There is a whole variety of business use cases for AI. Artificial Intelligence can predict call volume in call centers to support staffing decisions, predict customer behavior, recommend products that the customers will enjoy, classify customers, forecast product demand, detect fraudulent credit card transactions, filter spam email, but also detect faulty products on a production line, provide language translation, generate captions for images, power chatbots, and even help diagnose patients.
According to McKinsey, 47% of organizations have already implemented AI in at least one function in their business processes, taking advantage of Machine Learning (ML), Deep Learning, Natural Language Processing (NLP) or Predictive Analysis. The companies that will be late with implementing AI into their service may soon fall behind their competitors.
What industries can benefit from AI development?
AI can be used across different industries. E-commerce, telecoms, healthcare, HRs, agriculture, security, law, education, transportation, finance, SaaS – they can all benefit from using AI. What they all share in common is data – AI proved to have a huge impact on all the data-related tasks, including its processing, analyzing, finding patterns, and building predictions.
Top use cases for Artificial Intelligence
Let’s see how companies among different industries can use AI!
1. Better search. Natural Language Processing (NPL) can help clients of the online retailers narrow search results to the most relevant ones – also with the voice search.
2. Personalized recommendations. Personalization has a huge impact on clients’ purchase decisions. The ability to successfully suggest clients their next buy (or next content to consume) can be a game changer for the retail, but also for the media publishers, SaaS products, or the telecoms.
3. Better customer service. A lot of queries can be handled by chatbots which significantly shortens the time of response. With more complex issues, the bot is able to identify the right specialist to handle it and forward the message there. Such a solution can be used by all the companies that offer their services online.
4. Administrative workflow automation. Solutions such as voice-to-text transcriptions combined with NLP and structuring the information into a report can save a lot of any staff’s time. AI can take care of the legal research, processing the CVs and shortlisting the best candidates, automate administrative tasks at the doctors’, in schools or at offices.
5. Detection of the defects. Neural networks fed with the roentgen pictures of different forms of cancers at different levels of the advance is already proved to diagnose cancer better than the qualified doctors. It misses the lesions less often and is less likely to misdiagnose. In a similar way, AI can be able to spot the defects of the machines in the factories, cyber attacks, or plants diseases.
6. Churn predictions. By analyzing the behavioral patterns, AI can successfully predict which customers are most likely to churn. With that information and some product recommendations, the consultants are able to prevent the churn by offering their clients a better offer at the right time.
7. Reducing employee retention. Using behavioral patterns, predictive models can also predict which of the employees are most likely to look for the new job. Combine it with personalized recommendations, identifying the right benefits or training options to help them develop, and you may be able to prevent your employees from leaving.
It’s all about data
As you can see, Artificial Intelligence can be used across different industries. The decision about going into AI Development in a company, however, should not be determined by a simple will of “having AI”. In the first place, Artificial Intelligence has to solve business problems and help achieve some specific goals.