The 4 most overlooked limitations of AI in business

limitations of AI in business

We have already talked about how AI will eliminate 12.5% of jobs in Asia by 2024. Do check our last episode. Today, we’re going to see about some limitations of AI in business. Well before getting started, you must know how much important is AI in the field of business.

One of the main reasons to use AI is to grow your business. By using appropriate data and getting useful information as output for future reference. AI makes the work easier & more accurate also making it cheaper. But then there are certain disadvantages especially in the field of business.

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1. Data Requirements

Data Requiremenrs

AI requires a lot of data (or appropriate data) to train itself to come up with a solution. If you don’t have enough data. It will be hard to train and to get the correct output from it.

Parcell said, “The most pervasive limitation to AI adoption is data. AI needs data to learn to perform its function. Unfortunately, I’ve yet to speak to a company that has its data house completely in order. In most companies, data is typically siloed and rarely consistently cataloged and governed. Without good, relevant training data, a company will find it quite hard to get started with AI.

Also, it isn’t just the data, you must have data related to your work. Adobe ‘s head of data science said: “actionable data that will help them learn, that is suitable for whatever task they have in mind “.

2. Ethical issues

ethical issues in ai

It may seem like AI can do anything. But over smartness and knowing nothing both are dangerous. AI-powered weapons can create a lot of damage if there is any mistake. Also, you need to look after customers privacy, the data collected from the customers should not be leaked.

One of the main point to consider is fraud detection, you cannot just relay on AI you need a human touch as well because humans are better than AI at least for now. Many companies have their chatbots and that’s good as it saves money and human effort but most of the people prefer talking to a human. You may have called customer care at least once and always wanted to skip the step of chatting with AI. It isn’t like that we don’t trust AI but it needs to be more human to understand what we are saying.

3. Nothing outside the data

ai without data

It’s not just about how much data is being given to your model. If something new is introduced then your AI may fail to answer. Which means your AI is not knowledgeable enough to answer some questions. And many of us will ask or do something different that AI is not having data of. Plus you cannot give every single data present on earth. It will be very vast and even if you somehow found a way of doing it, processing this much data will not be easy.

4. Implementing AI

implementing AI

Implementing AI is not an easy task. High chances of losing out a lot of money and time. Once Parmenter said. “You’re going to get more data in wealthy neighborhoods because that’s where autonomous cars are gonna go first,” he added. “I really don’t think any practitioners in my field are bad actors, but we really have to be open to the implications of what we’re doing and making sure that we are fair and evenhanded.” Before actually implementing AI you have to collect enough data and resources to get it done.

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Hope you have liked this post stating current issues or limitations of AI in business. Stay tuned with PinProgram for future updates.



Yash Agrawal

Yash has been put on board to help out with the developer friendly content of the latest programming trends and conferences.

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