Artificial Intelligence, also known as AI, is, in simple terms, a computer or machine’s capability to imitate human-like intelligence. Instead of just following static, pre-written instructions, AI systems analyze data to recognize patterns, make decisions and, at times, solve complex problems.
Today, it is everywhere. It powers personalized recommendations on streaming apps, helps doctors diagnose diseases and enables voice assistants like Alexa, Google or Siri to understand user questions. It is about “smart” software that learns from experiences and patterns that process data at lightning speeds. It can seem so intuitive that it almost seems like the devices are listening.
How Businesses Should Use AI
For business operators, especially those looking to be more efficient, the question is not if they should use AI, but when. Below are some prime examples of Artificial Intelligence use in the workplace:
- When mounds of customer data have an organization making decisions based on “gut feel.”
- When an organization is collecting large amounts of data.
- When employees are spending hours on manual data entry, scheduling or basic ticket routing.
- When customer support is drowning in repetitive around-the-clock queries.
Some other uses are:
- Dynamic Pricing: When prices change on Amazon or a flight booking site, an algorithm has likely adjusted them based on demand, inventory and competitor data. Sometimes referred to as surge pricing, dynamic pricing can generate controversy because customers are paying different prices for the same products depending on when they make the purchase or even personal data.
- Financial Security: Banks use AI to scan millions of transactions per second. If a credit card is not declined during a trip, it is because invisible AI verified the pattern as “safe.”
- Personalization: Spotify and Netflix do not just “guess” what subscribers like; they use deep learning to analyze the specific “vibe” of the customers’ choices.
DHL and UPS utilize AI to optimize delivery routes in real-time, accounting for weather and traffic patterns before drivers even start their engines.
In manufacturing, companies like Toyota use computer vision to monitor assembly lines for micro-errors or safety risks that a human eye might miss. General Electric (GE) and Procter & Gamble use sensors and AI to predict when a factory machine will fail, scheduling repairs before a breakdown occurs to avoid millions in lost productivity.
And these are just the tip of the proverbial iceberg when it comes to the power of AI. The opportunities are almost endless, but business operators should always remember that AI is a supplement for humans, not a replacement.
They should also be careful when choosing to use AI because research shows that less than half of the world’s population trusts AI and businesses’ uses of it. After all, it is still relatively new and it will take time for a shift in trust by the general public.
What does AI say about trusting AI?
Trusting AI isn’t a simple “yes” or “no” — it is more about understanding what a specific AI is designed to do and where its boundaries lie.
When You CAN Trust AI
AI is highly reliable when performing tasks based on patterns, math, or vast data processing where “human-like” nuance isn’t the primary goal.
When You Should Be Skeptical of AI
The “hallucination” problem remains a reality in 2025. You should exercise high skepticism in the following areas:
- Fact-Checking: AI models are “probabilistic,” not “deterministic.” They predict the next most likely word, which means they can confidently state a “fact” that is entirely made up.
- High-Stakes Legal or Medical Advice: Never rely on AI for final legal filings or self-diagnosis. In 2024 and 2025, there were several high-profile cases of “AI-generated fake precedents” causing major legal sanctions.
- Unbiased Judgment: AI learns from human data, which contains historical biases. If not carefully “aligned,” AI can unintentionally discriminate in hiring, lending, or law enforcement.
How to Safely “Trust” AI
To use AI effectively, adopt a “Trust but Verify” framework
- Check the Source: Use tools that provide citations (like Perplexity or Consensus) so you can click through to the original data.
- Define the Role: Use AI as an assistant, not an authority. It is a brilliant intern, not a senior partner.
- Use Specialized Models: For math, use models with built-in calculators; for research, use models connected to live web-search.
As one AI-er put it, Artificial Intelligence is good enough for co-pilot but not quite good enough for auto pilot. Good business still starts with a human connection and the human touch, much like what is provided by the experts at FTC IT Solutions. They can provide guidance to help you determine if and when AI makes sense for your operations.
It is just part of what they can do for your business. They can also be your whole IT department if that is what you need. Or something in between.
Want to hook up with FTC IT Solutions and find out how they can help improve your business? Just give them a call at 888-218-5050.
