Content Intelligence: How Computers Process Information Easily

Organizing a heterogeneity of digital materials to process information efficiently helps manage the growing wave of big data and extract value from the report.

Most organizations do not analyze unstructured data. And so, unless you spend a lot of time and human resources extracting, processing, and sorting it, valuable information is lost. For this reason, the leading companies are taking advantage of advances in content management for artificial intelligence (AI), the content intelligence.

In particular, the development of machine learning and AI allows the creation of models in the information that would enable the content to be expressed thanks to the use of natural language, the use of speech recognition or image recognition, as well as other technologies useful for computing, images, and videos.

This Is How Content Intelligence Works

Applying cognitive technologies to content does not require an immediate change in pace. Content management for AI can be introduced through several steps. The more value a company wants to get from its content, the more advanced the cognitive technology to be used must be. Hence, content intelligence is a journey businesses must take to grow content’s value over time.

There are different levels of content intelligence. The first level is the simplest, where the content is digitized, removed from its native formats such as photos or paper documents, and digitally archived. Companies begin their journey with processes that are not particularly intelligent from a content standpoint. However, the ultimate goal should be to have an intelligent system capable of handling content in various ways and providing a better understanding to derive the brilliant data businesses need.

Using artificial intelligence content management models, systems can generate value-added information without the need for human intervention. It enables the sending of promotional communications on third-party products and services concerning data controllers using traditional and automated contact methods by the third parties themselves to whom the data is transmitted.

The development of higher cognitive skills increases value for companies that can strategically manage even challenging business problems. The more intelligent a content management service, the more it can take over and resolve previously worked activities, with wasted effort and fewer person-hours. The goal of content management for AI is to automatically create the meaning of unstructured content and turn it into structured data linked across multiple systems and processes. In this way, AI helps automate and streamline processes and eliminate errors.

Customer Experience And AI For Personalization

Personalization, powered by AI, is used in many companies to improve the customer experience online and in physical stores. At the time of purchase, it is possible to use machine learning algorithms to provide customers with personalized advice that supports the online user like a traditional salesperson and suggests the right product at the right time without being intrusive and respecting privacy. AI can also help employees of physical stores where the customer is recognized and guided based on previous purchases, products already seen, or registered interests.

The customer experience and artificial intelligence can use a large amount of data consumers leave behind while browsing, such as shopping behavior, preferences, and interests, to launch campaigns with personalized content for each potential customer or customer.

Marketing staff can align the content with the information provided by the AI ​​and innovate their strategies thanks to models based on company data and external communication. Thanks to the knowledge of customer behavior, it is also possible to conduct predictive and more effective target analysis to bring online content closer to the interests of the customer and email campaigns, smartphone messages, and advertising.

Proactive Protection Thanks To AI

In the face of increasingly sophisticated and unpredictable attacks, the collaboration of AI with cybersecurity is the solution that makes it possible to expand and improve the methods of intelligence managed by human staff and keep track of the rapid evolution of threats. Cyber ​​security systems based on AI do not allow the exploitation of an online malware vulnerability.

However, they act proactively, examine the company’s information systems and combine data from various sources, for example, already used attack patterns or interactions on the web. They can also help observe and identify ways in network traffic and propose the security policies to be applied depending on the topology of the network itself to carry out tasks that generally require considerable expenditure of time and personnel.

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