Don’t feel AI envy—what truly matters is that you're on your AI journey, regardless of where you currently stand.
Debasis Dutta, Senior Vice President and Head of Codecademy Enterprise Solutions at Skillsoft, shared this wisdom during this week’s VB Transform conference in San Francisco.
Dutta emphasized the importance of the journey itself: “It is the journey you are on. Just accept where you are, learn more, assess your potential, and focus on business outcomes.”
He outlined four phases of AI maturity for attendees: exploration, experimentation, innovation, and realization. Regardless of your enterprise's current stage, Dutta asserted, “What matters is that you address the different elements needed for success at each phase.”
1. Exploration: This initial phase focuses on identifying use cases, scenarios, and real-life examples that highlight the challenges AI seeks to resolve. Every enterprise has unique needs, necessitating a careful evaluation of AI tools, capabilities, and parameters.
2. Experimentation: During this phase, AI tools come into play, prompting leaders to identify processes requiring change. Establishing guidelines and governance models is crucial to prevent unauthorized actions, Dutta explained. Ongoing assessment is vital: Is AI performing as expected? Is the organization gaining traction? Are there viable solutions for identified problems using generative AI?
3. Innovation: In this phase, AI begins to integrate into the organization's DNA, ideally to the point where its presence is seamless and no longer a concern.
Dutta noted that timelines for these phases vary—some enterprises might spend a few weeks in experimentation, while others may linger for months.
Change Management and Skilling Are Essential for Success
A key factor that must be addressed from the outset is change management. “Change management is challenging, and it’s critical to tackle it first,” Dutta stressed.
Skillsoft has trained over 1 million learners in AI and generative AI in the past two years, working with significant partners like Microsoft, AWS, and Cisco. Dutta mentioned that many partners request their CEOs and C-suite executives undergo training first to demonstrate lead-by-example principles.
Reskilling and upskilling throughout the organization are non-negotiable, Dutta emphasized. The training should be intentional, interactive, and supported by a generative AI-powered platform.
“A holistic skilling development program is essential to accelerate your AI maturity model,” he advised. Tailored learning journeys help assess employee needs and aspirations while aligning with organizational goals. Progress must be effectively measured; leaders should test skills post-training, evaluate metrics, and confirm that employees are adeptly using AI in their daily tasks.
“You must benchmark their skills and reassess regularly,” Dutta noted.
Hands-on practice is crucial. While theoretical learning through videos is valuable, “unless you actively engage with the tools, you won’t truly understand their effectiveness,” he stated.
Ultimately, the process must be holistic and top-down. “Just sending people to a skilling program won’t suffice; you need a clear business outcome in mind. Testing, measuring, and program management are essential,” he said. Establishing success criteria is key.
Internal promotion and effective communication are also vital for stakeholder management. Dutta observed that skepticism and resistance are common, prompting essential conversations.
“Understand what people truly need,” he advised. “Are they anxious about AI? What tools can you provide to support their journey?”
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