These days, there is a general debate about what is artificial intelligence and its real and perceived impacts on our day-to-day lives. Although there have been a massive amount of studies and articles written on the subject, it is nevertheless still difficult to easily sum up the current state of the technology, much less accurately predict where it might lead us in the future. This lack of certainty is the cause of both high hopes and a great deal of anxiety, and there is a great deal of speculation as to whether many of us will lose our jobs to robots.
A series of studies have been developed that aim to present a detailed and realistic idea of the potential applications of artificial intelligence, as well as the direction that the technology is taking. In this post, we’ll discuss two important surveys of the field: the first, conducted by consulting firm McKinsey, is a snapshot of the current state of the industry, while the second, by the research and advisory firm Gartner, focuses on where the field is heading.
What is Artificial Intelligence?
What is Artificial Intelligence? First, we should go over the basic concepts behind the technology. To fully understand what artificial intelligence is, we went back to something the professor and researcher Renato de Brito Sanchez related to us in this article (in Portuguese). Professor Sanchez is an entrepreneur and the owner of two companies (one of which focuses on technology in automation, robotics and artificial intelligence). He said that artificial intelligence “is a concept that speaks to the realization of mankind’s dream of a distant future, one in which machines and humanoids interact with humans and animals.”
However, that distant future is already becoming a reality. Artificial intelligence became the latest step in an ever-accelerating technological revolution. It followed processors, which could perform calculations, and which subsequently evolved into the programmable systems we see in everyday life today. In AI, the processing of information will be based on systems learning from previous experience. The new technology will be similar to what happens in our brains, as we are constantly receiving information, processing it and adding it to our existing knowledge base.
The Current Uses of Artificial Intelligence
Let’s take a step back and think about how much of all this is already a reality. This recent study by the consulting group McKinsey takes a detailed look at the current impacts of artificial intelligence. The study looked at more than 400 use cases across 19 industries and nine business functions, and their uses of two types of analysis:
1. Traditional data analysis – Business Intelligence (BI) techniques that monitor, gather, and organize data. They analyze past actions, identify new opportunities and implement strategies based on data;
2. Deep learning – a system that requires thousands and thousands of data records so that models can perform complex logging tasks satisfactorily. Moreover, in some cases, it takes millions of those data records for the networks to perform at the same level as a human being. These are the so-called neural networks.
McKinsey’s study demonstrates how various segments within the economy have already understood what is artificial intelligence and have been able to employ the technology in a variety of important applications.
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Examples of the successful use of artificial intelligence
Next, the study reports on the current state of good practices in the use of artificial intelligence. One of them is “Predictive Maintenance”, which uses the power of cognitive computing to detect anomalies. By analyzing immense quantities of high-dimensional data, it can take existing preventive maintenance systems to new levels.
For example, AI may extend the life of a cargo plane beyond its original predicted useful life. It’s possible to combine traditional analysis techniques with airplane model data, maintenance history and IoT (Internet of Things) sensory data to detect anomalies. Additionally, images and videos of the condition of the aircraft’s engine may be added to that assessment to fine tune the system’s assessments.
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Reducing costs and deadlines
The technology has other applications in the logistics industry, where it is used to reduce costs with real-time forecasts and behavioral coaching. Techniques such as continuous estimation can add substantial value for the sector. Artificial intelligence is capable of optimizing the routing of delivery traffic, improving fuel consumption and reducing delivery times.
For example, according to the report, one European carrier managed to cut fuel costs by up to 15%. It did this by using sensors that monitor both the vehicle’s performance and the driver’s behavior. To improve the latter, drivers were given real-time guidance, including recommendations on when and how much to accelerate or decelerate, while also reducing maintenance costs.
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The future of AI
The other report, which deals with trends in artificial intelligence, was produced by the US research and advisory consultancy, Gartner. The report starts off with an astounding fact: the business value related to AI is expected to reach $3.9 trillion over the next five years.
Over the next few years, the study stated that the primary source of AI-derived business valuewill be the customer experience. This is based on the fact that an expanding pool of companies have been using tools like virtual agents and chatbots to help in their interactions with customers.
Beyond 2020, Gartner expects the most common use of the technology to be in “decision support.” In other words, artificial intelligence will be used for the science of data and other applications based on algorithms, which will permit the classification of data that had previously required human intervention. According to the consultancy’s forecast, this type of application should account for 44% of the total usage.
According to the study, there will also be another significant basis for the use of AI: ”decision automation systems.” This involves artificial intelligence systems that can turn voice into text, process handwritten texts, and assess the difficulty of classifying information. With this processed data in hand, tasks can subsequently be automated, and processes streamlined. This sector may account for 16% of the total usage of AI in 2022.
Intelligence for managing your workflow
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