Most business leaders today would confidently say they know what AI is.
You’ve heard it in every strategy meeting, seen it on every software pitch deck, and probably even used a tool or two with “AI-powered” slapped on the label. But here’s the thing: while everyone is talking about AI, many of us still cannot really wrap their head around it or talk about it clearly.
There still seems to be a lot of confusion, for example people still seem to confuse business automation and artificial intelligence. Spoiler alert… they are not the same.
How about we clear up a few things here?
Firstly…
Automation is not the same as AI (…but AI can supercharge Automation)
Business automation is about setting up rules that say: ‘If X happens, then do Y.’
A certain activity automatically triggers another activity. For example, automatically assign a sales rep based on region, or automatically send a follow-up email three days after a call. Super powerful, and with the potential to save you and the team a lot of time - but it’s not ‘thinking.’
AI, on the other hand, is the ‘thinking’ part. It is about learning from data, and making decisions based on data, mimicking human intelligence. It can find patterns, make predictions, and generate responses – not just follow preset rules.
AI therefore is not the same as automation, and it also does not replace automation; but it does makes it smarter. AI identifies what to do and then Automation carries it out – a dream team really!
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Diving a bit deeper into AI, there is a growing family of tools and terms I think are worth knowing. Here’s a quick breakdown:
Generative AI – The one you (hopefully) already use
This is the big one. Tools like ChatGPT, Gemini, Copilot, Perplexity, Midjourney or DALL·E all fall under this category.
Generative AI means AI that can create new things—writing, images, code, video, music—based on patterns it has learned from existing data (mostly the open web). If you’ve ever asked AI to draft an email, rewrite a proposal, or suggest an ad copy; you’ve used generative AI. And if you are not using it in your day-to-day yet… well, let’s have a chat.
⚠️ IMPORTANT: not all generative AI tools are created equal—especially when it comes to data privacy ⚠️
Many open-source or free models don’t offer clear guarantees around where your data goes, how it is stored, or who can access it. This could be a risk if you decide to feed in client info, internal strategies, or anything commercially sensitive.
As a business, make sure you choose paid or enterprise-grade tools that offer clear privacy terms, and make sure your team understands what should and shouldn't be shared with AI tools.
NLP (Natural Language Processing) – How AI understands you
NLP bridges the gap between human conversation and machine logic. It is what allows machines to understand human language, and the reason AI can read an email, summarise a document, or reply to your question in plain English.
Think Siri or Alexa, both use NLP to understand your commands and questions. Or when you type “show me last quarter’s deals” into your CRM and it knows exactly what to pull; that’s NLP at work.
NLP underpins most AI-driven sales tools, support chatbots, and even CRM assistants that can pull insights from messy notes or call transcripts.
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Chatbots vs AI Agents – There’s a BIG difference
Here’s where it gets interesting…
A chatbot (you know, that little pop-up in the bottom-right corner of a website) is typically rule-based and follows a script. It might answer FAQs, help you track an order, reset a password, or hand off to a human when it gets stuck. Super useful… and at the same time quite limited. It doesn't really think, and it certainly doesn’t learn.
The AI agent on the other hand, is a whole different beast. It understands context, can handle more complex conversations, ask follow-up questions and most importantly take action. For example, an AI agent can update your CRM based on a conversation, schedule a meeting in your calendar, draft a follow-up email and log it, pull in data from multiple systems and even learn your preferences over time.
It’s not just chatting; it’s collaborating.
Another way to look at this: a chatbot is like a polite person answering your call and following a script. The AI agent on the other hand is your operations-savvy employee who not only understands what you want, but knows where to find the info, how to act on it, and when to keep you in the loop. BOOM!
I think this is an area that could separate teams who are using AI from those who are actually benefiting from it.
🚀 You might also like: The Future of Pipedrive: How AI is Revolutionising Sales Automation
API – the term that makes it all work
You’ve probably heard someone say this before: “We integrate via API.”
API stands for Application Programming Interface, which is a fancy way of saying, here’s how two tools talk to each other behind the scenes.
But, why does this matter for AI? Well, your AI tools are only as good as the data they can access. APIs are the bridge that connect your CRM to your email platform to your website to your AI engine. Without APIs, you end up with silos. With APIs, you’ve got flow.
Tools like Zapier and Make can make it even easier to connect the dots. They are like the universal remote controls for your software stack.
🚀 You might also like: The Integration Advantage: Expanding Pipedrive's Functionality with Powerful Tools
Final Thoughts
The buzzwords aren’t going away. But as business leaders, our job is to cut through the noise, to spot the fluff, act on the real stuff, and turn the AI hype into hard results.
If your team is still just scratching the surface of AI, now is the time to start testing, exploring, and integrating. Not because it’s trendy… but because the businesses who understand and act now are more likely the ones that will win later.
Still unsure? Let me know which terms still feel fuzzy or what you would like to see demystified.
