03/11/2025
Welcome back to our series on five actual truths about AI in the workplace. So far, we’ve looked at topics like trust and employee skills. This time, we’re getting personal. It’s time to look at how AI personalisation can be a key driver in creating more bespoke user experiences.
Most of the talk about AI personalisation still focuses on customers. Better targeting, smarter product suggestions, dynamic pricing, you name it. But there are so many real opportunities to create meaningful AI personalisation right inside the workplace. Ironically, teams who work every day to design hyperpersonal experiences for customers often don’t get the same level of UX, live support or flexibility at work. Their tools, workflows and even training plans still look one-size-fits-all.
So, what would happen if AI could personalise work itself? Not in a futuristic way, but in the day-to-day sense, starting with how your employees learn, make decisions and collaborate?
Why personalisation is still the future
Across industries, expectations are growing faster than most organisations can keep up. Customers want bespoke services that feel perfectly curated and tailored to their interests and needs. So, why shouldn’t employees deserve the same? Unfortunately, most employees feel stuck working with legacy systems, data and processes that are built around uniformity.
AI can help close that gap, but it only works when it’s grounded in real context. If your data is still siloed or your processes can’t adapt, no algorithm can create meaningful personalisation. Gartner’s 2025 CIO Agenda points out that while most organisations are experimenting with AI, only a minority manage to turn those pilots into consistent results. Almost always, the challenge lies in how to make AI relevant to the way your people actually work and seek information. That means different things in different industries, as the use cases below show.
Banking: Making knowledge personal
Banks know the importance of trust and personal connection, yet many still deliver standardised digital experiences to their employees. AI can change that, but only if it helps people do their jobs better and faster.
Imagine a relationship manager who can instantly see which clients need advice because their spending habits or life events have changed. Or a compliance analyst who gets tailored insights on risk exposure without having to sit and read hundreds of pages of reports. That’s what AI can enable when it’s trained on quality data and paired with human judgment.
Right now, 92% of banks are investing in AI for risk and compliance, but only about a third say it’s meeting their leadership’s expectations (Gartner, CIO Agenda 2025). Is that a sign that they’ve chosen the wrong tools? It’s far more likely that employees aren’t clearly seeing the added value. To make AI investments worthwhile, it starts with choosing relevant use cases but also takes abundant communication and change management to get people on board.
Insurance: Personalisation through better understanding
Insurers have been working to personalise customer journeys for years, but not always successfully. Many policies still look more-less the same, and customer contact tends to follow fixed scripts. AI could finally change that by giving employees a 360-degree view of each customer’s situation.
Large language models can learn from real customer behaviour and claim patterns. This delivers insights that can help insurers tailor cover or advice to a customer’s actual needs. The same applies internally. A claims handler might get context that fits how they approach assessments, or an underwriter might see patterns linked to their portfolio instead of a standard dashboard.
But personalisation only works when everyone involved understands how those suggestions come about. A “personalised” recommendation that feels generic erodes trust. It all comes down to transparency. If your people can see how an AI tool works, they’re far more likely to use and trust it.
Manufacturing: from production lines to personalised learning
Manufacturers understand the value of personalised products. But personalised employee experiences have so far been under-prioritised in the industry. Engineers and line workers still train through static modules or manuals that don’t reflect their actual equipment or experience levels.
AI personalisation can change that. Digital twins and predictive systems are already reshaping maintenance, but the same technology can also tailor learning and shift planning. If a technician tends to make certain adjustments faster or spots faults more accurately, the system can adapt training accordingly. That builds confidence and speeds up progress without adding more pressure.
Companies like Siemens and Beko are already using AI in production to save energy and reduce downtime. The next step is to bring that intelligence to people’s daily routines. A good place to start would be using AI insights to personalise learning and development. It keeps skills fresh and creates positive, meaningful user journeys.
Retail: Personalisation behind the scenes
Retailers have led the way in coming up with innovative AI use cases, but those have largely focused on customers, not employees. It’s become standard practice to automatically retarget customers with personalised offers. But retail employees are often stuck working with rigid, standard procedures and inflexible tools.
Everyone benefits when the tools are transparent and well-understood. Yet even in retail, Gartner notes that nearly 70% of firms suspect “shadow AI” use, a sign that employees want smarter support but don’t always get it. That’s why it’s important to give store and support staff simple, visible ways to use AI in their daily decisions. If your customers are benefiting from personalised recommendations, your employees can too.
What real personalisation looks like
Truly personalised user experiences all have one thing in common: relevance. AI should give people the context they need, when they need it, and then get out of the way. In practice, that can mean fewer repetitive tasks and more space for human judgment. It also means smarter onboarding that adapts to each person’s background. Or genAI assistants and support tools that are always there when employees need them.
Personalisation is moving past customer experience and quickly becoming a workplace expectation too. With the right approach and mindset, it can make work feel more personal, more supported and more connected to purpose.
Get in touch with our dedicated team of experts, and start a conversation around your AI needs.
