Training Leaders: How to Think Practically About AI and What You Can Do with it Right Now

If you're a learning or training leader trying to make sense of Artificial Intelligence, you're not alone. 

We are in one of the most transformative periods in modern work, yet many organizations remain stuck—unsure how to get started or what “good” looks like when it comes to AI. 

My goal with this article is simple: to offer a practical, clear-headed way to think about AI—one that gives you the confidence to act, and more importantly, to act sooner rather than later. The next 6-18 months will determine who leads and who plays catch up. And the good news? You don’t need to boil the ocean to get moving.

But let me be clear—if your next incident isn’t just a fluke, but a training failure, can you afford to wait? In safety-critical industries, the cost of outdated training isn’t inefficiency—it’s incidents, violations, and irreversible mistakes. That’s why AI isn’t optional—it’s now essential. 

Let me show you how. 

A Simple Framework to Understand AI 

At Realizeit, we use a three-layer framework to make AI understandable and actionable. Each layer builds on the previous one and expands its impact. 

1. Generative AI: Do This for Me Now 

This is what most people think of today when they hear “AI”—tools like ChatGPT that produce content or perform tasks based on a prompt. Generative AI (GenAI) is command-and-response based. You tell it what to do or what you want, and it gives you something back.

Where it helps: It’s a powerful augmenter of human productivity—speeding up research, analysis, recommendations, content creation, content editing, summarization, and more.

What to know: You still must know what to ask GenAI to do in the first place. GenAI is an assistant to you. Value depends on your ability to frame good prompts and use the output wisely. 

2. Agents: Do This for Me Repeatedly 

Agents are different. Rather than waiting for you to prompt them, agents are configured to perform tasks continuously inside workflows. Think of them as AI employees with a specific job description—they know what to do, when to do it, and they get it done.

Where it helps: Agents free you and your team from repetitive, manual work. They automate quality checks, generate assessments, monitor completion, and much more—without needing to be prompted each time. This is a tremendous productivity enabler.

3. Agentic AI: Think and Act for Me 

Agentic AI is the next frontier. These systems go beyond simple and narrow automation—they autonomously reason, plan against goals, take necessary actions and often orchestrate multiple agents with limited human guidance. They understand context, anticipate needs, and execute. Think of this as hiring a new capable team member, not just a tool.

Where it helps:  Agentic AI doesn't just improve your workflow—it redefines it. You move from orchestrating tasks to enabling outcomes. More outcomes can be accomplished with fewer human resources. 

In short:

• Generative AI improves individual tasks. 
• Agents improve the efficiency and output of workflows.
• Agentic AI transforms how work gets done.

And here’s what makes this framework even more compelling: recent meta-analyses by McKinsey and MIT Sloan confirm what we’ve long practiced at Realizeit—AI’s true potential lies not in one-off automation, but in orchestrated, outcome-driven transformation. Dive into the study here. 

Where to Focus Now: Productivity Inside Your Workflow

While Agentic AI holds incredible promise, the most immediate ROI comes from improving productivity inside your existing workflows—especially in training and learning. 

This isn’t about marginal improvements. This is about: 

• Reducing costs by orders of magnitude.
• Accelerating delivery by 2–5x.
• Raising quality beyond human-only output. 

If you’re leading training or learning functions, here’s what this means for you: 

• Build and update materials faster. AI can generate relevant draft content, align it to objectives, and reduce rework. 
• Personalize at scale. Without adding headcount, you can deliver training tailored to each person’s knowledge, gaps, and context. 
• Automate assessments and verification. Know what people know, don’t know, and fill in gaps quickly, with confidence. 
• Deliver just-in-time guidance. Employees get coaching and support in the flow of work—not in separate learning environments. 

And this is not theory—it’s operational. At Realizeit, these AI layers aren’t aspirational—they’re embedded. 

How We Apply AI at Realizeit 

Where We Started 
Realizeit was built from day one to be intelligent. Our adaptive engine self-calibrates, personalizes content, and continuously learns from each user. In today’s terms, that makes it inherently “agentic”—capable of acting at scale without needing constant human oversight. 

Where We Are Today 
Right now, Realizeit equips you with embedded AI that: 

• For employees: Detects what they know, pinpoints gaps, and focuses their effort only where needed—building skill and confidence faster.
• For instructors and managers: Automates content creation, provides real-time visibility, and surfaces actionable insights.
• For training teams: Automates the “build, operate, manage” cycle—dramatically reducing the manual burden of training delivery. 

Whether you're a mine manager assessing underground readiness, a pharma QA lead responding to FDA updates, or a financial services director ensuring frontline compliance, AI must adapt to your environment—not the other way around.

Where We’re Going Next 

  We’re doubling down on two major paths: 

• Expanding AI across operational workflows for structured training and verification — Making it dramatically easier to build, manage, and scale training and verification programs with significantly reduced human effort.
• Extending structured training with continuous, in-the-flow enablement using AI — Imagine each employee equipped with a digital coach post-training that anticipates needs, supports in real-time, and improves employee performance on the job. 

And we are designing these systems with the necessary guardrails and governance for humans-in-the-loop to easily monitor and control the AI autonomy. 

Why This Matters 

Training and learning functions are evolving into performance enablement and operational assurance. 

• Stop overwhelming new hires—distribute learning over time, intelligently.
• Stop pulling employees away for training—embed it in the job.
• Stop acting as a content factory—start building operational capability.

At Realizeit, this isn’t future-state. This is now. Our customers—like Disney, Maximus, and AstraZeneca—are already seeing the impact.  

The AI conversation is full of hype. Our advice? Ignore it. 

Instead, focus on value:

• What tasks can be accelerated?
• What workflows can be simplified?
• What outcomes can be improved? 

Start there. Start now. 

If your current training system can’t tell you who’s truly job-ready—and what to do about those who aren’t—you’re not just behind. You’re exposed. Let’s fix that. Schedule a Realizeit strategy session today. 

Let’s build the future of performance enablement—together.