At Fruto, we’ve spent years helping organisations bridge the gap between what technology can do and what customers really need. Now, as AI changes markets and business models, that gap is more obvious and riskier than ever.
The problem is focusing on AI first instead of putting customers first.
We’ve seen a consistent pattern across product organisations:
Roadmaps driven by technical opportunity but not shaped by customer feedback or a clear understanding of user needs, leading to missed market opportunities, wasted investment, and slow growth.
Complex feature sets with unclear value and wasted effort, resulting in higher costs, product bloat, and confusing user experiences.
Slow adoption and weak retention with limited insight into the reasons why, undermining ROI, damaging brand perception, and risking customer churn.
Teams are busy building, but not always building the right thing, missing the product-market fit, burning resources, and delaying sustainable business impact.
Unfortunately, AI is amplifying these.
Since the technology is powerful and easy to access, many organisations begin by asking “What AI features can we add?” but the question that really matters is: “Where could AI meaningfully improve outcomes for our customers and for our business?” or even "Do we need to add AI into our product?".
If we don’t clearly understand users' behaviour, motivations, and decision-making, AI can add complexity rather than give us an edge.
Why user experience is even more important in an AI-driven world
AI changes how people interact with your application, platform or website, how users find your brand, make purchasing decisions, understand information, and trust systems and brand.
It introduces new challenges:
Transparency and explainability: Users must be able to understand how AI-driven decisions or recommendations are made, not just see the output, for example, the source of the information.
Trust and perceived control: AI can erode trust if users feel decisions are opaque or uncontrollable. Users need to feel confident in their ability to intervene or override the AI when necessary.
Accuracy vs. confidence: Highly confident AI outputs that are actually inaccurate can mislead users. Clear communication about uncertainty and limitations is essential, especially in high-stakes industries such as health and finance.
Cognitive load: New AI-powered experiences may add complexity, requiring users to learn new patterns or navigate unfamiliar interfaces, potentially leading to confusion or overwhelm.
Ethical responsibility: AI can amplify biases, threaten privacy, and pose ethical dilemmas. Organisations must ensure their AI aligns with both internal values and external regulations or societal expectations.
Consistency and predictability: AI systems can behave unpredictably, making user experiences less reliable.
User empowerment: There’s a risk that AI automates too much, removing meaningful choices or expertise from the user, which can introduce risks, reduce engagement and user satisfaction.
For example, in fields like healthcare, education, energy, nonprofits, and government, addressing these challenges is critical because the impact of AI on people’s lives, trust, and well-being is especially significant. We’re already helping clients add AI features to established platforms, especially in healthcare and medical imaging. Our experience keeps confirming one belief: Technology should serve human needs, not the other way around. Adding AI without a clear strategy just leads to confusion. But when it’s based on solid research and a clear product vision, AI can be transformative.
Markets are shifting, and user expectations are changing
We’re going through rapid technological change. Markets are shifting, user expectations are evolving, and business models are being reconsidered. The organisations that succeed will be those that align clear business objectives with deep customer insights, the intelligent use of technology, and strong product leadership.
Many businesses are moving past just experimentation. The focus is shifting from “trying AI” to discovering where it truly creates value and solves real customer problems. Investors are also shifting their mindset: instead of asking, “Does your product have AI?” (as a tickbox exercise), they are now asking, “How is it solving a customer need?”
This is where having a clear strategy really counts.
Recent AI & UX project examples
Embedding an AI featured driven by user research
We recently worked with a leading membership and professional body in the tax and finance sector, an organisation with a specialist online search product, to help them embed an AI-powered feature. We grounded our design and product decisions in user research, focusing on real customer behaviours and expectations to ensure the new AI feature would genuinely support users rather than simply adding technical novelty. Our design solution was then tested with users to refine it and ensure that the output enhances their experience.
User research to get insights into user behaviour shifts due to AI
In another project, we partnered with a major health information provider to conduct user research into how their target users turn to Google AI Overviews and ChatGPT to access health information. Our research examined how these AI tools affect user journeys, how much users trust the information they receive from AI, users' perceptions, whether people still visit the client’s website, the accuracy of the information, and the risks these technologies pose to user traction and web traffic. The insights are now guiding the client’s future AI strategy and initiatives.
What are the first concrete steps to align AI initiatives with customer needs?
1. Start with the problem, not the technology
The most successful AI features aren’t built by asking “Where can we add AI?” but by identifying where you’re losing time, money, or customer trust. Focus on the core problems you’re solving and the outcomes you want to achieve.
2. Conduct user/customer research first
Before you even consider technology choices, invest in understanding your users’ real needs, behaviours, pain points, and expectations. Use interviews, surveys, observation, and analysis of existing data to reveal genuine problems worth solving.
3. Map pain points into AI opportunities
Once you understand the user journey, look for moments of friction or unmet needs. Create an AI Opportunity journey map, an approach that combines user experience with backstage processes to reveal where AI can add the most value for both customers and your organisation. Prioritise these opportunities using an impact vs. effort matrix and frame each one with clear hypotheses: define the problem, the target audience, AI’s role, and how you’ll measure success.
4. Prototype the experience, not just the model
Don’t jump straight into building. Instead, simulate AI outputs manually, create design mockups, or role-play AI interactions with users. Early, lean validation (measuring usability, trust, and value) helps de-risk your investment and ensures you’re solving the right problem.
5. Continuous research and measurement of the impact of AI features
Conduct regular user research to measure adoption, effectiveness, trust, and performance. This accountability ensures your AI initiatives remain relevant and continuously improve with real-world feedback.
For a practical guide on how to map AI opportunities in your product, check out our blog post: Embedding AI that delivers real user value and business ROI
Connecting organisational goals with real customer needs
Fruto partners with leadership and product teams to turn user and customer insight into action.
We specialise in:
Customer-centred transformation – helping businesses embed customer thinking at the core of their operations in order to achieve measurable increases in user satisfaction and engagement.
UX and product strategy – enabling organisations to align team focus, resulting in clearer roadmaps and a faster path to market.
Service design – streamlining processes for outcomes like shorter onboarding times and improved service quality.
Ongoing product discovery – uncovering new user needs and opportunities, which drive incremental improvements and product-market fit.
UX and UI design for complex systems – reducing errors and support requests through intuitive, effective digital experiences.s
We work across healthcare, education, nonprofits, government, energy & netzero, cybersecurity, emerging tech and many other sectors.
Our role is to help organisations rethink how they define and deliver value because in a world where AI is available to everyone, lasting advantage comes from understanding behaviour, clarifying strategic intent, designing experiences that go beyond usability and creating products that are differentiated, not just functional.
Ready to rethink your product?
Take the first step: book a free 30-minute discovery call with our team. We can explore your challenges and identify where AI or customer insight could unlock new value for your business. Reach out to schedule your session today, no commitment required.
If you’re a product leader or business owner considering:
Introducing AI into an existing platform
Improving the user experience of a complex product
Aligning your roadmap more closely with customer needs
Reducing product investment risk
Strengthening adoption and retention
Then the starting point isn’t the model. It’s the human.
Fruto is ready to help organisations navigate this shift with strategy, confidence, and clarity. The next phase of digital products won’t be about who uses AI. It will be about who uses it meaningfully and strategically.
