AI From an Analyst's Point of View

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AI From an Analyst's Point of View

What if we developers listened to analysts about AI, just like everyone else?

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Artificial intelligence

It’s always interesting to listen to analysts' points of view on tech topics, at least because they are deeply listened to and followed by many key decision-makers. In this article, I’ll use source Gartner, IDC, and the World Economic Forum as my main sources.

What to Do Over the Two Next Years

Analysts seem to be converging on the fact that 2020 will be the year in which AI will start to take off with the first large-scale deployments. The years 2019 and 2020 will therefore be pivotal for the implementation of AI within companies, which must begin to prepare and reflect on the cases of uses that AI could carry.

Thus, of the five AI myths listed by Gartner, the fifth is to strongly encourage people to start defining an AI strategy now, which must be regularly challenged, even if the need for AI has not yet been felt.

Analysts are therefore advised to start with simple use cases with a short-term ROI, such as the use of RPA and the automation of IT operations. RPA should be used to raise awareness and acculturate people to robotization and the business use of AI. IT automation should be used to raise the technical awareness of IT. This appropriation of AI by the company should thus help to demystify AI.

By demystifying AI, companies will be able to approach this subject in a knowledgeable way. IT departments and businesses will then be able to more easily identify future use cases.

It is also recommended that CIOs prepare for the establishment of an AI Centre of Excellence in order to quickly address future needs. Indeed, skills are lacking, and the time to upgrade skills can be time consuming for employees who will have to work on them.

The HR Effect Is Not Always Studied…

With regard to the professions affected, no profession seems to have been spared, regardless of the level of qualification. However, AI would be above all a boon, and would deal autonomously only with simple cases. Exceptional and complicated cases are the responsibility of human beings.

There is also a risk of an impact on employment. According to the World Economic Forum, it is estimated that 71% of hours worked are by humans, compared to 29% for machines; they estiate in 2022 this ratio will change to 58/42. Nevertheless, to date, studies have converged towards an increase in the number of jobs in absolute terms, but with sectoral disparities, without necessarily being linked to the position.

There is therefore a high risk of professional mobility. The nature of jobs will also change significantly, requiring an increase in skills, and as a corollary to making greater use of external suppliers for specialized tasks. A company's AI strategy must therefore be accompanied by an HR strategy, which may involve training or even retraining its employees.

ai, ai in business, ai use cases, task automation

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