How to explain agentic AI to your leadership team, from Ashley Nicholson[1]:
It's not one, single tool. It's layers of capability.
Here are 5 levels that will determine who wins in 2026:
- Machine Learning:
- Turns data into decisions.
- Forecasts sales, detects fraud, and can predict churn.
- It can optimize pricing automatically.
- Tools: AWS SageMaker, Google Vertex AI, Azure ML.
- Neural Networks & Deep Learning:
- Complex pattern detection at scale.
- Inspects quality with computer vision.
- Powers voice commands and document processing.
- Enables facial recognition systems.
- Tools: TensorFlow, PyTorch, AWS Rekognition.
3. Generative AI
- Generates content and code at scale.
- Drafts marketing content and automates meeting notes.
- Builds knowledge bases and generates code.
- Creates product images instantly.
- Tools: ChatGPT, Claude, Gemini, Midjourney.
- AI Agents:
- Execute complex tasks autonomously.
- Handle IT tasks and generate leads.
- Process customer requests independently.
- Research topics without human input.
- Tools: LangChain, CrewAI, Microsoft Copilot.
5. Agentic AI:
- Networks of agents that collaborate autonomously.
- Modernizes legacy software systems.
- Builds AI into products seamlessly.
- Orchestrates end-to-end processes.
- Tools: Claude Code, OpenAI Codex, Devin.
Here's why this matters:
You can't skip they layers. Each one builds on the previous. Most companies are stuck at layer 1 or 2. While their competitors race to layer 5.
Here's the difference:
- Machine Learning analyzes and predicts.
- Neural Networks recognize patterns.
- Generative AI creates content and code.
- AI Agents follow through and execute multi-step tasks.
- Agentic AI runs entire processes.
- Leaders who understand this stack will dominate 2026.
Those who don't will unfortunately be left behind.
This article is shared at no charge for educational and informational purposes only.
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[1] https://www.linkedin.com/posts/ashley--nicholson_how-to-explain-agentic-ai-to-your-leadership-share-7498723238064103424-Es0b/
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