The day I first tried an AI-based chatbot (ChatGPT), I was astonished. It was not a mere extension of a search engine. I was already awed at the capabilities of Google’s search engine. But this was a radical jump!
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