AI Without the Hype: Practical Ways AI Can Help Your Business
Today, I had the pleasure of speaking at Meet Mayo in Ballinrobe Racecourse. My talk was all about cutting through the AI noise and focusing on what really matters: how AI can make a tangible difference to your business.
Let’s face it, we’re bombarded with AI hype every day. It’s easy to get lost in the buzzwords and grand promises. But here’s the thing – AI isn’t magic. It’s a tool. A powerful one, sure, but still just a tool. The key is knowing how to use it effectively.
In my talk, I shared some practical ways businesses can leverage AI today. No sci-fi stuff, just real-world applications that can save you time and money. Here’s a quick rundown:
One of the key points I emphasised is the massive disconnect we’re seeing in businesses. Employees are using AI a lot, but employers often aren’t being told about it. There’s literally no incentive for employees to talk about it, and plenty to lose – fear of punishment, job cuts, increased workload, you name it.
This is a problem because companies are missing out on huge opportunities for improvement. We need to bring AI into the open, provide training, establish clear policies, and normalise its usage.
I also introduced RAG – Retrieval Augmented Generation – as the killer app of AI for 2024. It’s a game-changer that enables AI to access your documents and data, generating responses tailored specifically to your business.
But the real value comes from finding the right use cases for AI in your business. It’s not always straightforward, but it’s worth the effort. I shared my COMPLETE™ framework for evaluating tasks suitable for AI automation:
- Complexity: How hard is it to automate
- Occurrence: How often it’s done
- Monetary cost: Time and money spent
- Priority to clients: Importance of human touch
- Likability: Employee enjoyment level
- Error reduction: AI vs human accuracy
- Time savings: Potential efficiency gain
- Efficiency: Overall improvement
I also shared some of my personal use cases, from processing meeting transcripts to generating on-brand images and even real-time voice translation.
Remember, you’ll find use cases when you start using AI tools in earnest, not before. It comes back to experimentation, training, and creating a culture of acceptable use.
Finally, I introduced the GOAL framework for talking to AI:
- G – Goal: Define what you want to achieve
- O – Output: Specify the format and style
- A – Additional Context: Provide relevant background information
- L – Look at the Output: Review and refine
If you’re new to AI interested in exploring more about how it can help, check out my . It’ll help you learn what you can put into AI, and what you should not.
