Over the last decade or so, organisations from across industries have understood the significance of artificial intelligence and are trying to implement AI-powered systems for several processes such as sales and business forecasting, responders and online customer support and more.

However, most of these growth-hungry organisations don’t have a clear view of the cost of implementation and the challenges regarding AI-based systems. The extent to which most companies think about the cost is just the tip of the iceberg. There are several other expenses and challenges that are added on when they go on to deploy AI.

In this article, we are going to discuss some points that show it is not a cakewalk to have an AI system to transform your business. There is another picture apart from the marketing hype that many companies have not seen yet.

AI Is Not A Product

Companies need to understand that when they approach a vendor or a third-party to help them with their AI system, it is not the final product. AI is going to be the helping hand to your existing process.

When it comes to the scenario when a services company provides a plug-and-play AI system, always ask them how they trained the system. If you are deploying an AI system, it must learn from the data that you feed in order to solve your business problems. If a services company claims that their AI solution is capable of solving your business problems, then there are a high number of chances that the system is trained on public data.

There are always expenses included even after deploying that AI — you have to make sure you are sourcing the most relevant data and feed that data to the system. Also, it’s not just feeding data, there is training involved, changes have to be made to make it fit your business model.

Yes, You Need A Dedicated Team/Department For AI

The is important to understand that IT is not the department that is supposed to take care of your AI system. Rather, IT is one of those departments that is supposed to reap the benefits of AI. Furthermore, IT is always considered to be one of the busiest domain, and when you are deploying an AI system, you don’t want to involve IT.

AI needs professionals who would work solely on them and when it is extremely crucial for companies when it is under experimentation during the initial days. Therefore, make sure, your organisation has an in-house team of professionals who has experience of working with AI solutions. You can either hire people or you can upskill your existing team by providing the much-needed training.

Data Management Is A Challenge

When you deploy an AI system, you need data to train the system. The better and more relevant data you provide to the system, the better the results it would deliver. Furthermore, there are other things as well that comes into the scenario — the amount of data it would need, how would you access that data, whether the data is available if it is available then how you are going to source it, where you are going to store it etc.

Implementation AI sounds really intriguing, but when it actually comes to make it work, there is a bunch of challenges.

Talking about managing and storing the data, many executives make the decision of going to a public cloud. Big companies like IBM claims to be one of the most secure platforms, but are they doing justice to us? Are they not using our data? There are a lot of questions that arise.

One of the better ways to ensure security is to have your own private cloud that would help you store your data within your in-house security infrastructure. But yes, it could be an expensive option.

It’s More Than A One Time Cost

Organizations have to accept the fact that having an artificial intelligence is not a one-time investment, you make several other allied and recurring investments along with it. It is not just about implementing the AI system and let it do its job; as we have already mentioned, data is one another aspect that plays a role in increasing the cost.  

Security and maintenance also come into the scenario when you have an AI system. Also, with time there are chances that the result might vary and starts to take a dip, and this is when you need professionals to work on it and make changes.

AI Is Not Automation

Organisations often tend to confuse AI and automation. There are companies that have ended up investing big on AI to have their automation thing done. However, AI is not something with a mandatory thing for automation.

Automation is all about making hardware or software do thing automatically without any human interference. While on the other hand, AI is about making machines mimic humans and do things just like humans. Furthermore, automation doesn’t need to have AI.

The bottom line here is, organisations don’t have the proper understanding of both the technologies. And this leads to making them spend more money on a problem that could be solved with a little investment.  There is no doubt that AI would make automation more effective but if there is no need for AI then why to make an investment.