AI dominates today’s headlines, often framed as an existential threat to jobs, especially for blue-collar workers. Warehousing is frequently positioned as the prime example: people-heavy, cost-heavy, and ripe for automation.
At first glance, Predyktable could be seen as part of that story. After all, we build AI-driven workforce planning for warehouses. On the surface, that might sound like replacing people with machines.
But having spoken to dozens of leaders and operators across the industry, I’ve learned something very different.
The Scale of the Challenge
Warehousing often looks like Exhibit A. Labour makes up 50–70% of warehouse costs, worth around £9 billion a year in the UK alone. The sector employs over 320,000 people, a third of them agency staff, with attrition rates nearing 50% annually.
Globally, the warehousing market is valued at over $1 trillion today and is projected to reach $1.7 trillion by 2030. Across the UK, EU, and US there are hundreds of thousands of warehouses powering global trade – the backbone of retail, e-commerce, and manufacturing. These are economic powerhouses of growth and employment, but many are struggling to keep up with change.
Why Automation Isn’t the Silver Bullet
From pharmaceutical distribution to delicate packaging, warehouses are ecosystems of hundreds of interconnected tasks requiring skill, judgement, and adaptability.
Unless you’re Amazon or Ocado, full automation isn’t viable. Converting a single site can cost upwards of £125M with a payback horizon close to a decade. For the majority of operators, whether retailers or 3PLs, that level of investment is simply out of reach.
And even where automation is deployed, it often creates new bottlenecks if it isn’t orchestrated with labour.
The Human Cost of Firefighting
Too often, warehouse teams are left firefighting. A late order spike. An unexpected absence. The default “solution” is to throw more agency workers into the mix.
But firefighting has a price. Just a 5% inefficiency costs the UK sector an estimated £450M each year.
And behind those numbers are people, people who show up every day, doing their best to keep pace with e-commerce demand. Too often, they’re rewarded with unpredictable shifts, forced overtime, and little space to grow.
The Real Opportunity: Elevating Labour
The answer isn’t stripping labour out. It’s elevating labour.
- Equipping warehouse teams with the tools, skills, and insights to move from reacting to anticipating.
- Giving them confidence weeks in advance about shifts.
- Reducing churn by making work fairer and more reliable.
- Freeing supervisors from spreadsheet admin so they can focus on people, coaching, and planning for the future.
This is what “modernising warehousing” should mean. Not just machines doing more, but people doing better in roles that are more sustainable, skilled, and valued.
Looking Ahead
Some assume AI in warehousing must mean replacing workers. But what I’ve seen, again and again, is the opposite: labour isn’t going away.
The future lies in orchestrating labour, automation, and operations together. Not replacing people, but equipping them to thrive in a modern supply chain.
AI doesn’t have to be the end of jobs in warehousing. If used wisely, it can be the start of a more resilient, human-centred industry; one that balances efficiency with dignity for the people who keep supply chains moving.
And here’s the perspective that really brings it home: if the global warehouse workforce were a country, it would be one of the largest populations on earth.
That scale tells us one thing clearly: the future of logistics will be written not just in code and robotics, but in how we invest in and empower the people who make it all work.