Pandemic has speed up the trend already present in the workplace and in the processes automation. The trend to use artificial intelligence initially adapted only within the large technology enterprises in the web industry is now expanding to the other industries. 

The companies and the large enterprise are more and more familiar with the data-driven approach and use it in the decision-making in order to reshape the offering based on the big data analytics and plan targeted actions following the suggestions from the algorithms and artificial intelligence.

The nowadays companies are mature enough to explore new solutions that use tools and technologies to enhance productivity and to adapt to the market changes as the result of easily accessible and cheap computational power.

The governance units in the large enterprises are usually keener to rely on massive quantities of the data to derive useful insights and reports for making a decision regarding next business steps. UnipolTech invests resources to analyze big volumes of data and therefore to transform it into useful information so that Unipol Group and potential customers can make data-driven decisions.

Due to pandemic it is become crucial and urgent to rethink the approach to manufacturing strategies and logistic infrastructures that also led to automation trends acceleration. The manufacturing companies of all the sizes are transforming themselves into the entities with the decision-making process driven by the big volumes of data delivered in the form of simple insights that are easy to visualize and comprehend.

A scenario where one can introduce automation tools like Robotic Process Automation aiming at reducing the costs, improving the manufacturing phases, automating the processes that require little expertise and highly repetitive execution, in other words, at facilitating people in automation of repeating actions, reducing costs and margins of error.

Capgemini estimates that introducing robotics software can bring to reduction of 1/3 of the costs of an external FTE and as much as 1/5 of an internal FTE with an overall saving between 20% and 50% and error reduction of up to 20%.

The World Economic Forum (WEF, 2018, The Future of Jobs Report) expects to see possibly profound changes between the humankind and the machine and as aftermath, a share of the human labor will decrease from 71% in 2018 to 58% in 2022. 

Capgemini estimates that introducing robotics software can create between 20% and 50% in overall saving and help reducing​ errors up to 20%

Are we actually witnessing the world that devides between the jobs that require strong cognitive-decisional skills on one side and the decrease of the number of jobs that are considered simple in terms of performance and compensation on the other? Are the jobs at risk those that require little expertise and routine execution? It looks like it.

Other consequence of this acceleration triggered by Covid-19 is related to recession phenomena: many people think that upgrading the manufacturing line with robotics and the technologies that are required to control them might be too costly for the companies that have been suffering from the crisis. However, the contrary might just happen. According to A Study From Brookings Institute, the most growth of the automation was actually noticed during the economic recessions. It is an extreme response of the entrepreneurs to the revenue losses to reduce the labor costs by replacing the less qualified workers with the machines and by only keeping the highly skilled professionals.

If the pandemic accelerate automation then it will become even more important to manage the transition starting from the very few certain things that we can rely on: all the solutions that will be implemented will require big investments into workers’ education, especially those less qualified so to prepare them for the big change. People will have to learn a more flexible approach, have a desire to learn new things and show willingness to transition. The change will be permanent. This is how it goes.