Why Your Business Is Using a Ferrari to Drive to the Corner Shop
Last week, I watched my colleague spent two hours setting up ChatGPT to write a simple "out of office"
Last week, I watched my colleague spent two hours setting up ChatGPT to write a simple “out of office” email. The same task would have taken three minutes with a basic template. It got me thinking about something AI researcher Karen Hao said recently in a video that perfectly captures what’s happening with AI tools for business right now.
She compared AI to transportation. Just like transportation can mean anything from bicycles to rockets, AI covers everything from simple automation to complex neural networks. But here’s the problem: we’re treating all AI like it’s the same thing.
Imagine if someone told you they needed “more transportation” to reduce their carbon footprint. You’d immediately ask what kind, right? A bicycle? Public transport? Because suggesting everyone commute by rocket ship would be mental. Yet that’s exactly what many companies are doing when choosing AI tools for business.
The Rocket Ship Problem
Many organisations are now implementing massive AI systems to tackle problems that a simple spreadsheet formula could easily handle. It is like taking a Ferrari for a quick trip to the corner shop for milk. Impressive, but costly and unnecessary. As Karen Hao explains, “When you’re giving people tools for free with regards to generative AI to just generate stupid images of nonsense, that’s kind of what we’re doing, right? It’s like saying, ‘Let’s use a rocket to get from Dublin to London to Paris.’”
The environmental impact alone should raise concerns. According to a recent McKinsey report, the current trajectory of AI expansion will demand an additional half to 1.2 times the UK’s annual energy consumption in just five years, with most of that load driven by fossil fuels.
Examples are easy to find. Some companies deploy advanced AI to write simple customer service responses, when a basic template system would achieve the same outcome at no cost. Others feed customer data into complex machine learning models to predict buying patterns, when last year’s sales data provides nearly identical insights. These tools work, but it is often the equivalent of hiring a brain surgeon to apply a plaster.
The Hidden Costs Everyone Ignores
Beyond the obvious expense, there are costs most businesses don’t consider. AI data centres need fresh drinking water for cooling. In some places, this is literally taking water away from communities that don’t have enough for people to drink safely.
That simple ChatGPT query uses significantly more energy than a Google search. When your simple processes rely on complex AI systems, you’re vulnerable to outages, price changes, and service discontinuation. Learning to prompt AI properly often takes longer than just doing the task the traditional way. Many companies end up with expensive AI tools for business that create more problems than they solve.
Choosing the Right Transport
The key is matching your tool to your task. When selecting AI tools for business, use simple automation for repetitive, straightforward tasks where the rules are clear. Use standard software when you need more flexibility and some decision-making capability. Reserve advanced AI for genuinely complex problems that involve large amounts of data or pattern recognition where traditional methods have failed.
Never use a rocket when a simpler solution already exists, when the environmental or financial cost outweighs the benefit, or when you’re just using it because it’s trendy.
When AI Becomes Overkill
Start by auditing your current AI usage. For each application, ask what problem you’re actually solving and what’s the simplest tool that could solve this. Most businesses will discover they can replace expensive solutions with simpler alternatives for many tasks, making their selection of AI tools for business much more strategic and cost-effective.
AI isn’t inherently good or bad. But using advanced AI for simple tasks is like taking a Ferrari to the corner shop. It’s wasteful, expensive, and completely unnecessary.
The smartest businesses will be those that use the right tool for each job. Sometimes that’s cutting-edge AI. Often, it’s a bicycle. As Karen Hao reminds us, we need to stop using “AI” as a catch-all solution and start thinking critically about what each task actually requires.
