Nowadays, even with all the research and study on the subject, when we talk about Artificial Intelligence (AI), we are automatically transported to the imaginary of cyborg films and sentimental computers loaded with mindfulness.
The truth is that today’s AI is still the tip of the iceberg of what is thought to be its evolution, and is still several decades, if not centuries, of computers capable of interpreting feelings and emotions in real world or being self-conscious. However, from the famous Deep Blue computer, which beat master Kasparov, to today’s limited-memory machines whose ability to interpret data makes them valuable in decision-making, a long way has been made.
One of the areas where AI can be applied is undoubtedly in the treatment of the information generated by the numerous internal and external business systems, including the increasing number of electronic data generating devices (RFID, sensors, online services), social networks, among many others, which can provide us with decisive arguments for business evolution. Whether it is detecting and reducing inefficiencies, automating processes and / or user interaction, finding new lines of business or behavioral patterns, predicting developments, among many others.
Business Intelligence (BI), being the set of methodologies, tools and processes dedicated to the collection, treatment and availability of information, has in AI the perfect ally to extend its capabilities and enhance its effect. Proof of this is the increasing presence of slogans such as Process Automation, Cognitive Insights or Cognitive Engagement in BI solutions characteristics.
Companies with their data-driven management are no longer science fiction and are increasingly becoming a reality, also in Portugal. Machine Learning algorithms, from increasingly large and diverse datasets, help identify trends and new business insights, enabling greater real-time competitiveness.
As an example, we can think of the factory manager who, through his BI application, receives an alert on his mobile phone indicating that the production of an assembly line has slowed at the usual pace. The same manager crossing this information with other data collected and processed in the same solution, can verify if an inspection of the equipment is necessary, anticipating actions, reducing the period of lower production, avoiding higher costs.
Another example of AI utility, with proven sales volume growth, is the use of smart suggestion when a customer starts typing a product in any online sales channel. The fact that the algorithm suggests, in real time, products based on the user’s personal tastes, collected from previous sales, but also from social networks or other sources, increases not only the likelihood of sale, but also the return to site rate.
However, in a country where 95% of companies have less than ten employees, it will not be possible to have a team of BI or AI specialists, so the help of specialized external consultants, will be a way to quickly understand how and where these tools can be used to their advantage.