today’s fast-moving AI landscape, tool selection is less about permanence and more about flexibility. What works today might not be the right fit tomorrow, so leaders must continuously evaluate tools based on real usage and measurable outcomes—not just hype. Look for consistency: A tool that occasionally delivers “wow” moments but fails to repeat them won’t scale well across teams. At the same time, security-conscious organizations must evaluate how well tools align with contractual obligations, data governance standards, and long-term vendor accountability. Gathering feedback from power users and monitoring adoption trends can help surface which tools are driving value—safely and reliably.

Whatever you choose now is probably not going to be right in six months. The industry is changing very rapidly … You’ve got to look for tools that give you repeatable results.”

5. Keep policies living, visible, and understandable

A policy no one reads is a policy no one follows and may unintentionally prevent AI adoption if people don’t understand what’s allowed. A strong AI usage policy doesn’t just mitigate risk—it builds confidence across the organization. To be effective, it must be short enough to read, clear enough to understand, and visible enough to reference when it counts. The best policies define what’s encouraged, what’s off-limits, and how to propose new tools—complete with examples that make expectations real. They should also reflect current legal, contractual, and data governance obligations without overwhelming users with unnecessary complexity. Most importantly, policies must evolve alongside the technology and be written for everyone—from entry-level employees to executives—so that AI adoption is safe, consistent, and scalable.

Your acceptable use policy should be short enough to read, easy to reference, and useful for everyone from the intern to the CISO.”

6. Build team confidence through leaders’ storytelling

Fear—of failure, of doing it wrong, or of becoming obsolete—is one of the biggest blockers to AI fluency. Leaders play a critical role in easing that fear by modeling transparency, vulnerability, and a learning mindset. Sharing real stories—especially where AI didn’t work as expected—normalizes experimentation and gives teams permission to experiment, learn, and grow. Security leaders can reinforce this safety by clearly defining acceptable use and distinguishing experimentation from risky behavior. When employees hear real stories from trusted voices, AI becomes less intimidating, and they will use tools with more confidence and less hesitation.

If I can tell my team, ‘I tried to solve this with AI and it didn’t work,’ it shows them I’m learning too. That creates safety.”

AI that promotes fluency and evolves with your team

Grammarly’s intuitive AI editor, assistant, and agents accelerate seamless adoption for professionals at every skill level. It works across 500,000+ apps and websites, integrates into everyday tools, and adapts to each employee’s writing style, task, and organizational context. The result? AI that’s easy to adopt and evolve with your business.

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Apply what you’ve learned

Next steps for team leaders

Share one to two clearly approved use cases during a team meeting or async post to create clarity around what’s encouraged.

Set up lightweight onboarding moments. Use team meetings or Slack threads to normalize sharing wins, prompts, or fails.

Share a time an AI attempt didn’t go as planned and what you learned from it to model experimentation and reduce fear across your team.

Nominate a tool champion, someone on your team who’s experimenting with AI and can help evaluate, pilot, and demo new tools in team contexts.

Establish a cadence for AI policy updates. Ensure your acceptable use policy evolves with tech and reflects current practice. Keep it short, practical, and accessible.

Budget time and resources for AI learning. Offer protected time, access to tools, or a small stipend to explore and grow fluency.

Choose tools that support AI fluency at scale

Building AI fluency requires more than training. It takes tools that meet people where they are, help them grow, and evolve alongside them. Whether you’re looking for personal tools to experiment with or rolling out AI to your entire organization, here’s what you should look for:

Personalized and contextual

The best AI tools adapt to you and your organization—learning your voice, understanding your workflows, and getting smarter over time.

Ubiquitous by design

True fluency happens when AI is with you wherever you work. Look for tools that integrate into your daily flow—not ones that interrupt it.

Built for AI-native work

AI tools should do more than assist. They should collaborate with you—helping you prompt, iterate, and get to stronger outcomes faster.

Trusted by security leaders

Fluency can scale only when trust is in place. Choose tools that are secure by default and embraced by IT and end users alike.

See how Grammarly’s Marketing team brings AI fluency to life

Grammarly’s Marketing team shares real AI use cases to build trust and accelerate adoption through our own team and beyond. Explore examples that show what fluency looks like in action—and how storytelling can spark momentum across teams.

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