Most companies struggle to get value from AI due to people and process issues, despite its potential for innovation and the risks of disruption.
AI accelerates agile processes by providing powered insights, automating tasks, and enabling faster experimentation, leading to a new competency called hyperagility.
Combining human strengths like creativity and ethical judgment with AI's data processing power requires developing new skills like prompt engineering and AI literacy.
Leading companies like Netflix and Microsoft integrate AI into their agile culture, while many others struggle with adoption due to people and process challenges.
Overcome bottom-up adoption challenges by establishing leadership vision, governance, and using a self-assessment to determine your organization's AI agility level.
Become an AI agile leader by following a three-phase journey from establishing a foundation with quick wins to scaling successful pilots and measuring enterprise-wide impact.
Mitigate common AI adoption risks by implementing robust data governance, creating upskilling programs for talent, and establishing clear ethics and compliance frameworks.
Leading organizations succeed by embedding a clear strategic vision, making cultural investments in learning, increasing execution speed, and fostering human-AI partnerships.
Transition to a new operating model that uses hypothesis-driven sprints, dual-track development, and robust MLOps to build, scale, and sustain AI agents.
Jobs that call for the skills explored in this talk.