With the increasing use of artificial intelligence (AI) and machine learning (ML) in companies, a new era is heralding in the economy. This is what the employees of Technogrips, experts for cloud data management, experience every day in customer contact. According to Joe Mathew, Director Channels at Technogrips, the utilization of data has proven to be a major advantage of the new technology in the long term.
AI and ML are topics that CIOs have to deal with, there is no way around it. And no, the AI has not yet become independent and made us slaves to confront dark visions. However, it has matured and the transition to mainstream means that AI can be used for more and more applications, «explains Joe Mathew.
As AI-enabled technologies continue to evolve, CIOs around the world will have their own understanding and perspective on their meaning. For me, AI allows technology to simulate what a human would normally do. ML takes place when the technology goes beyond simulation and starts to learn independently.
Of course, both AI and ML are only as good as the data they have access to. The more data there is, the more information can be provided. The “cleaner” the data, the more accurate the result. AI can be used as a tool to gather additional information from the vast amount of data that every company has. It can help companies analyze and automate data, providing incredibly valuable business insights.
All too often, AI was viewed as an independent component and not as a company-wide tool. However, the companies that have had the greatest success with AI are the ones that involve them in every aspect of their digital transformation.
For example, predictive modeling enables sales teams to predict which product will sell best, in which region, and when. By contrast, teams that deal with customers can use AI to analyze customer data and anticipate product problems before the customer notices, providing an unprecedented level of proactive customer satisfaction.
AI has a place in every corner of a company. CIOs implementing new applications should first ensure that they are equipped to use their business intelligence.
For a company's IT suite to run like a well-oiled machine, it is no longer enough to keep an eye on the here and now: CIOs must also know what is around the corner. From predicting whether their infrastructure will fail, through a particular web server facing a problem, to a cyberattack, AI and ML are the best way for businesses to address these issues directly rather than groping in the dark.
Ransomware is an issue that businesses around the world need to address and that AI and ML can help with. In this way, user behavior in the company can be monitored to create a basis for what is “normal”. An alarm would be triggered upon detection of unusual behavior that deviates from normal patterns. This makes it possible to react to an attack almost immediately and to minimize the total downtime. ML algorithms can continuously improve this approach over time, so companies are always one step ahead of new threats.
Even if AI and ML have huge potential, we are still a long way from robots taking our jobs on a large scale. Instead of replacing employees, AI actually supports employee productivity, «says Joe Mathew.
It enables them to concentrate on their actual work. AI empowers people to better perform their roles by improving workflows, finding information, learning, and collaborating, to name a few.
An example of this is the processing of the mother tongue, with which hearing aids can understand what a person is saying and can interpret this for someone else in their mother tongue. This application would make it possible for a person in China to speak to a business partner in Venezuela regardless of their language skills.
AI should therefore be considered as another team member, an extremely efficient employee who plays a role throughout the company and enables all other employees to work more efficiently.
Cloud data management as a central data platform for AI
“When I discuss AI implementation with companies, I have found that the biggest obstacle is that they are overwhelmed at the point where they should start. They want valuable insights, but they don't have the right data strategy, explains Joe Mathew. “My advice is always the same: focus on the data you have now and grow from there. Few insights are more useful than no insights, and your data can only grow.
From self-healing infrastructures to self-learning security to anticipation of the future: AI algorithms first need access to historical data. It is advisable to implement a cloud data management platform that knows exactly where all the data is located throughout the company. With the right technical architecture, all applications benefit from modern data storage and can make intelligent decisions.