Tune-In Tuesday – #13 Focus On: AI in digital experiences — what’s actually useful?

AI in digital experiences — what’s actually useful?

Almost every digital conversation now includes AI in some form. Whether it’s AI assistants, personalisation engines, automated workflows or AI-generated content, the technology is appearing across almost every platform, product and experience being discussed right now.

The challenge is that adding AI and creating something genuinely useful are two very different things.

We’re increasingly seeing a gap emerge between AI that meaningfully improves an experience and AI that simply exists because businesses feel they should include it. A lot of digital experiences now feature surface-level AI integrations that sound impressive in presentations but offer very little long-term value for real users.

Things like:

• Generic AI summaries
• Disconnected assistants
• Novelty interactions
• Unnecessary automation
• Chatbots with limited usefulness

Often, the issue isn’t the AI itself. It’s that the surrounding experience hasn’t been designed clearly enough in the first place.

The most effective AI often feels invisible

Interestingly, some of the strongest AI-enabled experiences are the least obvious from the user perspective. The technology fades into the background because the real value comes from helping users do something faster, more clearly or with less friction.

That’s where AI starts becoming genuinely powerful.

The most useful applications we’re seeing tend to focus on:

• Simplifying complexity
• Reducing friction
• Personalising experiences
• Accelerating decision-making

For example, AI can become incredibly valuable when it helps users surface relevant information quickly, navigate large content libraries, personalise learning journeys or simplify technical information that would otherwise feel overwhelming.

In these situations, AI enhances usability rather than competing for attention.

AI only works when the experience works first

One of the more important shifts happening now is that audiences are becoming much more selective around AI experiences. Early curiosity around generative AI created a huge amount of attention, but users now expect practical value very quickly.

If the interaction feels slow, generic or unnecessary, engagement tends to drop almost immediately.

That means AI experiences increasingly need to feel:

• Useful
• Contextual
• Fast
• Accurate
• Intuitive
• Low friction

rather than simply “innovative”.

We’re also seeing businesses recognise that poor user journeys don’t suddenly improve because AI gets layered on top. In many cases, unclear experiences simply become more confusing when AI is introduced without a clear purpose behind it.

The underlying experience still matters most.

Where AI is becoming genuinely valuable

Some of the most interesting applications we’re seeing now are in environments where users are already dealing with large amounts of complexity or information.

For example:

• Healthcare communication
• Learning platforms
• Interactive events
• Internal knowledge systems
• Proposal tools
• Customer engagement platforms
• Data-heavy environments

One particularly interesting shift is the rise of adaptive experiences — systems that adjust pathways, recommendations or content dynamically based on user behaviour, role or intent. That’s where AI starts moving beyond novelty and into something operationally valuable.

At Lucden, many of our AI conversations now begin by identifying friction points before discussing tools or models. The strongest AI experiences are usually the ones that remove complexity rather than adding another layer of it.

Because ultimately, the best AI experiences don’t just appear intelligent.

They make the entire experience genuinely better.