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Think Big, Act Small: What Is Agentic AI and AI Distillation?
With all the recent hype around DeepSeek and what makes it different from ChatGPT, Claude, Gemini, or Concentrix’s own iX Hello™, the conversation around AI has shifted in a fundamental way. The concept of AI distillation and small language models has people asking “Can AI do this specific thing?” versus “What are all the things AI can do?”—and that’s an important distinction.
We’ve been asking that first question for as long as AI has been in the market, and it’s what led us to explore the possibilities of agentic AI. Both AI distillation and agentic AI represent breakthroughs in leveraging AI for diverse business needs, yet they serve distinct purposes and use cases.
In this article, we’ll break down the differences, explore their unique roles in the AI landscape, and discuss how businesses can harness these technologies to drive efficiency and innovation.
AI Distillation Explained
AI distillation, perhaps better understood as knowledge distillation, is a machine learning technique where knowledge from a large, complex model is transferred to a smaller, simpler model. The idea is simple yet powerful—distill large volumes of AI-generated data into more focused and actionable knowledge.
The process aims to retain the performance of the large language model (LLM) while making the small language models (SLMs) more efficient and able to run on less powerful hardware. In addition, AI distillation uses these SLMs to train one another, enabling a perpetual optimization loop.
This ability to distill 975 trillion parameters of data into 7 billion is what allowed DeepSeek to run faster and cheaper.
What Are AI Agents and Agentic AI?
If you think in terms of outputs, AI distillation is all about providing specific answers, while AI agents are about performing specific actions. We’re talking about an intelligent system designed to take inputs, process those inputs with contextual understanding, and execute specific tasks.
Agentic AI takes this concept a step further. It focuses on multi-agent orchestration, enabling multiple AI agents, each specialized in distinct tasks, to collaborate dynamically. Instead of asking one AI agent to do all these tasks at once, which requires a massive amount of power to process those trillions of parameters, you have that agent call upon a team of specialty agents that only need to process a much smaller subset of data.
This, in a nutshell, is what iX Hello is designed to do.
The Role of Agentic AI in Business
Agentic AI is particularly transformative across functions such as customer experience, supply chain management, and marketing. By employing multi-agent orchestration, companies can ensure specialized agents handle distinct tasks seamlessly. Take arranging a family vacation for example:
- A booking agent for airlines arranges tickets for your family, based on the number of people, their ages and seat preferences, and the anticipated amount of luggage.
- A reservations agent for car rentals books your vehicle based on your preferred vehicle type and the company you use most often.
- A different reservations agent for hotels books your stay based on the number of people, their ages, your room preferences, and the hotel you stay at most often.
- A loyalty agent manages and redeems your user rewards for the airline, car rental, and hotel to maximize your rewards.
- A payment agent steps in only when a transaction is required to arrange your payment or down payment and payment plan based on your selections.
An orchestration agent ties it all together, ensuring these agents communicate effectively, coordinate details, and follow a logical workflow. This approach prevents chaos or confusion by aligning agent abilities with user intents, mirroring how humans operate in a team where everyone has a defined role.
How Does Agentic AI and AI Distillation Help My Business?
Both Agentic AI and AI distillation offer incredible benefits when applied thoughtfully, and the combination of the two takes thinking big and acting small to the next level:
- Customer service and CX: Modern CX strategies leverage AI distillation to refine user data while using agentic AI to deploy specialized bots or agents. These agents focus on core CX objectives such as sentiment analysis, fraud detection, and personalized interactions.
- Healthcare: AL distillation methodology could be critical for summarizing complex patient data, while agentic AI orchestrates tasks like appointment scheduling, insurance verification, and prescription renewals. This creates a tightly integrated and responsive care ecosystem.
- Marketing campaigns: Agentic AI is transforming how companies strategize by delivering actionable insights to improve campaign focus. Meanwhile, distillation ensures sharper, more targeted advertising recommendations with minimal human intervention.
What’s Next? The Future of Agentic AI & Distillation
The integration of AI distillation into agentic AI systems is the natural next step. This union promises dynamic, adaptive AI models capable of enhancing their own workflows. The true potential with AI distillation is its closed feedback loop, which allows these systems to learn, refine, and scale as data continues to grow. With agentic AI, it’s the rise of hyper-specialized agents that will transform business, focusing on niche areas that can’t afford dedicated human advisors, and amplifying efficiency across functions.
Together, they will allow business to work faster, better, and easier, with a drastically reduced need for technology or demand upon resources. Whether your business is optimizing workflows or redefining customer experiences, incorporating AI technologies like agentic AI and AI distillation isn’t optional—it’s essential.
Want to explore what AI can do for your business operations? Sign up for an iX Hello demo and experience how thinking big and acting small can expedite your transformation in ways you’ve never imagined.
Shawn Ennis
Director, Emerging Technologies
