AI brings new possibilities and some extraordinary capabilities. All businesses are keen to make the best use of AI. And why not? Who does not want better business decision-making? Lessor errors? And like it or not, in the capitalistic world, businesses love ‘independence from human involvement’ as humans are not controllable or fully predictable. (Of course we don’t know yet if AI will remain controllable forever.)

But we need to understand one important aspect:
Integration of AI engines does not necessarily make a good business solution!

In fact, without proper domain knowledge and business intellect, it can be catastrophic. A business involves knowledge of various aspects. Use of AI involves training the engine with the information related to these aspects. The processes and parameters, the data aspect, and the goals of business need to be understood clearly while designing the AI solution.

You need to understand what data is to be used for training the AI solution.

Every industry solution that we have provided so far involved a period of serious business understanding. It involved us, becoming a complete part of the client’s business.

A deep and thorough understanding of the business domain is essential for any software solution, whether AI or otherwise. Since AI may involve decision-making without human intervention, it is even more important to have the correct business understanding built into the solution.

Smart selection of what to automate—or left to AI—and what should be done with human intervention.At least, with the current status of AI, it is not a complete replacement of human beings. For the AI-based solution, it requires smart selection of deciding which aspects should have human involvement. Some decisions are automated, while some could involve an authentication from real people, and some could be purely human decisions based on the information provided by the AI engine.

Magnitude of parameters involved: In any business action, transaction, or decision-making, there are a large number of parameters involved. Which parameters to consider or train the AI on is a ‘humanly impossible task’, and one parameter missed can cause complete chaos. This is where you need to involve the human factor.

Case Study: Healthcare: Suppose healthcare decision-making AI engines are to be designed. Can a pure data scientist manage this? You need qualified, experienced doctors to get involved, as they are the ones who would miss fewer parameters and would know many nitty-gritty aspects of the decision-making. And the tech experts need to absorb sufficient knowledge before designing the system.

Would you like to explore how your business can leverage AI alongside human expertise? Understand why varied industries rely on us for their information technology needs for decades? (Key is understanding the business in depth.) Contact us today to discuss tailored solutions that work for your unique needs.

-By Parag Shah, CEO @Mechsoft

The post You need Business Understanding and Natural Intellect for AI to be useful appeared first on Mechsoft Blogs.

This is similar to a question: Would block chain technology help an e-commerce business selling $1 items?

What kind/size of businesses can be helped with AI involvement?

• Large data and complex decision-making is involved.
• Some decision matrices are ‘subjective’ and are taken by gut feel.
• There are manual interactions involved, which requires a lot of manpower to support, which sometimes makes the business case less viable.
• The business model is more or less stable, where complete disruptions and chaotic changes are not expected.

Here are actual examples of each of the above situations:

• Complex decision-making: A large factory making a customizable product that requires hundreds of spare parts. Decisions on inventory, complex supply chain scenarios, and waiting periods between various processes. You need to anticipate possibilities, and there is a ‘judgement’ call taken. AI definitely can help this situation.
• Any product/service support where there are questions asked by users/customers that need to be answered—a manual process can be improved, augmented, or replaced to some extent using AI’s natural language processing ability, and this is a simpler integration with a smaller training on the support information data.
• Industries like automobiles have been more or less stable for many years. Training on existing data for better decision-making will be easier. But things that are completely dynamic and fast changing—using AI on earlier data alone may not be enough, and the training will be trickier as you may need to link it with changes that can be anticipated and changes and trends that can be sniffed from the online knowledgebase/media.

At Mechsoft, it is not unusual that we say no to some tech advance that a client suggests when we think it is not useful or not right for them, even though it means saying no to a project.

-By Parag Shah, CEO @Mechsoft

The post Do I need a custom AI solution for my business? Read this before spending a fortune appeared first on Mechsoft Blogs.

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!

-By Parag Shah, CEO @Mechsoft

The post Real AI vs. Fake AI appeared first on Mechsoft Blogs.