Leadership in AI-Assisted Engineering

This presentation, led by Justin Reock, Deputy CTO at DX, discusses the integration of AI in engineering organizations. It highlights the importance of leadership in establishing best practices and measuring AI's impact through DX's AI Measurement Framework.

Key Points:

• AI Utilization and Impact: Google reports a 10% productivity increase in engineers using AI. However, the impact varies across companies, with some experiencing up to a 20% change in developer experience and others facing negative outcomes.
• Metrics Framework: The DXAI Measurement Framework helps correlate AI utilization with impact metrics. Key metrics include system velocity, developer satisfaction, change failure rate, and engineering hours saved.
• Challenges and Variability: The adoption of AI shows significant variability in change confidence and code maintainability across different companies. This highlights the need to evaluate AI's impact on a per-company basis.
• Leadership Strategies: Successful AI adoption requires addressing compliance early, encouraging innovation, and providing employees with time and resources to develop AI skills. Emphasizing AI as a productivity augmenter rather than a job replacer is crucial.
• Psychological and Operational Impact: Addressing the psychological impact of AI on teams by promoting transparency and understanding of metrics to avoid misuse and maintain productivity.

The presentation underscores the complex dynamics of integrating AI in engineering, emphasizing a nuanced, company-specific approach to manage its diverse impacts effectively.

This is the end of the AI-generated content.

To realize meaningful returns on AI investments, leadership must take accountability and ownership of establishing best practices, enabling engineers, measuring impact, and ensuring proper guardrails are in place.

When prompting practice and reflexive AI use is driven from the top down, engineers can align on the highest value use cases and experience peak productivity gains. When coupled with DX's AI Measurement Framework, leaders can gain a clear picture of AI's true impact, identify the real bottlenecks in the SDLC that can be augmented with AI, and drive improvement.

In this session, Justin Reock, Deputy CTO at DX, and author of DX's Guide to AI Assisted Engineering, will explain what the most effective leaders of AI enabled engineering organizations are doing to drive satisfactory utilization, augmentation, and psychological safety across their teams. Based on interviews, use cases, and data, leaders will walk away with an understanding of how to best lead their teams through mature AI rollouts.