DHL Logistics Trend Radar 7.0: Full Report Compilation – AI & Sustainability in Focus (2025)

Full Report Compilation

Insights. Shaping Tomorrow.

Your guide to innovation in logistics.

AI & Sustainability in focus.

Contents

Introduction 03

What’S New 05

Innovation Approach 06

The Logistics Trend Radar 7.0 07

Social & Business Trends 08

Technology Trends 88

Special Thanks & Contribution 195

The DHL Logistics Trend Radar

is an invaluable strategic resource for our

customers and the logistics community.

It consolidates key logistics trends, with

artificial intelligence and sustainability

taking the lead in this edition, driving the

evolution of businesses, consumers, and

technologies over the next decade.This

empowers our customers and us to stay

competitive in a demanding landscape.

Katja Busch

Chief Commercial Officer And Head Of

Dhl Customer Solutions & Innovation

INTRODUCTION Contents Radar

Insights. Shaping Tomorrow.

Dr. Klaus Dohrmann

Vice President,

Head Of Innovation & Trend Research

Project Director & Co-Author

Today’s professional climate is often called the “new Shaping to­mor­row re­quir­es in­no­va­tion and col­l abo­

normal,” implying our world has changed significantly ra­tion. The DHL Logistics Trend Radar underscores

since the global pandemic. But this new state is not static. the signi­fic­ance of both, enabling a deeper, shared

We are living in a period of constant transformation in understanding of emerging trends, anticipating future

society, business, and technology. Successful logistics disruptions, and encouraging organizations to foster

organizations are responding powerfully to this by partnerships. Collaboration within and outside the

putting customers at the center of every action, aiming industry is the most effective way to create and co-

for supply chain excellence that is global, resilient and, create groundbreaking solutions and proactively adapt

above all, sustainable. strategies to stay ahead of the curve.

Over more than a decade, the DHL Logistics Trend Please enjoy the discovery and inspiration of the latest

RadarTM has become a recognized benchmark for trends influencing logistics. We welcome you to connect

strategy, innovation, and education, helping logistics with the open DHL innovation ecosystem, and we look

professionals navigate ever-evolving landscapes and forward to shaping tomorrow together through true

seize new opportunities. With this seventh edition, innovation – beyond potential.

our commitment remains the same – to provide DHL

customers, colleagues, and partners with valuable

insights that reflect the direction of societies, businesses,

and technologies, enabling the logistics community to

shape tomorrow.

WHAT’S NEW Contents Radar

The DHL Trend Research team has been closely altered the composition of this latest publication, the

monitoring key technology as well as social and Logistics Trend Radar 7.0. There is more focus on trends

business trends for over a decade. Every two years, identified with an adoption timescale of five years or

the team updates the Logistics Trend Radar to reflect less, as well as showcasing noteworthy developments

our perspectives on the development of existing in artificial intelligence (AI) and in sustainability.

and newly emerging trends, and how they impact

logistics as a whole. The basis of the Logistics Trend Radar is DHL’s customer-

centric, integrated approach which empowers us to

Since publication of the previous edition of the Logistics harness the perspectives of our valued cust­omers along

Trend Radar in 2022, we have witnessed several with those of DHL colleagues who are on the ground daily,

relevant developments that influenced both trend driving and experiencing the transformation of logistics.

adoption and trend impact. This has changed the We complement these insights using classic research

position of some trends on the radar. Additionally, methodologies and incorporate the viewpoints and

through countless engagements with customers, assessments of multiple experts, including key opinion

colleagues, and partners, we have identified new leaders from influential think tanks, renowned consultancy

trends to drive enhanced discussions and accelerate firms, and top-tier academia from around the world.

collaboration on logistics innovation. Overall, this has

Logistics Trend Radar 7.0

Overview of changes vs. 6.0

New Trends

E­Commerce Green Urban Workforce

AI Ethics Transformation Audio AI

Evolution Focus

Remote

Environmental Next- Alternative Smart

Big Data Interactive Work &

Stewardship Generation Energy Labels

Analytics AI Teleoperations

Wireless Solutions

Next­

ESG Advanced Remote Smart

Gen AI Generation

Advocacy Analytics Operation Printables

Connectivity

Renewable

Energy Sustainable

Infrastructure Fuels

Graphic source: DHL (2024)

OUR INNOVATION Contents Radar

Approach

It is our core belief that delivering impactful in­no­ with facility managers and workers is testament to

vation in logistics can only be achieved by staying our dedication in visualizing and implementing

close to customers, close to technology, and close solutions that yield benefits for both our valued

to operations. customers and colleagues.

We cultivate open conversations and engagement with Our end-to-end innovation approach starts with

our customers about business strategies, future needs, thought leadership and continues through customer

and challenges in order to validate ideas, develop use engagement, technology scouting, and research,

cases, and leverage technologies and expertise. We all of which enables us to identify and understand

achieve success through strong customer buy-in and technological breakthroughs.

close collaboration across our innovation ecosystem.

This is the foundation of the Logistics Trends Radar

We are dri­ving the trans­for­ma­tion of log­is­tics by track­ and of many other DHL thought leadership trend

ing and en­gag­ing visi­onary de­vel­opers and providers reports. With a finger on the pulse of relevant trends,

across industries and by staying at the forefront of we run proof-of-concept projects in real-world supply

emerging technology and supply chain innovation. chain settings with our customers and within the DHL

This enables us to identify and co-create new solutions network of operations to fully understand application

beneficial to our customers. benefits and challenges. Successful projects open up

opportunities for productization and scaling, so that

We leverage our own global DHL logistics operations these solutions are available internally across DHL

to improve efficiency, quality, sustainability, and safety. operations and commercially to our customers.

Our commitment to spending substantial time on-site

DHL Trend Research Innovation Funnel

Graphic source: DHL (2024)

THE DHL LOGISTICS Contents Radar

Trend Radar 7.0

High Impact Low Impact Adoption

Revolutionary applications that Evolutionary changes with The common way of operating

are potentially disruptive incremental improvements and doing business in logistics

SOCIAL & Contents Radar

Business Trends

Section Contents

AI Ethics 09

Circularity 13

Cybersecurity 2.0 18

Decarbonization 23

Diversity, Equity, 28

Inclusion, Belonging

Digital Marketplaces 32

E-Commerce Evolution 36

ESG Advocacy 41

Everything As A Service 46

Green Urban Transformation 50

Mass Personalization 55

Metaverses 60

Supply Chain Diversification 64

Silver Economy 69

Smartification 74

Space Economy 78

Workforce Focus 82

Social & Business Trends Contents Radar

AI Ethics

The trend of Artificial Intelligence Ethics (AI As the topic of AI Ethics will impact most industries,

Ethics) refers to the increasing focus on the ethical this in turn will have significant impact on the

considerations and implications of AI technologies logistics industry.

and ensuring their responsible development and

deployment. Within this trend we also explore With increasing reliance on AI-powered systems for

legislative developments of AI platforms, and the managing logistics operations, there’s a growing need

implications of data safety and algorithm security. to address concerns regarding the privacy and security

of sensitive data. AI ethics standards will emphasize

AI Ethics is an emerging field concerned with ensuring the importance of robust data protection measures to

the responsible development, deployment, and safeguard customer information and proprietary data.

use of AI technologies. Its development accelerated

in response to growing public awareness of AI‘s Company compliance regulations for employees

ethical implications, fueled by high-profile incidents, have existed for decades. These must, however, be

debates around democratizing it, and developments in amended to also address compliant use of company

regulatory frameworks to address issues such as bias, data when AI is integrated with collaboration tools

privacy, explainability, and transparency in AI systems. and with company portals. Here at DHL, we recognize

company compliance regulations must align with

Topics to be addressed include explainability, trust- national laws. This opens a new domain in the world of

worthiness, transparency, robustness, and compliance and legal clauses/contractual obligations

interpretability. The trend plays a critical role in the for employees.

logistics industry, especially around these topics, as the

number of AI applications increases within logistics and

the supply chain. In particular, data privacy concerns

must be addressed and ethical use of AI platforms must

be ensured.

RELEVANCE TO THE Social & Business Trends Contents Radar

Future Of Logistics

Trustworthy & Explainable AI Ethical End User / Use

Explainable AI is the ability to trace back an algorithm

to the data that it is built on, and find the logical chain

of association from secure and trustworthy data,

and its traceable training, to build a deep learning Consumer ethical behavior around the use of AI

algorithm. In this logic similar to a mathematical systems includes compliant and ethical content

equation, we are able to determine and explain with creation and not publishing deep fakes of any persons.

high confidence the output of what AI has either Examples of this are the creation of deep fake videos

generated or analyzed. Explainable AI can offer of public figures posted with false messages about

insights into the factors influencing demand forecasts, companies, governments, or other public entities. Such

enabling better decision making and accountability. The occurrences would involve hacking and accessing

explainability of those outputs is found in the processing data which is “stolen” and not intended for use beyond

of consumer data which, if tampered with, renders the approved groups of people, and using this data to

output untrustworthy. Here we see an emphasis on generate untrustworthy outputs.

the importance of data security and protection against

cyberattack and hacking. In logistics, employees have access to customer data,

trade secrets, and other sensitive company information

AI can be made explainable and trustworthy through which can be used to build algorithms. Non-compliant

understanding: behavior could stem from this. There is a growing

need to implement robust measures to secure data

Intention: AI systems are constructed by humans to processing and accessibility.

make decisions based on historical data or real-time

information. Predetermined responses are embedded This can also be said for use cases such as AI-

in the AI systems. generated route optimization, or questioning outputs

that appear biased or discriminatory. End users may

Intelligence: The ability to make intelligent decisions report instances of bias to the relevant authorities

with AI systems is facilitated by combining machine or organizations encouraging the development of

learning and data analytics. AI isn’t intelligent like a fairer algorithms and mitigating potential harm to

human being. Human intelligence is closest to what a marginalized groups. Some consumers actively engage

machine can approximate. in co-design processes or participate in feedback

mechanisms to contribute to the development of

Adaptivity: AI systems compile information to make more ethical AI systems. By sharing their perspectives,

decisions based on collecting and adapting to new concerns, and values, all consumers can help shape

information. AI systems can improve the outcome AI technologies that align with ethical principles and

of decision making with information they learn from better service diverse needs and interests.

real-time data.

RELEVANCE TO THE Social & Business Trends Contents Radar

Future Of Logistics

AI Legislation & Democratization

While not legally binding, these guidelines influence

the development and deployment of AI systems in

various sectors, including logistics. Other legislative

implementations, such as the California Consumer

Privacy Act (CCPA), underline the economic impact

of AI and the need for regulatory measures to ensure

ethical use. It is essential to keep pace. For example,

in Singapore, government funding of $20 million

Singapore dollars (US$15.3 million) now enables

people aged above 40 to learn AI models.

General Data Protection Regulation (GDPR), applicable

in the European Union (EU) and the European Economic Democratization of AI involves making AI technologies

Area (EEA), regulates the processing of data and imposes accessible, affordable, and easy to use for the widest

strict requirements on data controllers and processors. range of individuals and organizations, irrespective

Logistics providers using AI systems must comply with of their technical expertise or financial resources.

GDPR principles, ensuring transparency, lawfulness, Key aspects of AI democratization include providing

and fairness in the processing of all data. accessible tools and platforms, offering affordable

pricing models, providing education and training

The European Commission has published opportunities, fostering community collaboration, and

ethical guidelines for trustworthy AI, emphasizing emphasizing ethical considerations in AI development

and deployment.

principles such as fairness, transparency,

accountability, and societal benefit.

The main branches of AI Ethics

Graphic source: Based on DataCamp (2023): Explainable AI – Understanding and Trusting Machine Learning Models

SUMMARY & Social & Business Trends Contents Radar

Trend Overview

Challenges Outlook

The logistics industry faces challenges related to Over the next five years, the logistics and supply chain

algorithmic bias, which can lead to unfair treatment, industries are likely to face heightened regulatory scrutiny

inefficiencies, and discrimination in supply chain regarding AI Ethics, with governments and industry bodies

operations (sanctions and geopolitical events fuel introducing new laws, guidelines, and standards to address

public algorithms). ethical concerns related to data privacy, algorithmic bias,

and accountability in AI-driven logistics operations.

Managing sensitive data within supply chains raises

ethical dilemmas regarding data privacy, security, and Companies operating in logistics and the supply chain are

ownership, particularly when AI systems are involved in expected to increasingly adopt and implement ethical AI

data processing and analysis. frameworks and best practices to mitigate risks, build trust

with stakeholders, and ensure responsible AI deployment.

Ensuring accountability and transparency in AI- This includes integrating principles such as fairness,

driven decision-making processes within logis- transparency, accountability, and societal benefit into AI

tics requires clear mechanisms for understanding, development, deployment, and use.

auditing, and explaining the reasoning behind AI-

generated recommendations and actions. As awareness of AI Ethics grows, there will be a greater

emphasis on ethical considerations throughout the supply

chain, including sourcing, manufacturing, distribution,

and customer engagement. Companies will leverage AI

technologies to enhance supply chain visibility, traceability,

and sustainability while addressing ethical concerns such

as human rights violations, environmental impact, and

employee welfare.

This trend should be carefully monitored with

implementations available for many use cases today.

Related Trends

Advanced Analytics Cybersecurity 2.0

Diversity, Equity, Gen AI

Inclusion & Belonging

Sources:

YourStory (2024): Subsidy to Learn AI Models: Singapore Budget to Accommodate AI Learning for People Over 40

Social & Business Trends Contents Radar

Circularity

The trend of Circularity aims to eliminate waste and However, new legislation is likely to strengthen

pollution by considering the full product lifecycle in progress. A good example of this is the European

advance, designing and utilizing each item and its Commission’s new rules on the ‘right to repair’ for

constituent parts to be returned in the supply chain. consumers, which may incentivize companies to

This trend seeks to reuse, repair, remanufacture, implement more sustainable solutions.

and recycle products as much as possible and, when

these processes are no longer achievable, products Circularity concepts require dramatic transformation

are broken down into reusable components and raw of the processes of product design, production, and

materials and ultimately biodegraded. recycling, which is why the supply chain is a key

enabler of this trend managing and moving flows of

There is gradual but unsteady progress towards a raw resources, goods, returns, and waste among a

circular economy. Although 55% of large businesses new network of users in a sustainable, circular manner.

have committed to circularity, more than half of their Circularity as a trend is therefore likely to significantly

initiatives are narrowly confided to recycling or waste impact the logistics industry, with logistics players

management. Many companies’ strategies are not becoming essential sources of knowledge for the

yet encompassing the full range of technologies and transfer of best practice across sectors. But current

business models for a circular economy, for example, momentum to explore, invest in, and adopt circular

re-engineering products to last longer, embracing products and solutions appears lacking. Hence, it will

repairability, adopting leasing models, reducing virgin take considerable time for circularity to achieve maturity

material use, and providing complementary services and widespread adoption along the supply chain.

throughout the lifecycle of a product.

The Circularity Gap Report reveals the vast

majority of materials entering the economy over

five years to 2023 were virgin, with the share of

secondary materials declining from 9.1% to 7.2%.

RELEVANCE TO THE Social & Business Trends Contents Radar

Future Of Logistics

The Rise of Recommerce

Esteemed platforms like Vestiaire Collective, which

is funded by luxury group Kering among others, are

gaining increasing popularity by offering second-hand

luxury goods such as bags and clothing. Furthermore,

companies like Patagonia embrace recommerce as

part of the business model, prioritizing circularity

and sustainability. As the industry evolves, it is crucial

for companies to consider the long-term environmental

impact of their business models on the future of fashion.

Recommerce business models present challenges for

all industries, especially in terms of goods inspection.

Currently, this task is labor-intensive, although digital

solutions, such as computer vision technology, may help

in the future. However, used items typically have low

profit margins, raising questions about the long-term

Industrial sectors, especially retail, are witnessing viability of these business models.

the rise of recommerce (also known as reverse

commerce), in which previously owned products, The rise of recommerce impacts logistics in several

new or used, are sold and shipped to buyers who then ways. Instead of traditional return logistics, recommerce

repair, reuse, recycle, and/or resell them, extending supply chains redirect return shipments to in-market

the lifespan of the product. This not only promotes repair, recycle, and/or resell channels, leading to more

sustainability but also reduces emissions associated localized, yet complex supply chains.

with manufacturing new products.

This trend is evident in the smartphone sector, with the Circular Packaging

market for new smartphones falling by 3.2% in 2023. In

contrast, International Data Corporation (IDC) estimated

that global shipments of used smartphones, including

officially refurbished and used smartphones, would

reach 309.4 million units in 2023. This corresponds

to an increase of 9.5% compared to the 282.6 million

devices shipped in 2022.

This development is also evident in the e-retail and

fashion sector; however, things are a bit more complex.

While customer-to-customer (C2C) platforms like

Vinted are growing, it remains uncertain whether large

companies are committed to transitioning to a circular

business model or if they view second-hand platforms In the context of circular packaging, plastic remains

as additional income sources only. In contrast to fast a significant concern. Over 90% of the 400.3 million

fashion giants, renowned for their mass production tons of global plastics produced in 2022 was fossil-

and affordability but often lacking a clear and based. In the five preceding years, greener alternatives

dedicated recommerce strategy, the luxury sector has – mechanically recycled, chemically recycled, bio-based

demonstrated notable advancements in this domain. plastics, and carbon-captured plastics – increased only

Relevance To The