In Psychology, there is an effect called the Michaelangelo effect. The Michelangelo Effect is named after the famous Renaissance artist Michelangelo Buonarroti, who described his sculpting process as “liberating the statue that already existed within the marble.” The Michelangelo Effect in business emphasizes the transformative power of supportive relationships between leaders, employees, and teams, where individuals are encouraged and guided to realize their potential and achieve their ideal professional selves. For example, a manager who identifies an employee’s aspiration to become a leader can provide mentorship, assign stretch projects, and offer constructive feedback to help the employee build the necessary skills.

The Michelangelo Effect is crucial for AI transformation. It helps employees align their growth with new, AI-driven roles, fostering adaptability and engagement. Companies can ensure smoother transitions and maximize workforce potential by supporting individuals in developing skills and mindsets for the AI age.

We are observing a trend in which companies, in addition to establishing standalone AI teams, are focusing on embedding and amplifying AI capabilities across all teams. Look at this graph, for example.  This graph illustrates a clear trend where the demand for AI-related skills has increased steadily over time while the demand for AI-specific job titles has remained relatively consistent. The Skills-based search data shows a higher percentage of job postings both globally and within Fortune 500 companies, with a gradual upward trend, particularly since 2021. In contrast, the Job Title-based search data reflects minimal growth, indicating a focus on integrating AI capabilities across roles rather than creating standalone AI roles. This shift suggests that organizations are embedding AI competencies within diverse roles instead of relying solely on dedicated AI positions. The data source is Draup, which tracks job postings over six years, highlighting this evolution in organizational AI strategies.

This shows that companies are embedding AI skills across Jobs rather than opening dedicated AI jobs.

Here is a sample list of Roles, Workloads, and Possible Tools across various jobs

Summary:  Draup observes a strategic shift in how enterprises approach AI. Instead of solely focusing on building AI Centers of Excellence (COEs), companies are increasingly embedding AI skills across a wide range of roles. This marks an exciting evolution in the adoption of AI capabilities.