Since AI and machine learning became the buzzwords, everyone wants to jump on the bandwagon! So many companies claiming AI solutions and products that you wonder—how is it possible that so many have the expertise in the latest technology within no time?
I had visited one event on AI, where there were hundreds of stalls with AI-based products. Except for a couple of them, I would say most claims of AI were not genuine. I call these fake AI!
Many products marketed as “AI” don’t actually meet the definition and may be basic automation disguised as advanced technology. Understanding the difference between real AI and fake AI can help you avoid bad investments and choose the right tools for your business.
Some easy signs of fake AI:
- If someone claims that your current application/database we will convert to AI, even without asking what data there or how much information is available, then of course they are talking about simple data reports or, at the most, data analytics! Most likely, they do not understand AI.
- A call to some existing AI solution, like Chatbot, does not make your product or solution AI-based.
- The product or solution remains the same over time—like a static application. Where is the learning involved? If no learning is involved, it is not AI.
- A simple parameter-based or even rule-based solution is not an AI solution. These may seem smart compared to completely static solutions, but these are not AI solutions.
- A solution that follows a fixed flowchart (if yes, then X; if no, then Y) can’t be called an AI solution.
- Lack of transparency: Apart from just the use of AI/ML/NLP kinds of keywords, there is no clear description of how and where the artificial intelligence gets involved.
What is real AI?
Real AI involves systems that learn from data, improve over time, and can handle complex tasks without constant human input. It includes technologies like machine learning, natural language processing, and neural networks.
Here are the basics involved in true AI. (Or ask if the solution matches these aspects.)
Is there training involved in the beginning? Building an AI/ML solution in a particular domain would involve a lot of learning. You need to train the AI engines with huge data. A very small dataset is not sufficient for training. Real AI systems learn from information.
Does the solution learn with time? A simple way to understand AI is to check similarity with how the human mind works. We keep learning with experiences. If we were static in our knowledge and behavior, we would not be the most intelligent species on the earth. So, the question is, ‘does the solution learn and improvise with time, inputs, and data? Is decision-making based on the learnings involved?
This is almost the same as the previous point: with improvised intelligence from learning, the decision process should improve.
Most importantly, integration with an AI engine does not guarantee a good solution. You need natural intelligence/domain intelligence to be able to build an AI solution that is useful!
Conclusion:
Real AI can transform your business, but only if you choose wisely! Understanding the difference between real and fake AI will help you invest in tools that truly deliver value.
If you’re ready to explore AI solutions that work for you, get in touch with us for expert, honest guidance!