How AI assistants are transforming shopping into conversation—insights from Sport 2000 CEOs

In this new commerce model, brands no longer need to be found – they must be mentioned, recommended, and suggested by AI assistants. Data quality becomes the key competitive advantage: precise product information, consistent assortments, and clear attributes determine whether a running shoe is recommended to a consumer preparing for her first marathon. Visibility no longer comes from search engine rankings but from real-time trust built between humans and machines.

From search commands to “intent and transaction”

AI assistants such as ChatGPT don’t just replace search bars – they replace the entire concept of search. Users express needs, scenarios, or styles instead of keywords. The AI interprets context, filters, evaluates, and acts. With instant checkout functionality, curated products can be purchased directly within the dialogue, eliminating redirects or shopping carts. “In international markets, particularly in the U.S. and parts of Asia, convenience has long been the key driver,” says Gosau. “Consumers expect seamless processes without having to switch between platforms.”

AI as gatekeeper—a structural shift for brands

For Gosau, this is not surprising: “The instant checkout launched by OpenAI in cooperation with PayPal is a logical step toward what we call ‘agentic commerce’ – a form of shopping in which AI systems not only advise but also execute purchases autonomously.” The implications are profound: consumer behavior will continue to change as AI becomes the gatekeeper of brand visibility, consumer behavior will continue to shift.

Strategically, this means SEO becomes AIO – AI Optimization. Brand content must be machine-readable, and product data becomes an infrastructural asset rather than an e-commerce detail. Visibility arises not only from campaigns but from explainability. Consumers will no longer navigate between platforms; they will communicate with an AI that chooses platforms, retailers, prices, and availability for them.

Trust becomes the core currency

While convenience dominates in the US, Andorfer believes Europe will balance it with trust. “Data protection, transparency, and reliability are deeply rooted in European consumer culture,” she says.

“Retailers and brands will adapt by preparing their product data and services in a way that can be understood and recommended by AI systems.” Andorfer believes established retail structures – such as associations or cooperative systems – have a clear advantage: they can embed digital innovation within an ecosystem of trust.

The more AI assistants on our smartphones and computers get involved in advising, selecting, and buying, the more important trust becomes. What Andorfer aims to achieve through Sport 2000’s cooperative system, large language models like ChatGPT address by integrating Stripe, PayPal, and Shopify. In this context, these partnerships are no longer just technical features—they become strategic anchors of trust. This connection of technology and reliability is crucial, especially in Europe, where skepticism towards AI remains stronger.

This may explain why Andorfer sees development s in Europe as more nuanced than in the US: “Issues such as data protection, trust, and transparency are deeply rooted in consumer culture here. Europe will therefore implement this trend cautiously, but also with a certain depth. In the coming years, we will see retailers and brands begin to prepare their product data, services, and consulting offerings in such a way that they can be understood and recommended by AI systems.” 

The return of physical retail – digitally connected

Interestingly, AI favors proximity. When a product is available locally, AI actively suggests nearby stores – a clear opportunity for connected sports retailers. However, this only works if inventory data is synchronized and real-time availability is provided. As Gosau notes: “Physical retail will thrive in the AI economy not through floor space, but through smart digital integration. This creates a whole new interplay between global technology and local relevance.”

The new discovery layer

For brands, visibility now depends on how well AI can read and recommend them. Product data, descriptions, and availability must be structured for machine interpretation.

Gosau summarizes: “It’s no longer enough to be present on social media or optimize search engines. How well a brand can be “found” in AI systems will be crucial. Product data, descriptions, availability, and reviews must be structured in such a way that AI can interpret and recommend them. The new discovery layer is the conversation.”

This forces brands to confront critical questions:

• How do we remain visible in the age of intelligent discovery?
• Can machines understand our product data?
• Is our brand logical, consistent, and narratively compelling for AI?
• How do agentic systems interpret our product range?

In the future, three factors will determine visibility:

1. Data consistency and structural precision
2. Narrative clarity and semantic depth
3. Genuine cooperation with AI platforms

Campaign reach may lose its power as a result. “This development is driven by consumers, not technology,” emphasizes Gosau, explaining further: “Younger target groups in particular expect advice, inspiration, and purchase to take place in a single moment. Those who make this possible—whether online or in-store—will be at the forefront of the next generation of retail.”

The global AI race

AI shopping assistants are becoming the new standard in online retail, and indeed already are. We are all familiar with them, and many of us have already interacted with them. Examples include Zalando’s Discovery Feed and Amazon’s Rufus.

Pinterest’s assistant is particularly exciting. This AI clearly shows where the journey is headed, as the assistance system combines images, voice, and text to organically link inspiration and purchasing flow – similar to how humans browse. What all systems have in common is that they learn preferences. They analyze community signals such as boards, reviews, or comments and use them to develop hyper-personalized recommendations. E-commerce is becoming more personal, faster, and more situational. This also means that trail blazers will set the standards. Late starters will only serve them.

Ten strategic priorities for the sporting goods industry and specialist retailers

The transformation breaks down into ten key steps:

1. Make product data AIO-ready

2. Develop AI-compatible brand storytelling

3. Ensure data quality along the entire value chain

4. Treat AI as a new sales channel

5. Optimize product ranges for AI triage

6. Connect brick-and-mortar shops digitally

7. Build AIO-enabled websites

8. Adapt payment and fulfilment processes

9. Train teams for AI commerce

10. Experiment early—before standards are set in stone

Brands must learn to speak AI

AI assistants aren’t simply the next step in e-commerce evolution—they represent a systemic shift. Consumers no longer search; they delegate decisions. Data quality and storytelling will define visibility.

“Younger generations are already open to this form of interaction,” says Andorfer. “They seek advice from AI, compare options in conversation, and expect the purchasing process to be as easy as chatting itself.”

The customer journey no longer begins in a browser—it begins in a conversation. Brands that learn to speak with AI clearly, consistently, and in a data-driven way will define the future.