Debasis Dutta from Skillsoft outlines four key phases of AI maturity and emphasizes the need for change management and skilling to ensure success.
The four phases of AI maturity: Dutta describes the AI journey as consisting of exploration, experimentation, innovation, and realization, stressing that it doesn’t matter which stage an organization is in, as long as they are making progress:
- Exploration involves identifying use cases, scenarios, and real-life examples, as well as outlining the challenges AI is intended to solve.
- During the experimentation phase, organizations begin using AI tools and establishing guidelines and governance models to ensure proper usage.
- Innovation occurs when AI starts making a real difference within the organization.
- Ultimately, the goal is for AI to become an integral part of the organization’s DNA.
Change management and skilling are essential: Dutta highlights the importance of addressing change management from the very beginning and the need for reskilling and upskilling employees:
- Some of Skillsoft’s partners have requested that their CEOs and C-suite executives be skilled first to lead by example.
- A holistic skilling development program based on a generative AI-powered platform is crucial for accelerating an organization’s AI maturity.
- Tailored learning journeys help meet workers where they are and assess their progress, ensuring they can effectively use AI in their day-to-day tasks.
Broader implications: The article emphasizes the significance of embracing AI technologies and the need for organizations to adapt and evolve their workforce to keep pace with these advancements. By focusing on change management, skilling, and a structured approach to AI adoption, organizations can successfully navigate their AI journey and reap the benefits of these powerful technologies.
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