The future of artificial intelligence

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Even if it is always difficult to answer the question "where should we be positioned in 3 years' time", it seems clear that the strengths of artificial intelligence make it an essential ally. Of course, AI cannot do everything. Not every use case can be solved with AI. But doing without seems a perilous choice. It's better to start with one or two well-chosen use cases and develop skills that are likely to be in high demand on the market very quickly (Python....).

Some key trends in artificial intelligence

At least half of all organisations have adopted AI functions within their organisation. As organisations continue to automate day-to-day operations, AI is becoming increasingly important. Businesses are more digitally connected than ever before and working from home has sprung into action. The adoption of AI is limited to improving operational efficiency or operational effectiveness. It can also be harnessed to improve stakeholder experience. Let's take a look at some of the key trends expected.

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Greater collaboration between cloud and AI

Artificial intelligence will play an important role in the widespread adoption of Cloud and Edge Computing solutions. By deploying AI, it will be possible to monitor and manage cloud resources and the vast amount of data available.

AI solutions for IT

The number of AI solutions being developed for IT will increase. AI solutions capable of detecting common IT problems on their own and self-correcting malfunctions or problems will increase in the coming years. This will reduce downtime and allow an organisation's teams to work on highly complex projects and concentrate elsewhere.

Greater collaboration between cloud and AI

Artificial intelligence will play an important role in the widespread adoption of cloud and edge computing solutions. Thanks to the deployment of artificial intelligence, it will be possible to monitor and manage cloud resources and the vast amount of data available.

AI solutions for IT

The number of AI solutions being developed for computing will increase. AI solutions that can self-detect common computer problems and self-correct malfunctions or issues will see an increase in the coming years. This will reduce downtime and allow teams in an organization to work on very complex projects and focus elsewhere.

AIOps is becoming more popular

In recent years, the complexity of computer systems has increased. Vendors want platform solutions that combine more than one monitoring discipline, such as application, infrastructure, and network. IT operations and other teams can improve their processes their decision-making and their tasks thanks to AIOps solutions and better analysis of the volumes of data reaching them. Now is a good time to find AIOps vendors that will drive collaboration across teams through end-to-end digital experiences, data correlation, and IT operations management toolchain integration.

AI WILL HELP YOU STRUCTURE YOUR DATA

As early as 2022, we will see more unstructured data being structured through natural language processing and machine learning processes. Organizations will take advantage of these technologies and create data that RPA or robotic process automation technology can use when it wants to automate transactional activity in an organization. RPA is one of the fastest growing areas of the software industry. The only limitation it faces is that it can only use structured data. With the help of AI, unstructured data can easily be converted into structured data, which can deliver a definite result.

ARTIFICIAL INTELLIGENCE WILL BECOME EASIER TO EXPLAIN

How can you trust when you don't fully understand? In the future, more emphasis will be placed on the ability to explain, simplify, illustrate through metaphor, on the popularization of concepts and on the democratization of the adoption of uses. As new data regulations come into play, trust in AI will be essential. This will involve understanding and clearly explaining how each feature will contribute to the final prediction or output of the machine learning model.

VOICE AND LANGUAGE-BASED INTELLIGENCE

The rise of remote working, especially in customer service centers, presents a great opportunity to adopt automatic language processing or automatic speech recognition capabilities. Less than 5% of all customer contacts are subject to systematic quality control. Due to the lack of one-on-one coaching, organizations can use AI to perform routine quality checks on customer understanding and intent to ensure ongoing com