In the article on analytics published a few weeks ago, we had focused on the importance of data in order to improve business productivity by enabling constant growth through digital innovation. In particular, we had delved into Tableau’s innovations in data evolution. Today we would like to delve into how data creates value in a company through the use of AI. Let’s go into more detail.
Artificial intelligence and data: creating value
When we think about artificial intelligence, we cannot exclude data and the position it takes in achieving results in the enterprise. Fundamental to consider is that we are not just dealing with software, but more importantly with the ability to use and leverage an approach that turns out to be purely mathematical in order to understand how best to leverage this technology to solve business problems. Business processes and goals. This is the aspect that every company usually focuses on in order to then decide what data to work with and manage in order to achieve the desired goals. But the logic of data is different and must be more focused on analyzing it in order to identify the law underlying the lines of business. The result is a continuous discovery of phenomena and situations that would otherwise remain submerged. Identification of process weaknesses, new opportunities for new services or improvement of existing ones. This is only a small part of what the data in a marketing management system is capable of working. Starting from the data to structure the strategy in order to achieve the goal is not an idea of those in IT who are veterans but are young as is their ability to know how to manage them. All of this leads to an increased likelihood of falling into error. And this is where we get to the point, to the core of data and its use: through data it is indeed possible to create value.
Artificial intelligence and data: the benefits of AI
Data and value creation represent the surplus value that makes it an invaluable source of information which, if worked on, can bring out great things. Getting more into the meat of the matter, when we talk about artificial intelligence and machine learning today we refer to a number of benefits:
- are able to find correlations between data that are often too complex for us humans,
- the speed with which assigned tasks can be performed is not comparable to that of humans
And here speed, in particular, often turns out to be the trump card. We are facing an impact of historic magnitude in everyone’s daily life: perceptual skills such as locating an object in a scene, recognizing voice in ordinary real-world conditions, and making decisions based on “common sense” are “features” that are now taken for granted in the latest computers and apps. Being fully aware that we are entering a new era will increasingly be common practice. Algorithms that, rephrasing the definition given above, are nothing more than “opinions embedded in mathematics” embody two kinds of biases that must become two important points of attention:
- algorithm bias (unbiased artificial intelligence: if you learn from data sets that are not truly representative, you will not be able to have unbiased systems),
- unfair algorithms (by analyzing social phenomena through a huge amount of data available today, they could also “learn” about injustice).
We live in a world punctuated by data even though truth be told few still realize its importance or have any desire to understand how it really works. Here again, training is a turning point for literacy on the subject that will lead the way for all those who wish to study, understand and interpret data.
Artificial intelligence and data: solutions to problems at your fingertips
Let’s dive into a fascinating world where artificial intelligence (AI) becomes the protagonist, responding to challenges and offering solutions. This extraordinary discipline of computer science represents much more than just programming. In fact, we are looking at an approach that combines mathematics with insight from the corporate world, opening the door to a new way of addressing organizational challenges. AI can address a wide range of problems, which can be divided into three key categories:
- classification,
- clustering
- forecast.
Artificial intelligence and data: classification
Imagine a world in which computers learn to categorize objects based on complex data. Here we are not talking about predefined rules, but autonomous learning. For example, if we were to organize objects not by color, but by more elusive characteristics such as size or gloss, the AI can learn to do this on its own. This is like having a virtual quality assessor that does its job accurately and quickly, without human error.
Artificial intelligence and the data: clustering
In the marketing world, AI plays a key role. It can analyze incoming data to uncover hidden patterns of behavior. For example, AI might detect that people who buy wooden handles are also interested in seeds and scythes. This is the secret behind personalized recommendations on platforms like Amazon or Netflix. Here, the variety of input data is crucial for meaningful results.
Artificial intelligence and data: possible applications
Beyond marketing, this technology can revolutionize the way we interact with public services. Imagine being able to automatically categorize requests or documents, to route incoming emails to the right offices, reducing time and complexity. This is just one of many applications where AI can simplify the lives of individuals.
Artificial intelligence and data: predicting phenomena
AI not only analyzes the past but can also look into the future. Through historical data and an advanced analytical approach, it can predict what will happen. This is useful not only for linear growth models but also for complex situations with sudden peaks and troughs. Here, the key is to have complete data and multiple input variables. In summary, AI is a very powerful ally for data analysis and decision making. However, data quality is essential, as is a judicious approach to avoid bias or error. This fascinating world offers endless opportunities to improve daily life by transforming the organization of work and services. Ready for adventure?
We conclude by saying …
We have been going on and on about artificial intelligence as a fabulous and ever-previous tool capable of analyzing data and at the same time the evaluation criteria for how good it is. Error is always around the corner, obviously less than human error. Nevertheless, those who deal with data in the enterprise must possess a really necessary characteristic: the critical spirit in understanding and choosing the right way at the right time after the analysis, several attempts and testing phase. The truth is that the only way to get to theoptimum is to measure, doing it constantly and painstakingly is the only thing that matters because nothing is immutable except the need to change (quote Heraclitus). Ergo: algorithms with time change just like the behaviors they represent. While there is a need to disseminate how these innovative technologies can be used in the marketplace, there must also be the availability of professionals who can be a bridge between mathematicians and business in order to understand well the needs of organizations. Only in this way will it be possible to dialogue with science and build new opportunities to improve our organizations.
