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AI and Machine Learning

10 best practices for deploying AI at scale

December 2, 2025
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Pat Day

Head of Customer Success, Google Workspace, Americas

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Although AI has become an everyday tool for millions, translating AI adoption into real, measurable impact remains a challenge. In fact, more than 70% of business leaders report significant implementation issues. These might stem from unclear goals, clunky rollouts, or under-investment in training.

As a customer success leader, my team and I work with hundreds of organizations who use Workspace to help them embrace an AI-first culture. And while any new way of working is an adjustment, the boost to productivity and innovation after deploying AI make this change speak for itself. To help organizations get there, we spoke with 20 recognized AI adoption leaders. Here’s what we learned about successful rollouts.

Build a foundation

  • Anchor adoption in culture by aligning your AI rollout with your organization’s existing values, practices, and priorities. Create company-wide programs like roundtables and usage awards to help integrate AI into workflows and build employee skills.
  • Assign a clear owner or champion to help guide adoption and provide a central point for guidance, feedback, and ideas. Working with AI champions across teams helps break down silos and foster knowledge-sharing throughout the organization.
  • Set governance guidelines to give your team the freedom to experiment without exposing the organization to undue risk. Vague — or absent — guidelines can lead to employees making choices about data sharing or AI usage that don’t align with company values. Concrete examples help provide clarity and a starting point for risk-averse users.  

Implement the right tool

  • Focus on the right use cases to clearly showcase gen AI’s benefits. Match your use cases to your company’s needs. Starting with specific “jobs to be done” and “problems to be solved” helps accurately assess gen AI’s impact for the organization.
  • Define metrics to celebrate success and justify investment. Set clear, measurable targets for success that reflect your business goals. For example, Sports Basement gauged the success of their rollout of Gemini to their customer service teams by measuring time spent on responses. With gen AI, the customer service team spent 30%-35% less time responding.
  • Balance business impact with rollout complexity to get quick wins without sacrificing larger strategic projects. At Google, many teams prioritize projects based on three elements: business value, actionability, and feasibility. Quick wins jump to the front of the queue. Larger changes come after we lay the groundwork for AI. That means faster rollout and more-strategic resource deployment.

Drive interest and adoption

Invest in communications, training, and rewards to build excitement, reduce friction, and encourage experimentation. Gamify usage and reward high-impact contributors to help drive momentum that helps your rollout succeed. Host hackathons or AI immersion days to celebrate creative applications and encourage experimentation — you never know where the next big idea might come from.

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Bring the team together for brainstorming new AI use cases

  • Align with team and user needs to help ensure no one gets left behind. This drives enthusiasm and buy-in as users start to see the full impact AI can have on their work. Pepperdine University built a change management team to deliver support — and snacks! — to every department with tips tailored for each team. The program also provided a smaller-group setting to address ongoing concerns.

Sustain momentum

  • Refine your strategy as needs change to keep up momentum. Deployment plan flexibility helps you stay agile in the ever-changing gen AI space. As capabilities evolve, look for new opportunities to integrate AI into workflows — and encourage employees to keep experimenting.
  • Create a roadmap to guide your team through adoption with clear goals and timelines. Outline critical milestones, from pilot programs to org-wide deployment. Make sure to communicate the timeline broadly so everyone can get excited about what’s coming next.

For a deeper dive into deploying AI at scale, download our ebook.

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