What makes AI actually AI?

Or: 9 Factors that differentiate AI tools from regular Software.

Every tool claims to be an AI tool at the moment. And I have to admit, some software I tested in my video course “Boost Your Productivity - AI Toolkit” left me wondering: what exactly is the AI part in this tool!?

The issue is that many software companies are using the term AI to hype their products up, even if they don’t actually use AI-powered technology in them. This can make it difficult for consumers to find the real AI tools that can truly help them.

Here are some markers to distinguish software that uses artificial intelligence (AI) from software that only uses the term AI in their marketing, but don’t tick the following boxes:

AI-powered software:

1. Is adaptive:

AI software can adapt and improve its performance over time based on data and user interactions.

2. Learning:

It can learn from patterns and make predictions or decisions without explicit programming.

3. Natural Language Processing (NLP):

AI software can understand and generate human language, enabling chatbots and language translation.

4. Computer Vision:

AI software can analyze and interpret images and videos, useful in tasks like facial recognition.

5. Recommendations:

AI software can provide personalized recommendations based on user preferences and behavior.

6. Automation:

It can perform tasks autonomously, like self-driving cars or automated customer support.

7. Neural Networks:

AI often involves deep learning models, such as artificial neural networks.

8. Problem Solving:

AI can tackle complex problems and optimize solutions using algorithms.

9. Speech Recognition:

AI software can transcribe spoken language and enable voice assistants like Siri or Alexa.

Software that doesn't use Artificial Intelligence:

1. static:

Non-AI software typically follows predefined rules and instructions without learning or adapting.

2. Manual Data Entry:

It relies on manual data input and does not autonomously extract insights from data.

3. Limited Language Abilities:

It may not understand or generate human language beyond basic text processing.

4. Manual Image Analysis:

Non-AI software requires manual analysis of images and videos.

5. Generic Recommendations:

It provides generic recommendations without personalization.

6. Manual Task Execution:

Non-AI software relies on user instructions and doesn't automate tasks.

7. Traditional Algorithms:

It often uses traditional programming and algorithms rather than deep learning.

8. Simple Problem Solving:

It is suitable for straightforward problem-solving but struggles with complex, dynamic issues.

9. Lack of Speech Recognition:

It does not have advanced speech recognition capabilities.

Keep in mind that the lines between AI and non-AI software can blur, and some software may combine elements of both. The key is whether the software can learn, adapt, and make decisions based on data and user interactions.