The video discusses the challenges enterprises face in adopting AI and introduces the “crawl, walk, run, fly” framework to guide organizations through the process, emphasizing a decentralized approach that encourages exploration and experimentation. It outlines the phases of AI adoption, from initial curiosity and discovery to operational integration and establishing a Center of Excellence, ultimately aiming to foster innovation and productivity through effective AI use.
In the video, the speaker discusses the challenges enterprises face in adopting artificial intelligence (AI) and presents a framework called the “crawl, walk, run, fly” model to facilitate this process. The speaker identifies a significant barrier to AI adoption as the skepticism and uncertainty surrounding the technology, which stems from its novelty. Many organizations struggle with how to deploy AI effectively, often leading to misguided attempts to establish centralized Centers of Excellence (CoEs) that can hinder progress rather than promote it. Instead, the speaker advocates for a decentralized approach that empowers product teams to explore AI organically.
The “crawl” phase of the model emphasizes the importance of exploration and discovery without the pressure of immediate returns on investment (ROI). The speaker argues that organizations should encourage employees to experiment with AI tools, fostering curiosity and familiarity with the technology. This phase is crucial for building confidence and understanding of AI’s capabilities, as many employees may be skeptical or unaware of how to leverage these tools effectively. The speaker highlights that the goal during this phase is to engage curiosity rather than seek immediate value.
Once organizations have moved past the crawl phase and employees are no longer bored with exploration, they can transition to the “walk” phase. In this stage, teams begin to identify specific tools or applications of AI that can add measurable value to their work. The speaker shares a personal example of using AI-generated art for book cover design, illustrating how AI can provide better, faster, and cheaper solutions compared to traditional methods. This phase marks the beginning of integrating AI into workflows with a focus on achieving tangible results.
The “run” phase follows, where organizations start to operationalize their AI initiatives based on the lessons learned from the walk phase. This involves scaling successful applications of AI across different departments and establishing systematic processes for using AI tools. The speaker emphasizes the importance of measuring outcomes, such as reducing the time to resolution for support tickets or improving marketing efficiency through automated A/B testing. This phase is about embedding AI into the organization’s culture and operations to maximize its benefits.
Finally, the “fly” phase represents the culmination of AI maturity within an organization. At this stage, companies can establish a Center of Excellence led by individuals who have developed expertise in AI through the previous phases. These leaders can then create best practices and strategies for AI deployment, ensuring that the organization is well-equipped to leverage AI for ongoing innovation and productivity. The speaker concludes by expressing a desire to accelerate AI adoption across industries, believing that widespread use of AI will drive economic and scientific progress.