Every business these days wants to focus on efficiency, generating the best value for money and always ensuring there’s a great return on investment. Artificial intelligence can be a solid option to consider here, although there are natural challenges to take into consideration here. Implementing AI into your business always comes with its own, hidden costs, and that’s a thing you have to take into account all the time.
Data preparation and management
Yes, this is a challenge that you always have to take into account. Everything from data cleaning, removing errors and duplicates, all of that can have its fair share of challenges. And then we also have data labeling, as well as data storage and access as well. These things alone can end up costing thousands of dollars, and it’s certainly the type of thing you want to implement correctly as much as you can.
Legacy system integration
Clearly, AI systems are not meant to work very well with older systems. The problem is that a lot of companies rely on older systems, so making AI work with older systems is going to be challenging and definitely quite expensive. You can still find ways to tackle this problem, but if it’s done correctly, the results will be excellent, and it’s totally a thing you have to think about here. API development, data migration, these things take time and money.
Specialized talent and professional training
It’s important to keep in mind that AI talent is expensive. You also have not only the cost of hiring and retaining the talent, but you also have to train and upskill them, which is a major necessity. It gets expensive, but in the end, you do want to have access to the right talent in order to surpass competitors. So it’s certainly worth it, although it can be rather expensive to say the least.
Computing infrastructure
Another thing that adds up costs would be the computing infrastructure. When we talk about implementing AI into a business, clearly we should note that these things are going to take quite a bit of time and resources. It’s not an inexpensive process, that’s for sure. Here you can add up on-premise hardware costs, unexpected scaling costs and of course, anything related to running cloud computing. All of these costs add up and they can end up being rather expensive.
Maintenance requirements
Another thing to note about implementing AI is that this is not a set-it-and-forget it situation. It’s something that requires a lot of commitment, time and money as well. Ongoing maintenance for AI models is on the expensive side as well. That’s because you have security updates, software patches, and also model drifting. All of these things can ramp up the price beyond just implementing the AI, so that’s totally a thing you have to take into account here.
Regulatory compliance
Staying compliant with the latest industry regulations is extremely important, and certainly a thing you have to consider as much as possible. Not only do you need to consider the AI-specific laws, but also CCPA, GDPR and adjacent regulations. Then, we also have liability risks, which could end up becoming a problem due to AI. All of that can bring unforeseen costs, which is obviously something you need to avoid. But in the end, if it’s all handled correctly, it can provide exceptional results.
Reputation management
Aside from those costs, we also have to think about reputation management and ethics. And yes, PR and crisis management, bias audits are also necessary in this type of situation. These costs aren’t that cheap to begin with, but if you are tackling them correctly, the outcome will be extremely interesting.
Vendor lock-in
That’s a problem a lot of the time, because you become dependent on a specific vendor, and if they raise their costs, which is unavoidable in the long run, you are pretty much locked to them. Switching vendors can be very expensive, so it’s certainly a thing that you have to focus on. plus, you have limited customization a lot of the time. It’s not a problem if you don’t need a lot of customization or want to stick with a single vendor. But once you want to make changes to that, costs are adding up.
Clearly, implementing AI is always going to prove challenging, and that’s why it’s incredibly important to focus on results as much as you can. Knowing how to implement AI and making the most out of it is extremely important. Yet at the same time, you need to learn what hidden costs are there, and ensure that you are handling them appropriately. The more you know about this, the better it will be, and it will help alleviate a lot of potential challenges, especially when implementing AI solutions. After all, you want to be very well prepared for anything!
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