Talent and culture 13. Innovation Culture Embedded: just ML engineers—such as Organizations ensure innovation is part behavioral scientists, social scientists, 11. Mandatory AI Training: Organizations of the day-to-day work environment. and ethicists. enforce AI-specific training programs to They encourage mindsets, behaviors improve AI fluency, which are tailored and routines that all serve as a vehicle Responsible AI for senior leadership and specific for experimentation, collaboration functions, e.g. salesforce, product and learning from ideation to product 16. Responsible AI: Organizations have engineers, etc. They also create development to market launch. an industrialized, responsible approach deliberate opportunities for employees to data and AI across the complete to learn and apply AI in their roles. 14. Innovation Culture Encouraged: lifecycle of their AI models—an Organizations promote and reward approach that can meet changing 12. Employee Competency in AI- innovative mindsets and behaviors regulatory requirements, mitigate risks, Related Skills: Organizations regularly including entrepreneurship, and support sustainable, trustworthy AI. measure the competency level of collaboration and thoughtful employees to determine where further risk-taking. 17. Responsible AI—Change: training is needed to improve overall Organizations have improved their acumen. They measure and build 15. AI Talent Strategy: Organizations have responsible data and AI practices expertise in critical areas like coding, an AI talent strategy—hiring, acquiring, between 2018 and 2021, effectively data processing and exploration, retention—that evolves to keep pace translating into a higher data and business analytics, domain and with market or business needs. They AI maturity. business acumen, machine learning, also have an AI talent roadmap for visualization and more. hiring diverse AI-related roles, beyond The art of AI maturity—Advancing from practice to performance 38