Artificial intelligence is changing job roles, daily workflows and organisational structures. The relevant question for employers is not whether the change is simply positive or negative, but which capabilities it expands, which work it displaces and which new responsibilities it creates.
Automation increasingly handles work that is repetitive or manual. McKinsey & Company estimates that by 2030, between 400 million and 800 million people could be displaced by automation and need to find new jobs under its midpoint and earliest adoption scenarios.
The original article cites the World Economic Forum’s Future of Jobs Report 2020, while its source list links to the 2023 edition. The cited figures estimate that 85 million jobs may be displaced as the division of labour between people and machines changes, while 97 million new roles may emerge. Many of those roles require AI programming, machine learning or data-analysis skills.
Changes to everyday work
AI systems can process large volumes of data quickly, support faster analysis and reduce some types of error. AI-driven analytics, for example, can provide current information about market trends for strategic decisions.
Project-management tools and virtual assistants can automate scheduling, email management and other routine work. A PwC survey found that 54% of executives said AI solutions implemented in their businesses had already increased productivity.
AI can also support remote work through communication tools, task automation and intelligent cybersecurity monitoring. Remote work became widespread during the COVID-19 pandemic and may remain permanent in many sectors. For some organizations, that could mean more flexible hours and a better work-life balance.
There are possible accessibility benefits as well. Voice recognition and text-to-speech tools can improve communication for employees with disabilities. In hiring, algorithms can apply consistent criteria, although that does not guarantee that the criteria or training data are free from bias.
Skills and transition
Employees will need to update their skills as the technology changes. The OECD states that workers will need to upskill or reskill for roles created by AI and automation. That requires ongoing learning from both educational institutions and employers.
The transition will not affect every occupation or community equally. McKinsey Global Institute predicts that by 2030, 75 million to 375 million people may need to change occupational categories and learn new skills. Routine work in areas such as manufacturing and data entry is particularly exposed. Communities that rely heavily on those jobs could face wider social and economic disruption.
Bias, privacy and accountability
Workplace AI raises questions about data privacy, surveillance and algorithmic bias. Policymakers and business leaders need rules that protect workers’ rights and determine who is accountable for automated decisions.
Transparency is a particular problem in deep-learning systems. Their internal decision process may be difficult for users and even developers to explain. When the reason for a decision is unclear, it becomes harder to identify mistakes, challenge biased outcomes or assign responsibility.
Economic concentration
AI can support innovation and growth while also widening inequality. The benefits may concentrate among large technology companies, firms that can afford the investment and workers with advanced digital skills. Other workers may face displacement or wage stagnation. A Brookings Institution study found that AI could increase economic disparities for those reasons.
Concentration of data and resources among a small number of companies can also create barriers for smaller firms and startups. Reduced competition may mean less market diversity and potentially higher prices for consumers.
The risks are connected: bias and limited transparency affect individual decisions, while displacement, surveillance, inequality, market concentration and security affect entire groups. Regulation and oversight therefore have to develop alongside the technology.
Dickens’ full passage is a fitting close:
“It was the best of times; it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness, it was the spring of hope, it was the winter of despair, we had everything before us, we had nothing before us, we were all going direct to Heaven, we were all going direct the other way—in short, the period was so far like the present period, that some of its noisiest authorities insisted on its being received, for good or for evil, in the superlative degree of comparison only.”
Sources
- McKinsey & Company: “Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages.” November 2017.
- World Economic Forum: “The Future of Jobs Report 2023.” October 2023.
- PwC: “Global Artificial Intelligence Study: Exploiting the AI Revolution.” 2019.
- OECD: “Future of Work and Skills.”
- Darrell West: The Future of Work: Robots, AI, and Automation, 2019.