Will AI take your delivery job? A Real Look at Logistics, Robots, and the Road Ahead

MBL Team
2 days ago
13 min read

A futuristic delivery scene – a courier and a four-legged robot work side by side, transporting packages in front of a modern warehouse. — Man and machine in last-mile logistics – this is what modern delivery robot tests really look like.

AI is already here. Not in ten years. Now.

But will it take your job? Let’s see.

Are you a delivery driver? If so, you’ve likely already noticed the changes — your navigation app is becoming smarter, your dispatcher often knows about road issues before you do, and fleet management systems are predicting almost everything.This is no coincidence. It’s AI in logistics — already transforming how you work today.

But the real question is: do these changes mark the end of your career, or the beginning of it — in a completely new form?

What AI Is Already Doing in Logistics (Here and Now)

Before we begin speculating about the future, let’s look at the present.Artificial intelligence is no longer science fiction — it is now an integral part of the supply chain.

AI in Route Planning

Your routing app knows about a traffic jam before you even set off. That’s not magic — that’s AI.

Systems like Wise Systems use advanced machine learning algorithms that analyse real-time data from multiple sources.And it’s not just basic traffic data — AI considers historical patterns, weather forecasts, local events, and even individual driver behaviour.

Amazon has taken things even further with Wellspring — a generative AI system that creates detailed delivery maps.This technology identifies building entrances, parking spots and specific flat numbers in apartment complexes, using satellite imagery, road network data, and customer instructions.

As a result, drivers receive precise guidance on optimal delivery points, significantly reducing stop time.

Smart Dispatchers

Dispatchers no longer just assign routes — they collaborate with AI systems that predict problems before they happen.

Machine learning models analyse traffic patterns, weather conditions, and even social media updates to proactively suggest alternative routes.

Wise Systems introduced Machine Learned Service Times — a system that accurately predicts how long each stop will take.

The AI accounts for parcel size and weight, delivery priority, delivery type, the specific driver, the day of the week, and even the time of the month.

This enables route planning with over 90% accuracy.

Predicting Traffic and Delays

AI doesn’t just respond to current conditions — it can anticipate them in advance.

Systems analyse historical shipment data, weather patterns, geopolitical events, and live traffic conditions to forecast potential delivery delays.

One leading logistics company integrated predictive AI analytics and reduced transport delays by 30%.

Dynamic Predictive Visibility (DPV) has been evolving for over a decade.Initially, its prediction accuracy was only around 30%, but today — thanks to improved algorithms — it exceeds 70%.

Delivery Time Window Optimisation

AI-powered systems don’t just plan routes — they also optimise delivery time windows.

Amazon uses machine learning models to analyse sales history, market conditions, and regional variations.

The system can forecast, for example, a rise in demand for ski goggles in Boulder during ski season or a surge in orders for specific products during sales events.

Order Distribution Applications

Platforms such as Onfleet and DispatchTrack use AI to automatically allocate delivery tasks.

DispatchTrack’s AI-powered routing optimisation builds schedules for thousands of vehicles within minutes, achieving 98% accuracy in estimated arrival times.

The system learns from real-world delivery data — including traffic, driver performance, and handling times — eliminating the need for time-consuming manual planning.

Onfleet offers advanced route planning and optimisation features that significantly reduce delivery times and increase efficiency.Its mobile app, with over 7,000 ratings and an average of 4.8+ stars, is the highest-rated last-mile delivery app in the industry.

Robots Tested in Deliveries: Truth, Not Hype

Now let’s move on to what worries delivery drivers the most: robots.

Are they really being tested in deliveries? Yes — but the reality is more nuanced than it may seem.

Spot by Boston Dynamics Tested by Evri

Evri, the UK’s largest dedicated parcel delivery company, became the first in the country to trial deliveries using four-legged robots.

The Spot robot from Boston Dynamics has been equipped with a secure delivery compartment and is currently being tested in Barnsley.

Spot can move over difficult terrain, walk on stones or stairs — unlike most mobile robots.

It moves at a speed of 1.6 m/s, handles inclines of +/- 30 degrees, carries up to 14 kg, and operates for about 90 minutes on a single charge.

But — and this is crucial — the robot does not replace the courier; it supports them.

It jumps out of the van and delivers parcels to doorsteps, easing the courier’s physical workload.

Boston Dynamics’ Spot robot — the same model tested by UK-based Evri for last-mile delivery support, pictured without company branding. — Boston Dynamics’ Spot robot – the exact model used by Evri in trials supporting courier operations.

DPD and Autonomous Courier Robots

DPD has gone a step further, testing fully autonomous delivery robots. Trials began in Milton Keynes in 2022 and have since expanded to Raunds, Bristol, and Lincoln. The Cartken robots, operating at Level 4 autonomy, navigate pavements using only cameras — making DPD one of the few in the sector to achieve this with a vision-only system. Since July 2022, these robots have travelled nearly 500 miles and successfully completed over 2,500 deliveries. They operate within a one-mile radius of a depot, have up to 12 hours of battery life, and can handle up to 30 deliveries per day.

Elaine Kerr, CEO of DPD UK, emphasised: “Realistically, we won’t be replacing our delivery drivers any time soon. Nor would we want to. The service they provide is fantastic.”

Yandex delivery robot — one of the models used in DPD’s autonomous delivery trials, shown in an urban environment. — **Yandex delivery robot – one of the models tested by DPD for last-mile urban deliveries.**

Amazon Scout, Starship Technologies and Others

Amazon is trialling a system called Vision Assisted Package Retrieval (VAPR), an AI-powered tool that projects green circles onto parcels meant for delivery at the current stop and red Xs on those meant for later. The system will be rolled out to 1,000 Amazon vans next year, potentially shortening delivery routes by around 30 minutes.

Meanwhile, Starship Technologies is a pioneer in robotic autonomous delivery, already operating in multiple cities worldwide — including across the UK.

NHS Drone Trials for Medical Deliveries

The NHS is launching a genuine revolution in medical logistics. Northumbria Healthcare NHS Foundation Trust will begin using drones to deliver medical supplies to around 30 facilities from next autumn. Zipline electric drones, with a range of 130 miles, will deliver prescriptions, wound care supplies, and other essential items by parachuting them onto hospital grounds.

In London, BVLOS (Beyond Visual Line of Sight) drones are already flying over the city centre, carrying urgent blood samples for the NHS. The first flight took place on 7 October, servicing a route between Guy’s Hospital Cancer Centre and the lab at St Thomas’ Hospital. A journey that would take over half an hour by car was completed by drone in under two minutes.

A Robot at Your Door? Relax – It Won’t Climb to the Third Floor

All of these systems still face significant limitations and require human support.

Smart Lockers, Facial Recognition and Dynamic Delivery

Automation today goes far beyond robots — it includes intelligent delivery systems that are already transforming how we receive parcels.

InPost and the Next Generation of Smart Lockers

InPost is rolling out autonomous parcel lockers powered by solar energy. These lockers retain the functionality of standard machines but are equipped with rooftop solar panels and an energy storage system that functions even in sub-zero temperatures. A built-in battery allows them to be deployed virtually anywhere, regardless of access to the power grid.

In addition, InPost integrates AI into its customer service: intelligent, self-learning chatbots respond to customer queries in real time. Back in 2017, the company was the first in the industry to adopt AI — well ahead of its competitors.

Smart Lockers and Biometric Verification

Amazon has implemented facial recognition technology to verify the identity of its Flex drivers. The system scans drivers’ selfies and cross-checks them with ID documents to ensure only authorised personnel gain access. Uber had previously introduced a similar approach.

Real-Time Delivery Point Adjustment

Dynamic delivery is no longer a futuristic concept — it's happening now. AI systems analyse traffic data, weather conditions and customer availability in real time, adjusting delivery times and locations accordingly. These systems can even anticipate congestion before it occurs and redirect drivers proactively.

Predictive Delivery — Before the Customer Even Realises

Amazon uses generative AI to forecast product demand with exceptional accuracy. The model factors in regional patterns, market conditions, sales trends, and external events. As a result, forecasting accuracy has improved by 10% nationwide and 20% regionally for millions of popular products.

According to WISMOlabs, AI systems can now predict delivery dates within 1–2 days of actual arrival, based on data from thousands of previous shipments.

Automation in Sorting Centres – Where Jobs Truly Disappear

This is where the situation becomes more dramatic than on the road. Sorting centres are undergoing a true revolution.

Amazon and Warehouse Automation (Kiva Robots)

Amazon acquired Kiva Systems in 2012 for $775 million. Kiva robots reduce order fulfilment times from 60–75 minutes to just 15 minutes. Warehouses equipped with Kiva robots can store up to 50% more inventory, as the robots occupy less space than traditional systems.

Amazon currently uses over 750,000 robots to sort, lift, and move parcels.

The latest Sequoia system integrates AI, robotics, and computer vision to consolidate inventory and improve efficiency. Sequoia allows Amazon to identify and store inventory up to 75% faster.

Cardinal, a robotic work cell, uses advanced AI and computer vision to select a single parcel from a pile, read the label, and place it precisely into a GoCart. Amazon is currently testing the Cardinal prototype to handle parcels weighing up to 50 pounds.

DHL and Automated Sorting Centres

DHL is implementing DoraSorter – AI-based robotic systems in its Atlanta distribution centre. The robots process parcels in an average of 3.6 seconds with an almost zero error rate.

Both systems are equipped with 3D scanners and can sort approximately 1,000 parcels per hour, with a maximum weight of 6.8 kg. The “sort-to-bag” configuration increases efficiency by 80%, while the “sort-to-Gaylord” system features a proprietary conveyor belt that enables the sorting of diverse parcel types into twenty separate five-foot Gaylord containers. DHL plans to invest $100 million in automation over the next five years.

Ocado – A Human-Free Warehouse

Ocado uses 3,000 robots in its automated warehouse in London. These washing-machine-sized robots move across a grid at 4 metres per second, passing each other with just 5 mm of clearance. They are controlled by artificial intelligence operating like air traffic control.

The robots can complete a typical 50-item order in just 5 minutes with 99% accuracy.

Alex Harvey, Head of Advanced Technology at Ocado, stated that the company's goal is full automation and delivery of products without any human touch.

In 2024, Ocado picked over 30 million items using AI-driven robotic arms, achieving significant productivity gains with only a minimal number of arms installed.

Then: 40 Workers – Now: 6 Technicians + AI

The statistics speak for themselves. Amazon achieved a 22% reduction in operational costs per warehouse thanks to Kiva robots.

If the Kiva system were deployed across all 110 of Amazon’s fulfilment centres, it could result in savings of $2.5 billion.

Not everything is changing on the road. But in the back-end – there’s no going back.

Fact: warehouse automation is advancing much faster than last-mile delivery automation.

Will AI take your delivery job? – No-Nonsense Facts

Time for an honest conversation. Will artificial intelligence take your job as a delivery driver?

Really — will AI take your delivery job?

Yes – Some Jobs Will Disappear

A report from the World Economic Forum estimates that 85 million jobs will be replaced by robotics and automation by 2025.

Robots are expected to take over up to 40% of warehouse jobs by 2030.

In logistics, the greatest risks are:

• Simple, repetitive warehouse tasks (sorting, packing, lifting)

• Long-distance driving jobs (where autonomous trucks are most effective)

• Basic administrative work (data entry, routine analysis)

Edoxi estimates that nearly 20 million jobs will be replaced by automation in the coming years.

But: AI Won’t Replace Relationships, Judgement, or Improvisation

80% of surveyed companies successfully transitioned staff into higher-value roles, creating entirely new job types.

Research by Politecnico di Milano and Amazon shows that businesses can reallocate people to more complex activities by relieving them from repetitive tasks.

Amazon evolved from a workforce of mostly pickers and packers to over 60 distinct roles, including specialised technicians and data analysts.

In 2024 alone, over 20,000 last-mile logistics workers across Amazon’s European network were trained to operate new technologies.

Distinction: Simple Tasks = Risk; Complex + Human = Safety

Delivery drivers are far more than vehicle operators. They are:

• Customer service experts – they build trust and loyalty

• Problem-solvers – they handle unpredictable situations

• Brand ambassadors – every interaction reflects on the company

• Local logistics specialists – they know their routes better than any algorithm

73% of warehouse operators cannot find enough staff.

Amazon experiences over 100% annual turnover in its fulfilment centres due to demanding working conditions.

Automation isn’t taking jobs away – it’s often the only way to fill critical manual labour gaps.

History Repeats Itself: Every Revolution Takes Something – and Gives Something Back

Fear of technology replacing jobs is nothing new. Every major technological revolution has triggered similar concerns.

Steam, Electric, Digital Revolutions

The Industrial Revolution: mechanised production eliminated some traditional jobs but created new roles in engineering, logistics, and machine operation. The steam engine drove this shift, attracting people to urban centres and generating new employment.

The Computer Revolution: the rise of computers in the 20th century led to fears about the loss of office jobs. Instead, it gave birth to entirely new industries – from software development to cybersecurity. The spread of computing technology is credited with 30–50% of the increased demand for skilled labour since the 1970s.

The Internet Boom: the digital revolution created careers like digital marketing, app development, and e-commerce management – jobs that didn’t exist just decades ago.

New Roles Always Emerge

Data from the UK dating back to 1871 shows that technology has created more jobs than it has destroyed. Between 1992 and 2014, the number of farmers, secretaries, metalworkers, and typists fell by more than 50%, while the number of nurses increased by 900%.

Technology helps us avoid boring, repetitive, and dangerous work. In 1871, only 1.1% of the workforce was employed in care professions. By 2011, nearly a quarter of England and Wales’ workforce worked in such roles.

Today: AI Technician, Systems Operator, Service Engineer, Dispatcher 2.0

The World Economic Forum predicts that automation will create 97 million new jobs by 2025. These roles will include:

Data analysts to monitor AI performance and tune models
Systems integration specialists to connect AI with existing operations
Robotics technicians to maintain and repair automated systems
AI operations managers to oversee human-machine collaboration
Customer service specialists using AI-powered tools

According to McKinsey, 63% of companies report revenue growth due to AI adoption. Top-performing firms are nearly three times more likely to report revenue increases above 10% than others.

How Not to Fear AI – and How to Prepare (A Practical Guide)Survival in the AI era isn’t about escaping technology – it’s about using it to your advantage.

Don’t Avoid New Tech – Embrace ItBe “tech-ready” – test new apps. Get familiar with GPS and route optimisation tools. DispatchTrack requires minimal training and allows drivers to deliver effectively from day one.Onfleet features a user-friendly design that enables drivers to start delivering without additional onboarding. The app has over 4.8 stars and is the highest-rated in the last-mile delivery sector.

Build Your Skills: Communication, Flexibility, Responsiveness

Key delivery driver skills in the age of AI include:

Time management – keeping schedules and meeting delivery windows
Communication – clear, professional interaction with customers and employers
Customer service – leaving a positive impression on behalf of the company
Problem-solving – responding on the spot to unexpected situations
Adaptability – adjusting to new technologies and evolving processes

16% of consumers say they would stop buying from a company after a single poor delivery experience. That’s why drivers must be courteous, professional, and solutions-oriented.

Ask Questions, Learn Fast – That’s How Tech Becomes Support, Not Threat

Lifelong learning is essential. Delivery drivers must be tech-savvy to keep up with innovation. Training programmes are crucial to help drivers adapt to new technologies.

Companies now offer specialised training to equip drivers with the skills to efficiently use GPS navigation, routing apps, and other advanced tools.

What Does MBL Logistics Say? – Our Approach to Technology

We don’t fear innovation – the logistics industry is rapidly adopting AI and automation. Companies are investing in real-time data processing, predictive analytics, and autonomous decision-making tools to streamline operations.

AI is here to support drivers, not replace them. As the examples of Amazon and DHL show, the most effective AI implementations focus on human support – not human removal.

We listen, we learn, and we introduce new tools. 97% of CEOs in the manufacturing sector plan to integrate AI into their operations within the next two years. Early adopters of AI in supply chains enjoy 15% lower logistics costs and 35% better inventory performance compared to competitors.

We are looking for people who don’t just drive vans – but deliver real value. The AI era demands drivers who are flexible, communicative, and ready to adopt new technologies.

Summary: Will AI Take Your Job?

Not today, not tomorrow. But change is coming.

The facts are clear: AI is already reshaping the logistics sector – but not in the way you might fear. Rather than mass replacement of drivers, we’re seeing:

Tech support for drivers (better navigation, predictive route planning)
Warehouse automation – replacing manual labour with robotics
New roles that require human-AI collaboration
Growing importance of soft skills – communication, problem-solving, customer service

The best strategy? Stay one step ahead of the change.

Every technological revolution in history – from steam to digital – ultimately created more jobs than it eliminated. But only those who adapted, thrived.