A culture of experimentation

Once employees have acquired the necessary foundational knowledge, the next step is to cultivate a culture of experimentation within the organization. Establishing this culture encourages employees to explore and experiment with AI technologies in their everyday work, leading to novel and disruptive ideas. Here are some strategies to foster a culture of experimentation:

Executive support and leadership

Cultural change does not happen with the snap of the CEO's fingers, but leadership plays a pivotal role in supporting and promoting desired behaviors like AI experimentation. Executives should communicate the importance of AI experimentation and encourage employees to take risks.

Establish "safe to fail" environments

We always said it was important for our team to "fail fast to learn fast." I cannot stress enough how important this is. We know that true growth is most impactful when it comes from failure, but individuals' tolerance for their own failure will vary. To open the door for rapid growth and understanding, leadership needs to make it clear that employees are encouraged to fail, so long as their experiments fall within the acceptable parameters set by leadership. For example, we set specific guidelines for the tools our employees could experiment with and the types of use cases they could use AI to facilitate their work. Encourage employees to treat failures as opportunities for learning, rather than punitive events. Leadership that encourages this mindset will empower employees to take calculated risks, knowing that their efforts will be rewarded and valued.

Continuous learning

AI technologies evolve rapidly, and it can be challenging for individuals to stay up-to-date with the latest advancements. To prevent skills gaps (and bridge those gaps when they inevitably happen) provide continuous learning opportunities, such as workshops, online courses, or mentorship programs. As part of our training, we created interdisciplinary teams that were specifically dedicated to AI experimentation. Employees across different teams, and with varying levels of AI expertise, worked together on AI projects. We made sure each group had at least one "power user" who could guide the other members of the team and push their boundaries. Allowing employees to share their diverse perspectives has been a pivotal part of the knowledge sharing process and has made it more for our team to make innovative discoveries.

Provide dedicated resources

Your workforce needs guidance on AI in order to properly experiment. Instead of saying vaguely "go learn about AI," provide access to dedicated resources — AI tools, datasets, and training programs — and give them actionable recommendations for how to experiment. What sorts of tools do we encourage using? Given the current capabilities and pitfalls of the technology, what tasks are best performed with AI and what tasks are not recommended for AI? These resources can be part of an AI innovation hub, allowing employees dedicated time to collaborate and experiment. For more advanced users, give them license to perform advanced tasks with AI and provide them with the infrastructure and tools to help them do so safely and effectively.

Reward and recognize

Incentivize AI experimentation by rewarding successful projects and by rewarding innovative ideas, regardless of their success. Our enthusiasm as leaders should be infectious when we see AI innovation in our teams. We want to see rapid growth and drive our more cautious team members to that wonderful light bulb moment, so our leadership purposefully celebrates employees who demonstrate innovative thinking and achieve breakthrough results through AI. This recognition not only motivates individuals, but also signals to the entire workforce the value we place on experimentation and disruption.

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How to empower your workforce to experiment and grow with AI

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