Big data and artificial intelligence have made great strides in digital marketing and their applications have grown conspicuously. According to research by Deloitte, 73% of the companies surveyed believe that AI is really important to their business by enabling the acquisition of new quality leads, unlike their competitors both direct and otherwise.
The same can be said about big data, which is used in industries such as health care or insurance to get more information about consumers, to search for new customers, and to improve website navigation.
In this post, we’ll discuss the importance of big data and artificial intelligence, highlighting the main trends affecting this market with a focus on the role of unstructured data.
A definition of Artificial Intelligence: some statistics
For some years now, the importance of artificial intelligence has been rediscovered thanks in part to advances in technology.
But what is it exactly? It is the ability of hardware and software systems to provide performance that in some ways simulates human behavior.
However, artificial intelligence is often confused with Machine Learning and with the aspects related to algorithms. However, they are two independent, although interrelated, technologies; while AI concerns machines that simulate human behavior, machine learning on the other hand is the algorithm that allows this software to develop and improve over time.
For this reason, it’s not surprising that the first field of application of such systems was factories. In fact, robotics applied to the industrial sector makes it possible to achieve numerous benefits, increased productivity first and foremost. By replacing and simulating some manual human tasks, it also improves worker safety.
Within the B2C and B2B world, the fields of application can be endless: from screening submitted resumes, to recognizing a person’s face in a security setting, to the ability to sort a large amount of documents based on their content. To date, some companies in both the Italian and European landscape are beginning to understand the importance of applying AI internally, entrusting this software with less valuable tasks for the time being, leaving the decision-making part to people.
This trend is also confirmed by recent research by Eurostat, which shows that within the European Union, only two out of 10 companies use artificial intelligence, while in Italy the figure drops to as low as 6%. This could be due to the underdeveloped infrastructure and the lack of specialized personnel at the moment.
Nevertheless, artificial intelligence is a great advantage for the analysis of Big Data, as it enables a detailed analysis and processing of this large amount of data.
Artificial intelligence applied to the analysis of unstructured data
Extracting value from the analysis of big data is a difficult and complex process that requires some technological efficiency and is conditioned by the quality of the data and whether it is unstructured or structured. The latter, as the term suggests, are those that adhere to a predefined set of rules and follow a certain pattern.
In contrast, however, unstructured data does not have a predefined structure and represents the majority of available data: on a daily basis we receive emails or images, just as our company receives documents, provides support or services, and acts on multiple channels that are related to managing unstructured information.
How is unstructured data managed within a company? Through artificial intelligence. For example, within a call center, the ultimate goal is to streamline call traffic and provide high quality service to the customer, avoiding long wait times on the phone.
This includes the whole universe of chatbots, virtual assistants that have been defined as the most mature part of artificial intelligence, but at the same time the one where it is difficult to discern the value between different technologies. Just think of the voice assistants we have inside our smartphones, such as Siri, Google, or even Alexa.
There is wide application within the company for handling documents. In fact, certain industries, such as banking and insurance, often handle documents with unstructured data without being able to understand their priority. Thanks to artificial intelligence, however, it is possible to get into the merits of the documents and understand the data they contain.
Another interesting field regards dealing with very complex documents, such as contracts, which is a field with a very wide application, from the legal world to the world of B2C and B2B where many companies like Doxee operate. Managing a contract can be very difficult, as you also find yourself with reminders, penalties, and understanding certain timelines, which require very quick response times and almost zero margin for error.
Generally, work activities, especially in the fields just mentioned, are carried out by people who have a more or less limited time frame to make reasoning and apply it exhaustively to all documents. Here then, artificial intelligence applied to the analysis of big data could overcome this lack of time, allowing the acquisition of large-scale data while ensuring an important return.
What will be the future of artificial intelligence and big data?
Understanding what the future of artificial intelligence will be is very important for companies, as the data that will be available will become more and more diversified and therefore the support of technologies will be crucial.
To date, the most important challenge for those working in technology is to widen their scope. In fact, we often talk about democratizing AI, that is, making it possible to apply artificial intelligence to people who work in the business and not just data scientists.
It is also important that the information and data that is collected is made available to a cloud. Some projects and processes involving customer data may have privacy issues, while others may be seamless and therefore the data can be distributed to the cloud, making a document much faster, functional, and so that the person in charge can start working on the data immediately.
Another aspect that we cannot underestimate is the purely linguistic aspect of software. For years, the true language of words was not considered and therefore technologies employed certain keywords—there was no way to distinguish between different verb tenses, or between singular/plural and masculine/feminine. Therefore, natural language understanding must be implemented more and more, especially when it comes to providing adequate answers to customer queries.
More generally, in the coming years, artificial intelligence will be increasingly used by companies in both the B2B and B2C sectors and the benefits are there for all to see. In fact, according to recent studies and projections by 2025, investment in AI will reach around €60 billion in global investment, up from €2 billion in 2016. Globally, however, the United States ranks in the top spot in terms of the number of investments and companies using AI, followed by the European Union. By 2030, Western countries will be surpassed by those on the Asian continent, especially China.
Also taking into account the increase in the amount of big data to be stored and processed, the same software will evolve, enabling strategic decision making and problem solving in the shortest possible time. The innovations of artificial intelligence are already visible in some industries, such as telecommunications, where some problems are solved by chatbots based on collected data or in the insurance industry, as previously mentioned, thus ensuring a high rate of data processing and speed of response, which the human brain would not be able to provide.
To date, artificial intelligence is much more developed in the B2C sector, as it is much easier and faster to gain ROI. In the future, the use of AI software will continue to expand in the B2B sphere where some companies are already experimenting through chatbots and AI algorithms for customer service.
It can therefore be said that artificial intelligence and big data will certainly shape the future of our world by opening up the possibility of automating and speeding up some processes, making information acquisition more efficient, and improving the customer experience. It will also expand to other sectors such as energy and media.