Study: European e-commerce to grow despite challenging consumer climate

European digital commerce is projected to grow by 6 percent annually until 2029, despite the challenging consumer climate. According to the authors of the McKinsey study, “Europe’s new e-commerce agenda: How AI is resetting growth and competition”, this not only indicates “remarkable resilience” but also describes a fundamental shift. Artificial intelligence (AI) is no longer just a supporting tool; it is a driving force completely reshaping European online retail. This transformation is unfolding through five key changes that are fundamentally revolutionising how companies grow and compete with one another.

“Developments in e-commerce range from new methods of product discovery to the complete automation of transactions by AI agents. For retail companies, this means transitioning from individual pilot projects to the full integration of AI into all core commercial and operational processes,” commented Philipp Kluge, a partner at McKinsey in Munich, in a press release.

1) Paradigm shift in e-commerce

The first major change concerns the emergence of a new technological paradigm, replacing previous leaps from catalogue to webshop and from desktop to smartphone. As leading experts emphasise in the study, this new era of AI is fundamentally changing how customers shop and how retailers serve them, as technology is now integrated more deeply into the value chain than ever before.

“AI is the next paradigm shift in e-commerce. We have evolved from catalogues to online shops, from online shops to mobile offerings, and from mobile offerings to platforms. Similarly, AI will fundamentally change how customers shop and how we serve them,” explains Otto CEO Boris Ewenstein in the study.

2) ‘Agentic commerce’ changes the playing field

The second fundamental shift affects consumer behaviour itself and is manifested in what is known as agent-based commerce, or “Agentic Commerce”. In this model, platforms are moving away from being mere user interfaces designed exclusively for the human eye, towards systems that can act autonomously.

Customers are increasingly delegating tasks such as finding the best offer; automatically reordering standard items; or compiling a shopping basket according to defined criteria like price, brand, delivery speed or sustainability. AI systems are increasingly able to interpret consumer intentions, independently evaluate various options and execute multi-step actions, ultimately taking over the shopping process on behalf of consumers.

More than one-third (38 percent) of Europeans already use AI for purchase research. This automation disrupts traditional customer engagement patterns and partially shifts decision-making power from humans to software. According to the study's experts, the market potential is enormous. By 2030, between three and five trillion US dollars in global business-to-consumer (B2C) retail sales could be generated through agentic commerce models.

3) Retailers compete for the favour of algorithms

This development directly leads to the third key change, which redefines the entire competitive landscape. Retailers are no longer primarily competing for the attention or clicks of human users, but for the favour of algorithms. Since AI assistants make the pre-selection for customers, the battle for market share is shifting behind the scenes of data streams.

The authors of the study make it clear that product data, pricing logic, availability signals and delivery reliability are the crucial inputs for this automated decision-making by the software. Therefore, companies must learn to be optimised for machines instead of people.

4) Shopping experiences rely on social media content

The fourth shift affects the internal processes of retailers, transforming creative work in marketing into a strictly data-driven growth lever. AI systems are taking over the automated creation of content, the testing of different product variants and the precise delivery of personalised messages in real time. Industry experts describe in the report that AI increasingly determines what content is created and which messages are shown to whom. At the same time, retail media, the marketing of advertising space directly on retailers' platforms, is becoming a structural lever for companies' profit margins.

“I foresee three different customer journeys. One segment prefers the traditional shopping experience and is often sceptical about AI and data privacy; another segment relies on hyper-personalised recommendations, particularly influenced by social media. Finally, a new ‘headless commerce’ model is emerging, where AI assistants shop seamlessly on behalf of users across different platforms,” predicts David Roberts, chief technology and product officer of the online shopping platform Allegro.

5) AI reinvents omnichannel

The fifth and final change is the establishment of a completely new, AI-powered omnichannel intelligence, which finally eliminates the outdated separation between digital and brick and mortar retail. Instead of viewing data in isolated channels, leading players are bringing all information together on a single platform.

As McKinsey's analysts highlight, AI gives the omnichannel strategy a whole new edge by integrating behavioural, transactional and operational data. This allows for the optimisation of prices, promotions, stock levels and service across the entire customer journey, rather than just at individual, isolated touchpoints.

“Customers don’t think in channels, and neither should we. Omnichannel means consistent pricing, promotions and service, and optimising for the entire customer journey, not just individual touchpoints,” summarises Jesper Damsgaard, senior vice president of e-commerce at the jewellery brand Pandora.

In summary, the study shows that European e-commerce companies face the challenge of radically adapting their business models to these five shifts to avoid falling behind in the intensified global competition. Success in this new reality depends heavily on how quickly organisations advance the networking of their data and implement AI as a central operating system. Only those who manage to seamlessly feed both the customers' autonomous algorithms and their own internal processes with precise data will be able to achieve long-term profitable growth in a market increasingly organised by machines for people.