Building a foundation for AI success: Organization and culture

This is part five of a six-part blog series. See part one, part two, part three, part four, and download the white paper.

What does it mean to become an AI-powered organization?

It’s long been understood that technology isn’t an island; it requires people and processes to deliver results. But AI, and especially generative AI, is unlike any technology that has come before, which requires us to look at the equation a bit differently, taking an intentional approach to deploy and drive adoption and value.

In this post, we’ll explore a few of the emerging best practices that are helping leaders position their organizations for success in the age of AI:

• Start at the top: communicate your vision and priorities
• Empower diverse teams
• Foster a culture of agile experimentation
• Empower employees with learning and skilling resources
• Establish a clear operating model

Start at the top: Communicate your vision and priorities

Becoming an AI-powered organization begins with clarity, and clarity begins at the top. It’s critical for leaders—starting with the CEO and throughout the entire C-suite—to communicate their organizational priorities and their vision for how AI will support the future of the business so teams know what they’re solving for and can propose and execute on the highest-impact use cases.

Empower diverse teams

Studies continue to demonstrate the relationship between diversity and business performance, and this is as or more valuable with AI, given its wide applicability to many different types of use cases and human impacts. Leaders should reinforce the importance of diverse teams that represent multiple areas of the organization, as innovation can come from anywhere, whether it is human resources (HR), marketing, advertising, finance, sales, product management, or another group.

Diverse teams also deliver significant value related to anticipating potential issues, as having broader representation on a team helps to ensure that AI systems meet the needs of the widest possible range of customers and consumers.

Foster a culture of agile experimentation

Successful AI projects involve trial and error, experimentation, and a willingness to learn from failures as well as successes. But this can only happen when leaders actively encourage and value a growth mindset and create the conditions for psychological safety. This does not mean that “anything goes,” however. It does mean shifting from a linear development approach to more of an iterative one.

This is where process comes in. An iterative approach—what developers know as agile development—is specific, rigorous, and proven, and well-suited to the nature of AI. Agile development values principles such as customer satisfaction, collaboration between business and technology experts, and short timescales, among other things. Fostering agile approaches across the organization will help to create the kind of alignment among business and technology stakeholders that is critical to the success of AI initiatives and will help increase the velocity at which your organization is able to innovate.

Empower employees with learning and skilling resources

Because AI represents a new way to work, and it’s evolving so quickly, it’s important to offer continuous learning resources to enable employees across the organization to acquire new AI skills and stay abreast of industry trends.

• Encourage employees in the business to build their understanding of how AI works and experiment with AI-powered tools. This will enable them to stay current and envision new ways to use AI in their organization.
• Provide technology teams with access to skilling content on critical topics such as model building and refinement, prompt engineering, and responsible AI development so they can keep current with the latest tools, approaches, and techniques.
• When possible, deploy AI to entire teams within a specific business function, like customer service or sales, to enable them to share insights, learn from one another, and multiply impact.

Establish a clear operating model

As the number of AI-related projects grows, it becomes increasingly important to establish a clear operating model so that you can build sustainable value across the organization. Whether it is a center of excellence, a distributed team, or a different structure, a clear operating model should enable all teams working with AI—irrespective of their geographical location or business unit—to share best practices and resources, training and skilling tips, measurement strategies and learnings, and provide leadership with visibility on AI projects at an aggregate level.

Next steps

Organizations around the world are just starting their journey to become AI-powered. Yet because AI is such a significant change, and that change is coming faster than ever, leaders are increasingly trying to anticipate what’s next. One thing is clear—leaders who lean in early to the opportunities that AI represents will be best positioned to drive value for their stakeholders.

Stay tuned for the final post in our series: “Building a foundation for AI success: AI Governance,” in which we will explore the security, data privacy, and responsible AI best practices that are critical to building trust in and success with AI.

Download a copy of the “Building a Foundation for AI Success: A Leader’s Guide” white paper.