AI Education in the Enterprise

AI model advancements and agent capabilities will force a radical transformation of talent, teams, and organizational structures.

While many organizations are still trying to enable and teach the most basic AI assistant functions in ChatGPT, Claude, Copilot, and Gemini, the AI labs are racing ahead.

We must build on proven approaches to learning and development to reskill and upskill workforces at the speed the market and the technology demand.

Dynamic Learning Is the Essential Path Forward

This requires a foundation of dynamic learning and personalized journeys.

This is the premise of an essay I published this week titled, “AI Education in the Enterprise.”

Providing access to AI tools and course catalogs is not enough to drive people toward competency and mastery that grow their careers and organizations.

Dynamic learning continuously adapts to technology and organizational changes, as well as the learner’s AI literacy, role, goals, and progress.

In short, dynamic learning delivers the right knowledge and skills to the right person at the right time, continuously adapting as the learner—and the world around them—changes.

Why is dynamic learning essential in the AI age?

Consider a snapshot of AI advancements over just the last two years that completely altered what was possible with AI, and how it should have been taught within enterprises:

• September 2024: OpenAI introduces o1, the world’s first publicly available reasoning model. AI could now support more complex problem-solving and decision-making.
• Winter 2025: Advancements in AI agent capabilities, specifically related to Claude Code and OpenClaw, demonstrate the near-term potential for agents to perform long-horizon tasks that would take humans hours or days.
• August 2026: Hugging Face discloses it had been hacked by OpenAI agents that escaped containment in testing, showing the risks and opportunities of agent swarms to collaborate (and conspire).
• September 2026: Multiple AI leaders and labs claim the latest AI models, such as GPT-6 Astra, have achieved artificial general intelligence (AGI). While it is a broadly debated term, it roughly means that the AI models are on par with (or superior to) the average human worker at most cognitive tasks.

In addition, despite calls for regulation and “pacing” AI research and development, the AI labs are locked in a competitive battle resulting in new state-of-the-art frontier models being released every 2-3 months.

The rate of releases drives confusion and uncertainty for business leaders, and leads to constantly shifting user experiences in leading AI platforms as the labs attempt to productize and market their innovations.

Organizations have the opportunity to rapidly evolve and strengthen their learning and development programs with the right technology, curriculum, and applied experiences.

See the full essay for more details, and how we’re planning to evolve AI Academy by SmarterX to meet the moment.

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