Companies can no longer simply attract talent from abroad or encourage workers nearing retirement to stay on longer. They must also invest in the technological transformation of their business processes.

Experienced workers play a key role in productivity. But getting this generation back to work will not save the economy, as researchers at the Institut du Québec point out. They insist that retaining early retirees or encouraging retirees to return to the workforce will not solve the current labour crisis.

For example, the labour force participation rate for Quebecers aged 60 to 69 is 39.1 per cent, one of the lowest in the industrialized world (the rate is 46.3 per cent in Ontario). If all retirees in this age group were to return to work, only 37,000 people would be added to the Quebec labour market. A drop in the ocean since employers have 255,000 positions to fill and according to this article since September, the job market is growing from coast to coast.

And the situation will not improve over time, as 78% of Quebec workers aged 45 and over plan to retire at age 65 or earlier, according to the Institut de la statistique du Québec. Worse: three-quarters of people aged 55 to 70 will not return to work, regardless of the conditions, according to a recent Bank of Canada survey.

This is without considering the effect that recent waves of resignations will have on organizations. Recently, many workers have left their jobs due to burnout, others have, since the pandemic, decided to reorient themselves or they have been tempted by better working conditions elsewhere. Add to the mix the phenomenon of “quiet quitting“: those employees who are content to do the bare minimum at work – just enough to avoid being fired. This “workforce volatility,” as Gartner calls it, will negatively affect 40% of organizations by 2025.

Invest in automation
It’s for all these reasons that companies need to invest in technology solutions like robotization and, artificial intelligence (AI). And they need to do it now. Because such disruptions normally take a long time to take hold in society. For example, only 3% of U.S. businesses were connected to electricity 20 years after Thomas Edison invented the light bulb, the Harvard Business Review recently reported in an article by Ajay Agrawal, Joshua Gans, and Avi Goldfarb. A passivity that hasn’t changed in a century, despite the current technology race.

Why are companies slow to embrace AI? By asking Chat GPT, a chatbot launched by OpenAI in November 2022 that has made the use of artificial intelligence accessible, we learn that companies can be slow to adopt AI for several reasons. Primarily, because implementing this technology involves changing behaviors, evolving skills, and profoundly disrupting the company’s infrastructure.

AI is not a miracle solution, but it plays a very important role in ensuring the future of organizations. It enables changes in governance and business processes so that the company can focus on its core mission, without being distracted by constraints like workforce volatility.

Most importantly, AI enables better decisions to be made through predictions made with data. To do this, a leader must use foresight and judgment. While judgment is essentially an intuitive process, influenced by experience, culture and environment, foresight is informed by facts and data. And AI is adept at processing information from huge amounts of data.

AI and automation can touch all parts of an organization. Especially where humans are needed to do tasks that are time-consuming, repetitive or offer little added value. Such innovations create value by eliminating much of the bureaucracy: repetitive accounting tasks, resume analysis, payroll, inventory, procurement or IT infrastructure management are all examples. AI can also be integrated into existing management systems, such as ERP or CRM software. It can provide a more accurate picture of an organization’s situation by taking into account factors that are often underestimated or unforeseen, because it is learning.

Linked to robotization, AI can also automate certain tasks on manufacturing or logistics chains. One example is IKEA, which has used GreyOrange to optimize order processing and transform its operations: an innovation that earned the Swedish giant the “Best Use of Robotics” award at the Supply Chain Excellence Awards in 2021.

Today, manufacturing lines are being transformed by a new generation of robots. They are more agile and safe. Those who operate them have no specialized post-secondary training, as they control them with icons on their digital tablets.

But this kind of shift can’t be improvised. It requires planning at all levels of the organization. It is especially important to identify the bottlenecks where the efficiency gains will be the highest, based on the investment and effort required to implement and manage the change. To ensure success, we must take the time to describe the expected changes, the requalifications, the steps, the deadlines, the costs, etc.

Pragmatism is required, with input from executives and, most importantly, employees. Because AI and robotization arouse both fears and fascination. Ultimately, employees need to have confidence not only that the shift will improve their experience by making them more efficient, but also that they will remain useful and valued, continuing to do what AI will not be able to accomplish, because only humans can humanize things.

References:

  1. https://www.lapresse.ca/affaires/chroniques/2023-01-06/mauvaise-nouvelle-les-emplois-augmentent.php
  2. lapresse.ca/affaires/chroniques/2022-10-13/les-vieux-ne-sauveront-pas-l-economie.php
  3. https://institutduquebec.ca/ IDQ, 2022 , A llonger les carrières : défis et opportunités pour pallier les pénuries de maind’œuvre
  4. https://hbr.org/2022/11/from-prediction-to-transformation
  5. https://www.gartner.com/en/newsroom/press-releases/2022-10-18-gartner-unveils-top-predictions-for-it-organizations-and-users-in-2023-and-beyond
  6. https://www.forbes.com/sites/bernardmarr/2022/10/19/the-disruptive-economic-impact-of-artificial-intelligence/?sh=3bd0e5b640b7
  7. https://www.economist.com/business/2022/09/08/why-the-fuss-over-quiet-quitting