The Business of AI: From Hype to Reality, How to Make it Work for Your Company

By Fabián Jiménez - Services Director at Noventiq Latinoamerica

Artificial intelligence (AI) has been a buzzword in the business world for several years now, and for good reason. With the potential to revolutionize the way companies operate, it's no surprise that businesses are looking to integrate AI into their operations. However, moving from the hype of AI to its practical implementation is easier said than done.

Let's take a closer look at the business of AI and how companies can take advantage without it becoming a massive headache.

One of the main challenges companies face when it comes to implementing AI is separating the hype from reality. There's an insane amount of buzz around AI, and it can be difficult to pick out what's actually feasible from the hype. This is why it's critical that companies have a solid understanding of what AI can actually do before diving in headfirst.

The first step in making AI work for your company is to identify the business problem you're trying to solve. AI is a powerful tool, but it's not a magic bullet for solving all of your problems. To get the most out of it, you need to identify the specific pain points and business problems that you’re looking to address with AI. And here’s the thing – this could be any aspect of your business, from improving customer service to optimizing supply chain operations.

Once you've identified the problem you're trying to solve, the next step is to determine what type of AI solution is best suited for your needs. There are a variety of AI technologies out there, from machine learning to NLP (natural language processing), and each of them has its own strengths and weaknesses. It's critical that companies understand that, to get the best results, they need to work with experts in the field, such as Noventiq , to figure out what type of solution is going to be the best fit for their business.

The next step is to ensure that you have the right data infrastructure in place. AI relies on immense amounts of data to learn and make decisions, so having access to high-quality data is essential. This means having a robust data infrastructure in place that can collect, store, and analyze data in real-time.

Once you have the data infrastructure in place, the next step is to build your AI model. This involves training the AI system on your specific data set, fine-tuning it to improve its accuracy, and then validating the results. It’s a complex process that requires expertise in AI and data science.

When you have your AI model up and running, the next thing you need to consider is how to integrate it into your existing systems and processes. This can be quite the challenge, as it often requires changes to be made to existing processes and systems. To achieve the best outcome, you need to make sure you work closely with IT and other teams to ensure that the integration goes smoothly.

Finally, it's important to monitor the AI system over time to ensure that it's performing as expected. AI systems are not static, and they require ongoing monitoring and maintenance to ensure that they continue to operate effectively.

The business of AI is about moving beyond the hype and figuring out how to make AI work for your specific business needs, and that means identifying the business problem you're trying to solve, determining the right AI solution, building the AI model, integrating it into your existing systems, and monitoring it over time. It has to be said – it's a complex process, but with the right expertise and approach, companies can leverage the power of AI to transform their operations and stay ahead of the competition.