AI opening door to a shorter working week

Dan Schawbel believes the advent of artificial intelligence presents a unique opportunity to realise the possibility of a four-day workweek for most employees.

The concept of a four-day workweek has been gaining traction in recent years, with proponents arguing it can lead to increased productivity, improved work-life balance, and enhanced employee satisfaction.

In 2018, my company partnered with multinational software company UKG on a global study that uncovered the demand among employees for a four-day workweek.

Since then, the concept has taken off, with countries ranging from New Zealand to Iceland testing it.

The United Kingdom performed the largest trial, with positive results. Some 15 per cent of employees involved said no amount of money would convince them to go back to working a traditional five-day week.

As we stand on the brink of a new era in workplace dynamics, artificial intelligence (AI) has emerged as a powerful catalyst that could make the four-day week a reality for most workers.

Indeed, some business leaders believe AI can shorten the workweek to three days.

Research shows that with generative AI, up to 30 per cent of hours worked today could be automated.

AI has the potential to revolutionise how we work, making a four-day workweek not just possible, but potentially more productive than our current model. Here’s how:

Automation of routine tasks: One of the primary ways AI can enable a shorter workweek is through the automation of routine, time-consuming tasks.

AI-powered systems can handle data entry, scheduling, basic customer service inquiries, and many administrative tasks that currently occupy a significant portion of many employees’ time.

This allows employees to focus on higher-value, more engaging work that truly requires human skills and creativity.

Enhanced decision-making and analysis: AI excels at processing vast amounts of data and identifying patterns that might be invisible to the human eye.

This capability can dramatically speed decision-making processes and provide more accurate insights for businesses.

For example, AI algorithms can analyse market trends, customer behaviour, and internal performance metrics to provide actionable insights to managers.

This can reduce the time spent on data analysis and strategy formulation, allowing for more efficient use of work hours.

Personalised work optimisation: AI can help optimise individual work patterns by analysing when each employee is most productive and tailoring their work schedule accordingly.

This personalised approach could lead to increased efficiency, allowing the same amount of work to be completed in fewer days.

Moreover, AI-powered tools can help prioritise tasks, manage projects more effectively, and even predict potential bottlenecks before they occur.

Continuous learning and skill development: As routine tasks are automated, employees will need to focus more on developing uniquely human skills such as creativity, emotional intelligence, and complex problem-solving.

AI can facilitate this transition by providing personalised learning recommendations and adaptive training programs.

By making skill development more efficient and targeted, AI can help employees quickly adapt to new roles and responsibilities.

Improved collaboration and communication: AI-powered collaboration tools can enhance team communication and coordination, making it easier for employees to work together effectively, even when they’re not at the same physical location.

These tools can automate scheduling, facilitate more efficient meetings, even provide real-time language translation for global teams.

By streamlining collaboration, AI can help reduce the time spent on coordination and communication, allowing teams to accomplish more in a shorter workweek.

While the potential for AI to enable a four-day workweek is exciting, it’s important to acknowledge the challenges and considerations that come with this shift:

Job displacement concerns: As AI automates more tasks, there are valid concerns about job displacement.

Organisations and policy-makers must address these concerns proactively, focusing on reskilling and upskilling programs to help workers transition to roles that complement AI capabilities.

Implementation and integration: Implementing AI systems and integrating them into existing workflows can be complex and time-consuming.

Organisations will need to invest in proper training and change management to ensure smooth adoption and maximise the benefits of AI.

Ethical considerations: The use of AI in the workplace raises important ethical questions, particularly around data privacy, algorithmic bias, and the extent of AI decision-making power.

Clear guidelines and regulations will be necessary to ensure AI is used responsibly and ethically.

Resistance to change: Both employees and management may resist the shift to a four-day workweek, fearing reduced productivity or questioning the feasibility of compressing their workload.

Overcoming this resistance will require clear communication, pilot programs, and a willingness to adapt based on feedback and results.

Industry-specific challenges: While a four-day workweek facilitated by AI may be feasible in many industries, some sectors (such as healthcare or emergency services) may face challenges in implementing such a model.

Tailored approaches will be necessary for different industries and job roles.

To successfully transition to a four-day workweek with the help of AI, organisations and society as a whole will need to take several key steps.

They will need to strategically invest in AI technologies that can automate routine tasks and enhance productivity.

This includes not just the technology itself, but also the infrastructure and training necessary to support it.

As AI takes over more routine tasks, employees will need to develop new skills that complement AI capabilities. Organisations and educational institutions should focus on providing opportunities for continuous learning and skill development.

Simply compressing five days of work into four is not the answer. Organisations need to fundamentally rethink how work is structured, prioritising high-value tasks and leveraging AI to optimise workflows.

Dan Schawbel is a bestselling author and managing partner of Workplace Intelligence, a research and advisory firm helping HR adapt to trends, drive performance and prepare for the future.

This article is part of his Workplace Intelligence Weekly series.