Tired of nodding along in meetings when AI terms get thrown about? Here’s your no-nonsense guide to understanding AI speak – decoded into plain English for busy business leaders.
Ever sat in a meeting where someone’s talking about AI and found yourself wondering if they’re speaking English? You’re not alone. Let’s translate the tech talk into something that actually makes sense for your business.
The Basics: Essential AI Terms You’ll Hear Everywhere
What They Say vs. What They Mean
Artificial Intelligence (AI)
- What they say: “A computer system that can perform tasks that normally require human intelligence.”
- What it actually means: A clever piece of software that learns from information and makes decisions or suggestions – like a very efficient assistant who gets better at their job over time.
- Real example: Think of Netflix suggesting shows you might like based on what you’ve watched before.
Machine Learning (ML)
- What they say: “A subset of AI that enables systems to learn from data without explicit programming.”
- What it actually means: Software that spots patterns in your business data and uses them to make predictions or decisions.
- Real example: Your local supermarket forecasting how many sandwiches to make for lunch rush based on previous sales, weather, and local events.
Algorithm
- What they say: “A set of mathematical instructions or rules that helps solve a problem or complete a task.”
- What it actually means: A recipe that tells the computer what to do with your information.
- Real example: Like having a very detailed checklist for sorting through customer emails and routing them to the right department.
AI Terms by Business Function
Customer Service AI
Natural Language Processing (NLP)
- The fancy term: “Technology that helps computers understand and interpret human language.”
- In plain English: Software that understands what your customers are asking, even when they word it differently.
- Cost context: Basic chatbots with NLP start from £50/month; more sophisticated systems range from £200-500/month.
Sentiment Analysis
- The fancy term: “The process of determining the emotional tone behind words.”
- In plain English: Software that can tell if your customers are happy, frustrated, or angry in their messages.
- Real impact: A local hotel uses this to spot unhappy guests and fix problems before they hit review sites.
Marketing and Sales AI
Predictive Analytics
- The fancy term: “Using data, statistical algorithms and machine learning to identify future outcomes.”
- In plain English: Using past information to make educated guesses about what might happen next.
- Real example: A Brighton boutique predicting which clothes will sell best next season based on past sales and fashion trends.
Customer Segmentation
- The fancy term: “The practice of dividing customers into groups based on common characteristics.”
- In plain English: Automatically grouping your customers based on their buying habits and preferences.
- Practical use: A local gym using this to send different offers to early morning versus evening exercisers.
Red Flags: When to Be Skeptical
Buzzwords That Should Make You Pause
“AI-Powered” Everything
- What they claim: “Our solution is fully AI-powered!”
- Reality check: Ask what specific tasks the AI actually performs. Sometimes it’s just basic automation wearing a fancy hat.
- What to ask: “Can you give me a specific example of how the AI makes decisions in this system?”
“100% Automated”
- What they claim: “No human intervention needed!”
- Reality check: Good AI usually works alongside humans rather than replacing them completely.
- What to ask: “What happens when the system encounters something it doesn’t understand?”
Price-Related Terms to Understand
“Per User Pricing”
- What it means: You pay for each person who uses the system.
- Watch out for: Hidden costs for admin users or viewing-only access.
- Better alternative: Look for “per business” or “per location” pricing for small teams.
“Processing Credits”
- What it means: You pay based on how much you use the AI.
- Watch out for: Unexpected spikes in usage that could blow your budget.
- Tip: Ask for usage estimates based on businesses similar to yours.
A Simple Framework for Evaluating AI Solutions
Before Signing Up, Ask These Questions:
1. Data Questions
- What data will it need?
- Where will the data be stored?
- How is the data protected?
2. Cost Questions
- What’s included in the base price?
- What might trigger extra charges?
- What’s the minimum contract length?
3. Support Questions
- Who helps if something goes wrong?
- Is training included?
- What’s the response time for problems?
How to Sound Knowledgeable (Without Being Pretentious)
Good Questions to Ask Vendors:
- “How does the system learn from our specific data?”
- “What kind of results have similar businesses seen?”
- “Can you walk me through a typical user journey?”
Questions to Avoid:
- Don’t ask: “Is it AI-powered?”
- Instead, ask: “What specific tasks does it automate or improve?”
The Bottom Line: Keeping It Real
You don’t need to become an AI expert – you just need to understand enough to make good decisions for your business. Think of it like buying a car: you don’t need to understand how the engine works, but you do need to know what questions to ask and what features matter for your needs.
Quick Reference: The Only Terms You Really Need to Know
- AI = Smart software that learns and improves
- Machine Learning = Pattern-spotting technology
- Automation = Tasks done by computers instead of people
- Analytics = Making sense of your business data
Need help cutting through the AI jargon for your specific business? Book a free, plain-English chat with our team. We promise not to use any buzzwords without explaining them first! Book Your Free Consultation