Staying ahead in the age of AI

The pace of AI progress is unlike anything we’ve seen in technology. Early adopters are already growing revenue 1.5× faster than peers⁠(opens in a new window), yet many companies feel the pace is too fast to plan for effectively. One of the questions we hear most is how to keep up, enable employees to adopt AI, and build an AI-first organization. D rawing on the experience OpenAI has had with leaders at companies like Estée Lauder, Notion, the San Antonio Spurs, and BBVA, this playbook shares five practical steps - Align, Activate, Amplify, Accelerate, and Govern - to help your organization move quickly and confidently as AI continues to advance.

Employees adopt change faster when they clearly see how new AI initiatives enhance their skills, enable more meaningful work, and contribute to their company’s competitive advantage. Leaders play a critical role in driving this alignment by explicitly communicating the purpose behind AI initiatives, demonstrating their commitment, and actively supporting employees throughout the transition.

Be specific on why AI adoption is key to your company's future, whether it's keeping pace with competitors, responding to evolving customer expectations, or sustaining growth. When employees hear a thoughtful “why,” it creates trust and clarity, helping them see how these changes align with their own work and goals.

Define a measurable goal that connects AI adoption to everyday work. This could be new use cases, frequency of AI tool usage, or setting benchmarks for team experimentation, and incorporate these goals into company planning and KPIs. Communicate this goal through allhands or company updates to build momentum and signal that AI is part of how work gets done.

Ask senior executives to regularly share how they use AI in their roles. Hearing directly from leadership about how AI helps them stay ahead of market trends or quickly analyze customer insights normalizes and encourages AI use and experimentation.

Line-of-business leaders are best placed to connect AI initiatives to the realities of each team’s work. Encourage them to hold sessions that highlight relevant use cases, invite feedback, and answer questions. This helps employees connect AI to their everyday work and understand its value.

Nearly half of employees say they lack the training and support needed to confidently adopt generative AI. Yet, they rank training as the single most important factor for successful adoption.⁠(opens in a new window) Companies that move fast invest in supporting their employees' learning. This means making space for experimentation, equipping teams with department specific training, and normalizing the need for learning.

Ask your Learning & Development team to create clear, role-specific training that moves employees from basic AI awareness to hands-on use, prioritizing skills that directly support real workflows rather than abstract concepts. For example, the San Antonio Spurs boosted AI fluency from 14% to 85%⁠ by embedding training into the flow of daily work instead of treating it as a separate initiative.

Identify and train passionate employees to serve as internal AI mentors. These champions help colleagues become confident AI users through workshops, informal coaching, and spreading enthusiasm.

Give employees regular time to explore AI tools. Try dedicating the first Friday of each month for teams to workshop how AI could improve their work. Pair this with no-code hackathons where cross-functional teams can prototype real solutions, and fast approvals to ensure promising ideas move forward.

Directly link AI engagement to performance evaluations and career growth. Use OKRs or similar mechanisms to set clear, role-specific goals, like identifying workflows to enhance with AI or piloting new use cases. Highlight meaningful AI contributions during promotion and recognition conversations, so employees see experimentation as central to their professional success.

The fastest way to scale AI impact is to stop solving the same problems in silos. Amplifying progress means turning scattered wins into shared knowledge, documenting successful prompts, workflows, and use cases so other teams can reuse, improve, and build on them.

Build a single, easy-to-access hub (e.g., in Confluence, Notion, or SharePoint) where employees can find everything related to AI: training resources, hackathon dates, policies, guides, and best practices. A centralized hub reduces confusion, saves time, and prevents teams from reinventing the wheel.

Regularly highlight impactful AI projects, practical lessons, and easily replicable wins through monthly newsletters, internal webinars, or short segments in all-hands meetings. Showcase a balance of big breakthroughs and smaller, everyday successes. Share the steps teams took so others can easily apply these insights to their own workflows.

Establish dedicated communities (such as Slack or Teams groups, or an internal AI Center of Excellence) to promote peer-to-peer learning, realtime collaboration, and rapid sharing of insights. Lean on your AI champions to regularly encourage discussion, share useful resources, and keep the conversation active and engaging.

Directly link AI engagement to performance evaluations and career growth. Use OKRs or similar mechanisms to set clear, role-specific goals, like identifying workflows to enhance with AI or piloting new use cases. Highlight meaningful AI contributions during promotion and recognition conversations, so employees see experimentation as central to their professional success.

In order to scale quickly, teams need flexible infrastructure, clear decision-making authority, and lightweight approvals. Accelerating means removing friction and ensuring good ideas move quickly from pilot to production.

Make sure teams can quickly access the data and AI tools they need to test and build. If it still takes weeks, or months to get approval for basic tooling or to pull clean data, your infrastructure is holding you back. Many companies are increasingly empowering employees to recommend the AI tools they find most valuable, accelerating adoption and productivity.

Create a simple, transparent way for teams to submit AI project ideas, get quick feedback, and understand how priorities are set. This reduces confusion, avoids duplicated efforts, and ensures energy goes to the most promising use cases.

Create a small, executive-sponsored group with authority to unblock projects surfaced through your intake process, resolve cross-functional issues quickly, and fast-track approvals for high-potential initiatives. The council s role is to remove friction while keeping efforts aligned with broader company goals and ensuring that risk, compliance, and governance considerations are addressed early.

When specific teams create efficiencies or cost savings with AI, give them the resources or time to reinvest in further innovation. Recognizing and rewarding these wins not only accelerates progress but also signals that high-impact teams earn the freedom to keep pushing boundaries.

Moving fast doesn’t mean ignoring risks. It means having clear, practical guidelines so teams can move quickly within established safeguards. Good governance should support rapid action, not create new roadblocks.

Document practical, easy-to-follow guidelines that help teams use AI responsibly, and make decisions consistent with those guidelines instead of needing manual compliance reviews each time. Focus on what’s “safe to try” and what requires escalation.

Hold lightweight quarterly audits of your AI systems, processes, and governance guidelines. Focus on whether current protocols still make sense, both in protecting the business and enabling teams to move fast.

AI adoption is moving faster than most leaders ever imagined. Staying ahead is about creating the right conditions for your people and teams to adapt with confidence. The companies that will thrive are the ones that treat AI not just as a tool, but as a new way of working.

Start with clarity of purpose. Show your teams why AI matters, set company-wide goals, and role-model adoption at every level. Alignment builds trust and helps employees connect their daily work to your broader AI strategy.

Make learning real and practical. Invest in structured training, create AI champions, and give people room to experiment. When employees see AI as part of their growth and success, adoption becomes natural.

Don’t let wins live in silos. Share success stories widely, build knowledge hubs, and create active communities so everyone can learn from what’s working. Momentum spreads fastest when people see peers succeeding.

Remove friction. Make it easy for teams to access tools, submit ideas, and move projects from pilot to production. Empower decision-making and reward teams who push ideas forward.

Balance speed with responsibility. Clear, lightweight guidelines ensure progress without unnecessary bottlenecks. When governance is practical and evolving, it protects the business while keeping innovation alive.