Artificial intelligence (AI) has been getting a lot of buzz for the last few years, touching upon virtually every area of human activity. Even relatively levelheaded people sometimes seem to be sure that “strong AI” — AI with an intellectual capacity equal or exceeding that of a human — is just around the corner. However, everything indicates that anything approaching this level is still a ways off. Meanwhile, there is so much talk about AI that the very term seems to have lost its meaning, as representatives of various businesses tend to shoehorn it into every other presentation to demonstrate just how innovative and cutting edge they are. It is often mixed up with another relevant category of software applications — business intelligence (BI). So, what are the differences? Does every business need both? Let’s find out.
BI and AI: What is the difference?
Although BI and AI have many standard applications and overlap at some points, they have different overall purposes. BI is concerned primarily with collecting, processing, and analyzing data. All the tools, applications, and technologies that deal with improving the efficiency of this collection, quality of the resulting data and ways of using all this information are parts of BI. The tools in question analyze the data and create its visual representations: metrics, CFO dashboards, graphs, charts, and so on. Afterward, business specialists can use them to see a meaningful bigger picture instead of noise. However, they make their own decisions about how to apply this information. In other words, the purpose of BI is not to tell you what to do but to show you how things are and how they developed in the past. It is up to you to extract any kind of meaning out of it and make conclusions.
The purpose of AI is quite different. Its programmers try to create algorithms that would be able to imitate human thought processes, learn and, eventually, make their own rational decisions. All the while, they work with vast arrays of data. It means that once they learn to find correct solutions to presented problems, they can do so using vast arrays of information — much more than any human can hope to process. In other words, AI should not only find patterns in seemingly chaotic reality but also decide what to do about it. Then it can give a prescription to its human operator or carry out the necessary action on its own. For now, AI is still in its infancy, although we have already achieved significant success in creating artificial intelligence uses that are sufficiently good at narrow tasks. For example, chatbots can independently answer routine client questions, allowing human customer support members to work only on more complex situations.
BI and AI: Why businesses should consider both
The answer is simple: Of course, a business may forgo adopting these technologies now, for a variety of reasons. These tools still have limited applicability, and they are expensive, they need a lot of time to start bringing results, they can seriously disrupt a company’s business processes and often conflict with legacy software solutions. However, sooner or later one’s competitors will start adopting them anyway, and they will provide them with insights and suggestions that will give them a serious advantage over other companies in the same line of business. Even now, these advantages are noticeable enough to invest in it, which is clearly reflected in BI adoption rates.
The situation with AI may seem a little bit more dubious, for it still has relatively limited application. However, one has to understand that any AI in the current sense of this term needs vast reams of data to work. Only after processing them can it learn to find patterns and make decisions based on the information provided. It means that even if a business does not plan to adopt AI solutions right now, it is worth investing in BI tools. They can be used on their own for the time being, and meanwhile, they will gather data that later can be fed to AI so that it can achieve meaningful results sooner.
The now and the future: AI applications
Although currently existing AI applications are infinitely far away from superintelligent AI as envisioned by sci-fi, they are already successfully used in a variety of fields. In the future, their applications will broaden and encompass more industries. In general, the uses of AI fall within the boundaries of one or more of three categories:
Process automation: Probably the most common current application of AI is related to automation of processes that are normally carried out by humans. While automation, of course, existed before AI, the former allows the latter to rise to a whole new level, as AI can interact with information like a human. AIs are already capable of analyzing inputs according to predetermined rules, updating records across multiple systems and performing a variety of other tasks. As programmers find new and more efficient ways of teaching AIs, they will become “smarter” and capable of performing other, more complex tasks.
Cognitive engagement: These applications aim to automate and improve the efficiency of interactions between humans and systems. Already existing examples include recommendation algorithms that suggest additional purchases based on what the customer seems to be interested in, and chatbots interacting with clients. For now, the more complex applications are mostly used internally because businesses are rather nervous about entrusting something so crucial as customer communication to machines. As AI algorithms grow more sophisticated, we will see more and more automated interactions between humans and all kinds of systems.
Cognitive insight: It is the area where AI and BI overlap most of all. Using the vast stores of data at a business’s disposal, AI can find patterns unnoticeable by humans and provide meaningful insights based on them. For now, AIs are generally effective in this area because they can process much larger amounts of data compared to humans. In the future, however, they will learn to process and correlate broader swathes of information and find dependencies most humans will overlook even if they have all the data at their disposal.
As you can see, both BI and AI are of vast importance for any business whose owner wants to stay ahead of the competition — which means that programmers specializing in these areas are never going to be out of a job!
Featured image: Pixabay
More Digital Transformation articles
- Digital transformation and financial services: Banking on emerging tech
- Remote possibilities: Does an MSP have to use an RMM tool?
- OneDrive Request Files: A great new alternative to FTP
- Combating the inefficiencies of the digital workplace
- What to do when your boss is clueless about digital transformation