There are more and more sectors where it is possible to apply AI, thanks to the use of specific tools and algorithms.

Let's see some of the main ones:

  • natural language processing (NLP), for text analysis;
  • conversational AI (part of NLP), for customer communication (customer care, infotainment);
  • computer vision or image processing, especially in the fields of medicine, surgery, insurance (processing files in case of car accidents) and retail (vending machines);
  • voice recognition, to recognize what is being said by one or more people;
  • robotic, which are autonomous robots (usable for surgery or car repair), including self-driving cars;
  • recommendation systems, used in e-commerce (e.g. Netflix, Spotify and Amazon);
  • intelligent data processing, with algorithms that operate on data (structured and unstructured) to extract information (anti-fraud systems, anomaly detection, content creation, preventive maintenance, monitoring and control, pattern detection);
  • advanced analytics, which can leverage ML algorithms to perform intelligent data processing tasks.

Also in the auditing industry, AI can make a contribution in terms of efficiency and innovation.

RSM has developed two innovative and intelligent software programs that automate the basic functions of the auditor's activities, leaving space and time for the RSM consultant to provide their client with broader and more strategic support: Revisya, which supports the auditor throughout the process, in a totally innovative way, Genya CFO that allows a decisive simplification of the processes necessary to diagnose and prevent the state of crisis of companies.

Among the sectors that are receiving great benefits from the application of AI and for which a strong development is expected also in the future, are:

  • banking;
  • finance and insurance;
  • telecommunications;
  • IT service providers (cloud);
  • industry;
  • logistics;
  • automotive industry;
  • public administration;
  • justice and advocacy;
  • healthcare;
  • military. 

Some specific sectors deserve special note:

  • marketing and sales for which predictive analytics, based on AI algorithms and historical data sets, can improve customer relationships by anticipating their needs and offering them solutions calibrated to their specific interests and requirements.
  • utilities and energy, to provide reliable forecasts of demand, movement and supply of clean water through analysis of weather data and historical customer usage data; to determine the most cost-effective replacement strategy for aging plant assets; to more easily and quickly visualize performance issues through comprehensive analysis of data from gas, electricity and water sensors; to improve customer service through contact centers.
  • renewable energy for which machine learning is used in manufacturing, particularly solar and wind. Weather effects (cloudiness, precipitation, wind speed and direction) can alter the amount of energy produced and fed into the distribution grid, unlike traditional sources (fossil fuels and nuclear) which can be planned with extreme precision.