Are we surrounded by Artificial Intelligence? Solutions and applications of the technology of the future

10 Aug 2022

ChatBots, predictive tools, process automation, Machine Learning, natural language interpretation, data processing, Digital Twins… What do these solutions and technologies have in common? Exactly: Artificial Intelligence. Nowadays, it is almost too difficult to talk about technology and digitalisation without disscusing AI, and its applications seem infinite in terms of solutions, use cases, and sectors. From banking to telecommunications, industry to retail, layers of intelligence are transforming all kinds of businesses, there is a wide scope and a great value regarding this technology.

Artificial Intelligence within other technologies and solutions

Some of the solutions, and technologies that use Artificial Intelligence are:

  • ChatBots or cognitive agents. Although there are different types, the most advanced are those equipped with AI, as there are no limits on giving stagnant answers on general topics, but they can follow a conversation, understanding natural language, and taking different routes according to the needs of the interlocutor.
  • Predictive analytics. Thanks to AI, it is possible to take data analysis a step further, making predictions or estimates about all kinds of events. We could use it for scorings, creation of clusters, regressions, binary classification, etc.
  • Data processing. There are simple tools such as OCR, capable of “reading” data in structured documents. For unstructured documents, however, more advanced AI-enabled tools will be needed. These could even extract the most important data from an audio or video file. Not only that, but AI will allow information to be classified automatically.
  • Process automation. In the initial stages, the automation of some processes can be done through simple robotisation. This could be desktop-level or more advanced automation, capable of following complex rules for repetitive and recurring tasks. But if we want to move towards autonomous decision-making, AI-enabled robots can make it possible to automate more critical processes for companies and not just simple tasks.
  • Digital Twins. Digital twins are replicas of real products, services, or processes’ but digitally. To achieve a digital twin, we must collect a range of data from the original product, service, or process using tools such as IoT, Big Data or AI to manage the data, make predictions or build Machine Learning models.

Applications of Artificial Intelligence in different sectors of activity

AI can have multiple applications in different sectors and areas of activity, for example:

Artificial Intelligence in the insurance sector

Within insurance companies, Artificial Intelligence can add value in different areas:

  • Creation of intelligent Chatbots to improve customer service, from recruitment to the registration of a claim or any other need that may arise.
  • Innovation for processing data with AI will allow decision-making on new lines of business, new products, or different personalisation options.
  • Improved onboarding processes. In addition to KYC (Know Your Customer) technology for identifying customers digitally, using other technologies such as AI or Machine Learning will improve the process, reducing friction for the user.
  • Maximum personalisation using Artificial Intelligence to create tailor-made, configurable policies, calculating risks and prices in real-time.
  • Improved efficiency by incorporating automation and AI into company processes.

Artificial Intelligence applied to Marketing:

In the field of Marketing, Artificial Intelligence provides useful tools:

  • Customer segmentation through clustering (predictive analytics based on Artificial Intelligence).
  • Intelligent CRM is also equipped with predictive analytics to create lead scoring or sales forecasts.
  • Easier creation of audiovisual content, thanks to intuitive platforms capable of applying filters, automatic image enhancements, removing backgrounds, etc.
  • Application in the algorithms of social networks and other platforms, which continuously modify the content marketing landscape.
  • Creation of Chatbots to assist customers in their Customer Journey and boost sales.
  • Data-Driven Marketing, which will automate marketing decisions based on customer behaviour.

Artificial Intelligence in manufacturing processes

Some of the applications of AI in industry and manufacturing processes are:

  • Improved quality, thanks to the automatic detection of errors in the production chain.
  • Reduced breakdown costs and production downtime through preventive maintenance of machines due to the combination of IoT and Artificial Intelligence with its predictive features.
  • Increased efficiency by predicting demand for better stock management of raw materials and final products, also reducing storage costs.

Artificial Intelligence in the energy sector and a transition to sustainability

In the field of energy, which is transitioning toward more sustainable models and decarbonisation, we find that Artificial Intelligence can help in different ways:

  • Improving the efficiency of renewable plants thanks to digital twins. For example, a Digital Twin of a windmill in a wind plant can be created to predict its behaviour, power generation, possible failures, etc.
  • Easier to predict energy demand thanks to predictive analytics (which is based on AI).
  • Ability to anticipate weather conditions and other factors that may affect renewable energy production.

In addition to these examples, we could also talk about AI applied to banking, with risk prediction, Chatbots, creation of personalised financial products, etc. It could also be applied to transport and logistics, finding the best routes, in telecommunications to automate certain processes, and even in the public sector to automate tasks or generate recommendations for citizens. There is no doubt that Artificial Intelligence is one of the most relevant technologies at the moment, and it is estimated that it will reach 126 billion dollars by 2025. Its current applications are many, but the truth is that it is still being researched and developed to reach increasingly advanced solutions, which is why we will probably see use cases that revolutionise the way we interact with these sectors.

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