Original article can be found here (source): Artificial Intelligence on Medium
Does Your Business Really Need an AI Solution?
There is an incredible amount of hype about AI today. Businesses across various industries continue to adopt this technology to receive a competitive advantage over others, reduce operating costs, and improve customer experience. But does your business really need an AI solution? Some businesses have said that Artificial Intelligence is nothing but a waste of time and money. Also, some organizations face particular barriers to AI initiatives. Gartner’s research showed the most common obstacles are a lack of skilled specialists, a small amount of data, and the inability to measure results. Not all companies are ready to make AI a part of their corporate strategy. Does AI suit your particular business? To find the answer, we reviewed AI business usages and signs of whether a business is ready to integrate AI. Artificial Intelligence is a special algorithm that allows virtual machines to learn from experience automatically by recognizing patterns in the data, and adapt new information to solve particular business problems. AI includes the following sub-fields: Machine Learning applied neural network and statistical analytics to receive insights from data. Natural Language Processing allows the machine to analyze, understand, and generate human language. Deep learning empowers virtual machines with self-learning capabilities and many layers of processing units. In this way, the algorithm develops self-learning capabilities, applied to image and speech recognition. Companies that leverage AI for their business operations said about the following improvements: Businesses apply AI for the following tasks: With this in mind, let’s find out whether you can apply AI for business and what challenges you will face during AI adoption. The first thing to bear in mind is that not all companies are ready to leverage AI. If you want to find out whether AI suits your business, consider the following. Artificial intelligence requires a large amount of high-quality data collected in the right way. Moreover, gathering high-quality data is an essential struggle for all AI specialists and data scientists. In this case, we talk not about the data accessible on the internet, but rather about data your company collects. But, there is no particular answer to how much information your AI solution will need since. It depends on the complexity of your business problem and the complexity of the AI algorithm you are going to build. Thus, if you decided to hire data scientists to build an AI algorithm, you need to make the following preparations: Check out errors in the data. While AI algorithms can find insights from big data, they could not generalize the data format. For instance, if you did several misspells in a client’s name and still conclude that this is the one person, the AI algorithm doesn’t. In this case, AI machines will classify spelling variations as different persons, which impacts negatively on predictions. Keep the data up to date. If you want your AI algorithm to make precise predictions and get really valuable insight, you should keep your data updates.
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