For the past thirty years, digital interfaces have continuously evolved to support changing user behaviors. The personal computer introduced the graphical user interface. The web opened access to information, and mobile reshaped the experience by placing touch at the center of interaction. Today, a new transformation is emerging: the shift toward “AI-First” user interfaces, where artificial intelligence structures the interaction itself.
In response to this evolution, we have launched a user research program to analyze how AI-First approaches can transform the banking experience.
1. Why AI-First interfaces are redefining the banking user experience
AI-First represents a new stage in the evolution of digital interfaces, following the mobile-first paradigm, an approach that prioritised designing experiences for smartphones before adapting them to other channels. This shift made the smartphone the primary banking channel for more than 75% of European customers (Statista, 2025).
The AI-First approach fundamentally transforms the user journey and signals the emergence of an AI-first UX. Instead of navigating through menus, users receive immediate answers, personalised recommendations, and proactive action suggestions. The interface becomes a true intelligent copilot, embodying an AI-powered UX capable of anticipating needs, simplifying everyday tasks, and delivering information at the most relevant moment, whether through a suggestion, an alert, a financial projection, or a simple validation.
For banks, this means redesigning the experience around user intent rather than predefined screens. AI can help prevent overdrafts, optimise savings, or recommend financial trade-offs, transforming banking from a transactional tool into a proactive and engaging financial assistant.
Some European banks, particularly in Spain and the Nordic countries, have already taken this step by deploying advanced automation and intelligent assistance solutions.
2. Methodology: How we studied AI-First interface usage across Europe
To better understand user expectations regarding AI-First interfaces, we conducted a European study across France, Spain, Norway, Germany, and the Netherlands, built around a central question: “How can AI-First improve the use of banking services? Can it become the reference interface of tomorrow?” The primary objective of the study was to assess digital usage patterns, the adoption of banking applications, and the use of generative AI tools, focusing in particular on users’ perceptions and experiences (cultural differences and shared expectations) when interacting with an AI-First banking interface.
This article focuses on the French segment of the study and forms part of a broader research initiative aimed at contributing to discussions around AI-First interfaces.
In France, our sample consisted of 12 participants (9 men and 3 women), aged between 25 and over 68, with a majority between 26 and 50 years old and an average age of approximately 43.
All participants were recruited in advance through a screening questionnaire designed to establish a clear respondent typology. Several criteria were controlled, including level of digital proficiency, familiarity with generative AI tools, and intensity of banking app usage.
Following analysis, these 12 participants were identified as representing an early-adopter segment of the population, sharing several common characteristics: a mobile-first approach to banking, multi-banking behaviours (using two to four banks, both traditional banks and neobanks), and a strong level of proficiency in digital technologies and generative AI tools.
Each participant took part in an individual session lasting approximately 75 minutes, including observation of banking usage, a semi-structured interview about their relationship with banking and AI, and an immersive projection using a video prototype of an AI-First interface (around 4 minutes), followed by a self-confrontation exercise.
The use of a prototype allowed us to concretely demonstrate to the panel what an AI-First customer journey might look like, including automatic anticipations such as spending projections, intelligent alerts, a conversational interface, contextual suggestions, and simplified pathways for routine transactions. It enabled us to test the understanding, acceptability, and desirability of these new interactions with potential end users.
3. AI-First Banking in France: Key Insights from Our User Research
3.1. Highly contrasted user profiles facing AI First interfaces
The qualitative analysis of the interviews revealed five distinct user categories, highlighting the diversity of expectations.
- Pragmatic AI Natives (18-30 years old): Young and hyperconnected, they already use AI tools daily, such as voice assistants or generative AI, and primarily seek fluidity, automation, intelligent categorization of their expenses, and useful budget alerts. Their main concern remains the security and transparency of financial transactions.
- Critically Minded and Digital-Conservative Users (35-50 years old): In contrast, these users are comfortable with digital tools but are frustrated by digital bureaucracy. They look for extremely simple, fast, and frictionless journeys, while remaining wary of overly automated systems and maintaining a strong need for human interaction.
- Multi-Banked and Vigilant Users (45-55 years old): Often dealing with fraud, these users express a heightened need for control, consolidated views of their accounts, and intelligent alerts to manage their finances effectively.
- Tech-Savvy Seniors (60-70 years old): Enthusiastically envisioning advanced wealth management applications of AI, particularly in areas like scenario simulations and financial optimization.
- Structured but Non-AI Experts (50 years old and above): These users primarily expect guidance, educational content, clear summaries, and human support during the initial stages.
These differences, observed even in this small sample, illustrate a central point: AI-First cannot impose a single mode of interaction; it must be customizable, gradual, and adaptable to the preferences of various user profiles.
3.2. How do Users perceive AI-First Interfaces? Study results
The interviews reveal a recurring tone that we would describe as "cautious enthusiasm", a blend of excitement and curiosity about the potential of AI (time-saving and simplification) coupled with fatigue from complex journeys and lingering concerns about security and data privacy.
In summary, participants are willing to adopt AI-First, but they are not willing to relinquish control. They are cautiously optimistic, open to innovation, but demanding when it comes to trust and control.
Additionally, our study confirms current market trends: the smartphone remains at the center of the banking experience, and AI is already widely used for productivity, content creation, and certain financial tasks. There is a strong desire for multimodal interactions combining voice, text, and visual interfaces. However, current banking chatbots are seen as limited and ineffective when situations fall outside standard scenarios.
Conclusion: How should banks prepare for the AI First revolution?
AI-First marks a new stage in the evolution of banking interfaces, following the graphical interface and the mobile-first era. By reorganising the experience around proactive, multimodal, and contextual intelligence, this model paves the way for a banking relationship that is simpler, more relevant, and more personalised.
User research reveals clear and pragmatic expectations. Current chatbots have eroded trust: an AI-First experience will need to demonstrate its value through genuine expertise and real actionability. Moreover, the interface must be designed as a multimodal experience, combining text, voice, and visual support, while enabling fast and simple journeys for everyday banking tasks.
Above all, users expect analysis and guidance, not full automation: budget projections, comparisons, and “what if?” scenarios. AI becomes a copilot, but the user must remain in control. Security remains a fundamental prerequisite. Banks must reassure users without overwhelming them.
Users want to understand why AI recommends a given action; otherwise, automation can feel opaque or intrusive. Algorithmic risk directly affects both trust and financial outcomes. AI-First must therefore be developed within the European regulatory framework (GDPR, AI Act), with human oversight and robust data governance to ensure explainability, security, and compliance.
As a result, for any bank looking to seize this opportunity around new user journeys today, the design recommendations are clear:
- Position AI as a copilot, never as an autopilot.
- Combine multimodal interaction with ultra-simple journeys.
- Make security visible and seamless by explaining any control or blocking mechanism, and by allowing users to configure the scope of AI involvement.
- Emphasise analysis and financial guidance, rather than pure execution.
- Articulate AI and human expertise, with smooth escalation to a human advisor.
For banks, AI-First represents both an opportunity and a responsibility: transforming the customer experience without creating a break in trust. Those who succeed in this transition will be the ones able to combine artificial intelligence with human expertise, operational efficiency with transparency, and automation with education.
AI-First thus establishes a new relational framework, and when well designed, it can become a true copilot for everyday financial life and a major lever of differentiation in the banking landscape.
At Sopra Steria, we are closely following this structuring trend and have mobilised our internal expertise—particularly in consulting, user research, and UX/UI design—to study, imagine, and design how these new AI-First journeys can be embedded within the banking interfaces of European banks.
FAQ
What is an AI First interface?
An AI First interface is designed from the ground up around artificial intelligence. It transforms the banking application into an intelligent companion, capable of immediately displaying the right information, projecting financial scenarios, and delivering useful alerts at the right time.
Is AI First compatible with GDPR?
Yes. AI First is compatible with GDPR, provided that requirements around transparency, explainability, and human oversight are met. European regulations such as GDPR and the AI Act govern the use of AI to ensure data protection and limit algorithmic risks. An AI First strategy must therefore rely on robust data governance to remain compliant.
What is the difference between AI-enabled and AI First?
- An AI-enabled interface uses AI as an additional feature or a punctual assistance tool.
- An AI First interface, by contrast, makes AI the core of the user experience. It becomes proactive, personalized, and anticipatory, and fundamentally reshapes how users interact with their bank.
What are the main risks of AI-First Interfaces in banking?
The main risks identified include:
- An intrusive or opaque perception if recommendations are not clearly explained;
- Algorithmic risk, as a poor suggestion can directly impact the user’s financial situation;
- A potential loss of trust if automation is not properly controlled;
- The need to guarantee security, explainability, and human oversight to prevent errors and misunderstandings.
- These risks justify a strict regulatory framework and a high level of transparency.