AI in digital commerce: Where the real value is created
Insights from Digital Commerce 2026 on how data, structure, and execution drive results.
Earlier this month, Epinova hosted the breakfast seminar “The Launch of Digital Commerce 2026” at NOVA House. Through real‑world examples, findings from this year’s report, and fresh analyses of AI, search, and visibility, one insight stood out clearly: when most organisations prioritise the same technologies, it is not ambition that determines results.
What separates those who succeed from the rest is the ability to execute — consistently, data‑driven, and over time.
Across industries and company sizes, the picture is remarkably consistent. Customer journey optimisation, personalisation, automation, and AI are all high on the strategic agenda. Yet the gap between intent and impact remains significant. Digital Commerce 2026 shows that value is realised only when technology is anchored in structure, ownership, and day‑to‑day execution.
Why data comes before AI: Lessons from Villoid’s growth journey
When Jeanette Dyhre Kvisvik, founder and CEO of Villoid, joined the seminar at NOVA House, she shared a candid account of how the company has built growth in practice. Not through rapid AI adoption, but by focusing on fundamentals early on. For Villoid, the initial years were spent creating structure in data — long before scale, profitability, or volume were in place.
The takeaway was clear: AI creates no value without data. Before automation, advanced analytics, or personalisation could work, ownership, quality, and structure of everyday data had to be established. Villoid reflects a broader pattern seen among high‑performing organisations today — they invested first in the groundwork, enabling AI to deliver tangible value later.
The core insight from Digital Commerce 2026: Execution is the real differentiator
The story from Villoid is not an exception. It reflects a broader pattern identified in Digital Commerce 2026. When the report was launched, Ann Kristin and Arild, both advisors at Epinova, presented the key findings. Across industries and company sizes, organisations point to the same strategic priorities: customer journey optimisation, personalisation, data‑driven ways of working, automation, and AI. What separates outcomes is not what companies prioritise, but their ability to translate those priorities into daily execution.
The strategy-execution gap holding many companies back
Digital Commerce 2026 highlights a persistent gap between ambition and practice. Many organisations have clear goals and strong intent, yet struggle to make initiatives operational. Common challenges include:
- limited capacity in teams
- unclear ownership of initiatives
- governance models that favour short‑term results over long‑term value
- insufficient room for continuous testing and optimisation
The consequence is familiar: strategies turn into plans, pilots, or isolated efforts — rather than becoming embedded in how the business actually operates.
Growth is shifting inward: Creating more value from existing customers
Another clear shift emerges in how growth is defined. Where growth previously centred on acquiring more traffic and new customers, it is now increasingly about extracting more value from the existing customer base. Optimising the customer journey ranks highest among priority growth areas. At the same time, the report reveals a tension. While ambitions focus on customer value and long‑term relationships, day‑to‑day decision‑making is still largely driven by traditional performance metrics such as ROAS, CPC, and conversion rate. Measures like repeat purchases, customer lifetime value, and long‑term profitability often remain secondary in practice.
Customer Data: Available, but under‑utilised
Many organisations have made significant investments in data platforms, data warehouses, and loyalty programmes over recent years — a clear sign of growing maturity. Still, customer data is often used tactically, primarily to support campaigns, discounts, and outbound communication. The largest untapped potential lies in using data to orchestrate the customer journey in real time: deciding which messages are shown, which products are prioritised, and which actions the business takes while the customer is interacting with the solution. This is not a technology challenge alone. It requires clear ownership, prioritisation, and strong organisational anchoring.
AI in practice: Widespread use, limited business impact
Erik Egeriis, Head of SEO at Rocket, shared insights into how companies are currently working with AI. The pattern is consistent: most organisations are active, but primarily in low‑threshold use cases. Typical applications include:
- content production
- SEO and search optimisation
- analysis and reporting
- support for everyday work processes
These initiatives deliver efficiency gains and time savings. However, only a small share of organisations can point to direct impact on revenue or profitability. Few have integrated AI deeply enough into core processes to influence business outcomes. Once again, the conclusion is clear: technology is available — execution remains the bottleneck.
AI, search, and visibility: Evolution rather than disruption
The introduction of AI Overviews in Google has sparked strong reactions and bold predictions. However, recent data points to a more nuanced reality. Clicks from organic search are declining slightly, while revenue from organic traffic is increasing. The traffic that does reach websites tends to be of higher quality. For digital commerce players, the shift is noticeable, but far from dramatic. The key takeaway is clear: classic SEO work remains highly relevant. Investments in structure, content quality, and technical foundations continue to pay off — also in AI‑driven search experiences. Here, structured data plays a critical role. For AI‑based systems, structured data is the language that enables understanding. Without clear signals around pricing, availability, product attributes, and quality, businesses become harder to interpret — and therefore harder to recommend. In this sense, structured data functions as invisible price tags in a digital store.
What Digital Commerce 2026 shows — in brief
- Most companies prioritise the same things. Customer journeys, personalisation, data‑driven work, automation, and AI are widely adopted at a strategic level. The differences lie in execution.
- The gap between strategy and practice remains significant. Many organisations have the right ambitions, but lack capacity, ownership, or governance models to make them operational.
- Growth is increasingly driven by existing customers. Focus is shifting from pure volume growth to creating more value within the current customer base.
- AI is widely used, but rarely core. Most organisations focus on efficiency gains, while few have integrated AI deeply enough to affect profitability or core processes.
- Data and structure are decisive. The strongest performers use customer data actively across the entire customer journey and in real business decisions.
Digital Commerce 2026: The state of Norwegian e‑commerce
Do you want a deeper understanding of where Norwegian e‑commerce stands today — and what separates those who achieve measurable results from the rest? Digital Commerce 2026 is Norway’s only annual in‑depth study of the digital commerce landscape. The report explores how leading organisations work with strategy, technology choices, innovation, and optimisation, providing a comprehensive view of the industry and its development over time. The report includes:
- insights into what organisations believe works well
- the challenges they experience in practice
- the priorities they are setting going forward
- expert analysis that explains not just what is happening, but why
