Here is a list of practical examples that can help you quickly take your business to the next level involving AI:
Machine Learning algorithms come to the rescue in areas built on a constant flow of heterogeneous data, whether it is several financial reports, payrolls, procurement, the analysis of employee productivity, or predicting further churn rates.
In short, AI takes over routine administrative tasks and changes the whole way of working. It gives employees and executives more space for making faster and relevant decisions.
Also, the capabilities of AI go further and can interact with clearly figured data requiring a single set of indicators and ephemeral parameters that have not yet been formalized.
According to
, 95% of businesses still need to process the unstructured data somehow. This approach is appreciated in many operational processes.
Let’s view human resources as an example of decisions in business operations. In HR, the entry, categorization, evaluation of employees’ and applicants’ data is essential yet monotonous. The first stages of recruitment are usually challenging: defining a position needed for a department, figuring out all the candidate criteria and areas to cover, sourcing, selecting the first CVs, and so on. Here AI comes in hand.
AI-empowered solutions help to facilitate the recruitment process, source better candidates, analyzes their interviews. Eventually, an HR team can make a robust decision of hiring a suitable candidate.
Overall, AI, in terms of inner business processes, is able to leverage business intelligence and make a company data-driven in many aspects, including decision making.
The potential of AI in decision making is robust, but you can
solve multilayer and complex problems
, too. For this, you must remember that AI solutions depend on the data you have and the step-by-step
.
