Enable has no dependency on Launchpad or Custom; it stands on its own, for any organization that wants its team using AI well before, alongside, or instead of any other engagement. Training here does three distinct things:
Literacy
People actually know how to use AI tools well and responsibly, not just how to click through them.
Shadow AI protection
A 2025 ManageEngine survey of IT decision-makers and employees found the two groups read the same behavior in nearly opposite terms: 97% of IT leaders considered shadow AI (the unsanctioned, ungoverned use of AI tools) a significant risk, while 91% of employees rated it as no risk, minor risk, or a risk worth the convenience. That gap isn't recklessness. It's people who don't know that pasting a document into a public AI tool, or connecting an unapproved app to company data, creates any risk in the first place. Training closes that gap by building understanding, not by adding a policy for someone to work around.
Discovery
Training built around your actual roles, workflows, and systems surfaces which tools and use cases would genuinely help your business.
Four Pathways, One Progression
All four pathways are tailored to the organization receiving them, and fully custom curriculum development is available where specific tools, data policies, or use cases call for it.
Foundations: Core AI Essentials
A shared understanding of AI across the organization.
Acceleration: Functional AI Applications
Moving from awareness to practical impact, with training specific to your team's roles, departments, and industry.
Engineering: AI Systems & Platforms
Enabling technical teams to design, build, and operate AI capability at scale: architecture, data pipelines, platform selection, AI security, and cost governance.
Leadership: AI Strategy & Governance
Equipping senior decision-makers to evaluate AI opportunities, manage risk, establish governance frameworks, and build a sustainable roadmap for AI-driven initiatives.
From Training to Implementation
The tailored training in Enable surfaces genuine AI use cases specific to your business, a direct result of how the training is built rather than an incidental benefit. Those use cases are ranked by impact and feasibility, the highest-priority ones move into an MVP for testing and refinement, and validated results move to full deployment. Where that path requires further engineering, it continues directly into Katalyst Blueprint™, informed by what the training already established.
