AI Will Put 10 Million Jobs at Risk — More Than Were Eliminated by the Great Recession

Automation is coming after jobs, from fast food workers to accountants. We analyzed which jobs are most — and least — at risk.

6 min readOct 11, 2017

The shift from traditional manufacturing to computer-enabled industry took nearly a century. But the shift from personal computing to billions of smartphones, massive networks, and the IoT has taken just a couple of decades.

And the next phase of technological evolution is already underway: advanced neural networks that learn, adapt, and respond to situations.

With AI and automation advancing at a breakneck pace, society’s capacity to respond is being stretched to the limit.

10 million US jobs at high risk of disruption

Automation is already all around us. Cities are seeing front-end automated restaurants like Eatsa gaining popularity, while in factories automation has already arguably been a part of life for years (if not decades) in the form of heavy industrial and agricultural robots.

Analyzing the automation landscape, we found that 10 million service and warehouse jobs are at high risk of displacement within the next 5–10 years in the US alone. This includes jobs like cooks and servers, cleaners and janitors, as well as warehouse workers.

Meanwhile, nearly 5 million retail workers are at a medium risk of automation within 10 years.

To put these numbers into perspective, estimates are that over a few years the Great Recession of 2007–2010 destroyed 8.7 million jobs in the US.

With the emergence of industry-specific AI, the effects of automation — initially felt in manufacturing — are seeping into retail sales, restaurants, e-commerce, marketing, and even software development.

The rise of automation (thanks to open source and corporate interest)

How did we get here?

The concept of artificial intelligence was introduced in the 1950s. But the expectations for what an AI system is capable of achieving have changed over the years.

Innovation in microprocessors — particularly Nvidia’s graphic processing units (GPUs) — have played a large role. While Nvidia GPUs were initially targeted at the gaming industry, they have showed promising results in artificial intelligence, and are now widely used in training deep neural networks.

This, combined with easy access to massive amounts of data (from the internet, IoT devices, etc.), led to a new age for AI.

Meanwhile, several big corporations have open sourced their AI software libraries in recent years — another major accelerant for AI.

For example, Google open sourced its TensorFlow machine learning library in 2015, and hundreds of users have contributed back to it and sought to improve it. It’s a two-way street: startups can now build on existing frameworks instead of starting from scratch, and at the same time Google’s own AI research is accelerated by contributions from outside the organization.

Other libraries include Deeplearning4J from startup Skymind and Microsoft’s Cognitive Toolkit.

How corporations are beginning to harness automation

Last year, Foxconn — the largest contract manufacturer of iPhones — laid off 60,000 workers, replacing them with industrial robots.

Some of these were manufacturing robots called “Foxbots” that were developed internally by the company and can reportedly perform up to 20 common manufacturing tasks.

Foxconn has also backed external robotics startups. In Q3’17, it participated in a $20M seed round to Canada-based Kinova Robotics, which focuses on industrial service robots. Earlier this year, it also backed China-based cloud robotics company CloudMinds in a $100M Series A round.

In an interview with Digitimes last year, Dai Jia-peng, general manager in Foxconn’s Automation Technology Development Committee, outlined a 3-phase strategy for complete factory automation: automating dangerous tasks, process line automation, and a third phase that would leave only a minimum number of humans on board for tasks like logistics and quality control.

Nike and Reebok are looking to speed up the supply chain & logistics process as well, and will automate the manufacturing process in coming years to keep up with high consumer demand and quick turnaround times. In 2013, Nike invested in California-based industrial robotics startup Grabit, which is currently deployed in some of Nike’s manufacturing facilities.

But there are hurdles on the road to automation.

Dai Jia-peng told the South China Morning Post that “highly automated manufacturing is still an ideal,” since ever-changing consumer demands require highly flexible manufacturing robots that are able to adapt rapidly to design and manufacturing changes. However, Foxconn has fallen short of its 2011 forecast of installing 1 million robots in its factories in 3 years.

Like Foxconn, most manufacturing- and logistics-focused corporations are progressing on the road to automation in fits and starts.

The road to automation passes through warehouses and factories where robots collaborate with humans (rather than simply replace them).

Amazon, for example, already uses 45,000 robots in various warehouses, but at the same time is creating thousands of new jobs for humans in its new fulfillment centers.

Robots are still less-than-perfect at gripping, picking, and handling items in unstructured environments. Amazon’s collaborative warehouse robots perform much of the heavy lifting, while workers focusing on delicate tasks like “picking” items off shelves and slotting them into separate orders.

The trend stretches deep into physical retail, although we believe e-commerce is the much greater threat to retail jobs.

Walmart has patents for autonomous robots that attach themselves to shopping carts in order to move them around stores, along with drone delivery systems. (A detailed analysis of Walmart patents can be found here).

Robotics are penetrating deep into large businesses including retail, consumer, and medical applications.

At financial institutions, AI is transforming how investment decisions are made.

“It means some functions will change significantly in nature… And it might mean that positions will no longer be there in the future. All-in-all, over the coming five years, around 7,000 functions might be impacted by these effects…” Ralph Hamers, CEO of ING

In financial markets, global risk and asset management firm BlackRock laid off around 40 employees earlier this year, including portfolio managers and stock managers. BlackRock is moving towards robotic stock pickers instead.

Quant hedge fund Two Sigma is hiring researchers for its new deep learning team.

And well-known hedge fund Man Group is betting on AI to power algorithmic trading.

Beyond financial institutions, AI software has penetrated deeply into industries including healthcare, cybersecurity, and e-commerce.

The outsize impacts on the labor markets

The majority of AI applications today still require humans in the loop. For many blue- and white-collar jobs at risk, this means employers will still need hands on deck — just fewer of them.

We used US Bureau of Labor Statistics data to compile a list of occupations that are key to labor markets and job growth in the US. We diagrammed the key tasks involved, and used our diagram to determine the relative level of immediate risk from automation.

Our time frame was the next 5–10 years, and the relative risk of automation was based on factors including tasks involved, current commercial deployment of technology, patent activity, investment activity, technological challenges, and regulations.

We excluded categories such as heavy manufacturing and agribusiness where large-scale automation is already taking place.

Specifically, we looked at over 25 million jobs across 7 industries:

Nurses and health aides (6.9M workers)
Retail salesperson (4.6M)
Cooks and servers (4.3M)
Cleaners (3.8M)
Movers and warehouse workers (2.4M)
Truck drivers (1.8M)
Construction laborers (1.2M)

In addition to the jobs listed above, we explore jobs with a lower — but not insignificant — immediate risk of being replaced with AI in the full report, as well as white collar automation and the jobs of the future, and which skills will be in most demand as AI spreads.

Jump to closer looks at specific trends here:

And if you’d like even more data on the AI startups driving this revolution, be sure to check out the CB Insights platform or subscribe to our daily newsletter to follow the biggest developments in the tech world as they happen.