Jul 31st, 2025
Tech Spotlight
Making Sense of AI
Written by: David Stevens, Director of Business Development
The roots of modern AI go back farther than most realize. Before ChatGPT or Microsoft Copilot hit the headlines, businesses were already using machine learning (ML) to detect fraud, forecast sales, and personalize customer experiences. Natural language processing (NLP) gave computers the ability to understand and respond to human language. And large language models (LLMs) became the basis behind many of today’s smartest systems.
But in the current business climate, AI is the fastest-moving, most-hyped technology in IT, and for good reason. The pace of innovation is staggering, and the pressures to “do something with AI” is hitting every business differently.
If you haven’t had a chance to step back and think through how AI might apply to your business, the options can feel overwhelming. That’s because AI isn’t just one thing anymore. It’s many. And the way businesses adopt it depends heavily on what they’re looking to accomplish.
What follows is my take on the main branches of AI we’re seeing in practice today. It’s by no means a complete list, but I hope it can provide a helpful starting point for thinking about where each type fits and which one makes sense for your goals.
Generative AI
This is the one everyone’s experimenting with. It creates text, images, code, etc. all from scratch, simply based on prompts. Think ChatGPT, DALL·E, or GitHub Copilot. It’s built on LLMs and ideal for brainstorming, summarizing, content generation, or accelerating repetitive work that benefits from a human touch.
When to use it: You want to move faster on creative, language-heavy tasks — from content creation and documentation to brainstorming or customer communication. A human still guides the output, but the AI handles the heavy lifting.
Predictive AI
This is where machine learning shines. Predictive AI leverages historical data to forecast outcomes. Things like customer churn, equipment failure, or sales numbers.
When to use it: You have structured data and need insights to help you plan ahead, spot risks, or make more confident decisions.
Conversational AI
Often powered by the same LLMs as generative tools, conversational AI is built to simulate human dialogue. This includes chatbots, voice assistants, and customer service agents.
When to use it: You want to grow your business’s ability to interact and communicate with customers and employees without growing your headcount. Deliver faster responses, 24/7 availability, and a more engaging experience at scale.
Agentic AI
This is the next frontier. Instead of simply generating answers, Agentic AI can take actions. These systems can reason through tasks, make decisions, and operate across apps or systems on your behalf. Think of it as an autonomous co-worker that handles the repetitive multi-step work so your team doesn’t have to.
When to use it: You need to automate entire workflows like onboarding, document retrieval, or case routing without human intervention at every turn.
The AI landscape is evolving fast, but clarity comes when you focus less on the hype and more on the problem that you’re trying to solve. Whether it’s generating content, forecasting outcomes, improving communication, or automating workflows, each branch of AI brings distinct strengths to the table. The key is to start with your goals, then find the AI that’s right for you.
Looking for more insights? Use the button below to contact us.