AI Will Create More Work, IWG CEO Warns

Over the past few years, I’ve worked closely with small businesses, remote teams, and content-driven companies that actively use AI tools to “save time.” The promise is always the same: automation will reduce workload. Yet, in reality, most teams I’ve observed are working longer hours, not fewer.

This aligns closely with a recent warning from IWG CEO Mark Dixon, reported by Financial Express, where he argued that AI will create more work—not less—making the widely discussed 4-day work week unlikely to become mainstream.

This article breaks down why that happens, what the evidence shows, and what workers and employers should realistically expect.

AI and the 4-Day Work Week: The Core Argument

What the IWG CEO Actually Said

Mark Dixon, CEO of International Workplace Group (IWG) the company behind Regus and Spaces recently stated that:

• AI increases efficiency

• Increased efficiency raises expectations

• Higher expectations lead to more output, not less work

This challenges the popular belief that AI will automatically translate into fewer working days.

Source: Financial Express, business commentary on AI and workplace trends.

Why AI Often Increases Workload Instead of Reducing It

1. Productivity Gains Reset Expectations

Historically, every major productivity tool—from email to smartphones—has followed the same pattern:

1. Tool saves time

2. Management expects more output

3. Saved time is reinvested into more tasks

Instead of working fewer hours, employees are expected to produce more within the same time frame.

2. AI Creates New Categories of Work

AI doesn’t eliminate work—it reshapes it.

New tasks include:

• Prompt engineering

• AI output review and correction

• Compliance and data verification

• Ethical and bias oversight

These roles didn’t exist before AI adoption.

3. Competitive Pressure Cancels Time Savings

When one company adopts AI:

• Competitors must follow

• Market standards rise

• Speed becomes non-negotiable

As a result, no company can afford to slow down, even if productivity improves.

Real-World Case Studies

Case Study 1: Marketing Agencies Using AI

Many digital marketing agencies adopted AI writing tools to cut content creation time.

What actually happened:

• Output doubled or tripled

• Clients demanded faster turnarounds

• Editors worked longer hours reviewing AI drafts

Result: Same deadlines, more deliverables.

Case Study 2: Software Development Teams

GitHub Copilot and similar tools sped up coding.

Observed outcome:

• Faster code delivery

• More frequent releases

• Higher maintenance and review workload

Developers spent less time typing code but more time debugging and reviewing.

Case Study 3: Customer Support Automation

AI chatbots reduced first-level support tickets.

However:

• Complex issues escalated to humans

• Customers expected instant responses

• Support agents handled more emotionally intense cases

Net effect: Higher stress, not fewer hours.

Comparison Table: AI Promise vs Reality

Aspect	AI Promise	Real-World Outcome
Work hours	Reduced	Often increased
Productivity	Moderate gains	Expectations rise faster
Job roles	Fewer tasks	New tasks created
Stress levels	Lower	Frequently higher
4-day work week	More feasible	Still rare

Why the 4-Day Work Week Struggles to Scale

Industries Where It Might Work

• Government pilot programs

• Highly unionized sectors

• Fixed-output roles (manufacturing shifts)

Industries Where It Rarely Works

• Tech startups

• Media and content businesses

• Consulting and client-based services

AI-driven industries tend to be output-maximizing, not time-minimizing.

What Experts Agree On

Most workplace economists agree on three points:

• AI boosts productivity, not leisure

• Reduced hours require policy intervention, not technology alone

• Without labor protections, efficiency favors employers

Reputable sources supporting this view include:

• Harvard Business Review

• World Economic Forum

• McKinsey Global Institute

What This Means for Workers and Employers

For Workers

• Learn AI tools early to stay relevant

• Set boundaries around availability

• Focus on high-value skills AI can’t replace

For Employers

• Avoid assuming AI equals fewer staff needs

• Invest in training, not just tools

• Measure outcomes sustainably

Conclusion: A Reality Check on AI and Work

AI is not a shortcut to shorter work weeks. As Mark Dixon’s warning highlights, technology amplifies ambition. Without deliberate structural change, AI will continue to increase workloads rather than reduce them.

The 4-day work week isn’t impossible—but it won’t happen automatically just because machines get smarter.