Ilenia Vidili
Keynote Speaker, Author, Trainer and HBR AdvisorAI & Knowledge Management in CX
Customer knowledge shouldn’t be an afterthought—it should drive decisions at every level.
In our continued exploration of AI’s transformative potential, we sat down with Ilenia Vidili to examine how knowledge management, empathy, and AI intersect to shape the future of customer experience.
A globally respected customer-centricity advisor, Ilenia brings a clarity of purpose to the conversation: that businesses must shift from product obsession to people obsession—and that knowledge, when shared and acted on, is the foundation of that transformation.
From collapsing silos to enabling predictive empathy, her responses offer strategic direction for organizations ready to move beyond automation and toward emotionally intelligent, insight-driven CX. We’ve included reflections through the SearchUnify lens—highlighting how principles from our work in support and service amplify the points Ilenia makes.
Let’s dive in.
Q & A
You emphasize the importance of customer-centricity in modern businesses. How can organizations leverage knowledge management to enhance customer experiences and create a truly customer-first culture?
Ilenia’s Answer
A company’s collective knowledge is one of its most undervalued assets. When employees can access and share customer insights effortlessly, whether it’s frontline feedback, historical interactions, or best practices, everyone makes smarter, more customer-focused decisions.
The problem? Too many organisations treat knowledge as an archive rather than a living, breathing resource that fuels customer experience. To build a truly customer-first culture, businesses must treat knowledge like currency—breaking silos so insights flow freely, giving frontline staff real-time access to critical information, and using AI to enhance personalisation, not just automate interactions.
Most organisations are drowning in data but starving for insight. Knowing what a customer purchased last year is useful. But knowing why they purchased, what problem they were solving, and how they felt about the experience? That’s the difference between reacting blindly and anticipating needs. The breakthrough comes when businesses treat knowledge management as the central nervous system of customer experience—turning raw information into strategic action.
Leadership must set the tone. Customer knowledge shouldn’t be an afterthought—it should drive decisions at every level. A global bank I advised embedded a simple but powerful rule: No product roadmap meeting could start without reviewing the top five customer pain points uncovered that quarter. This forced R&D, marketing, and operations to confront real customer truths, turning abstract data into accountability and action.
Because knowledge alone doesn’t change culture. Curated friction does. A true customer-first culture is built on understanding, empathy, and the ability to act on the full picture. Customer-centricity it’s a shift in mindset that requires businesses to embed customer knowledge into every decision. In my book, “Journey to Centricity: A Customer-Centric Framework For The Era Of Stakeholder Capitalism”, I explore how organisations can align their entire ecosystem around customer needs.
SearchUnify Lens
We see this every day in customer support: information isn’t enough. Our AI-driven knowledge systems, like Knowbler, don’t just retrieve articles—they contextualize knowledge based on user intent, behavior, and feedback. That’s how support transforms into strategic CX.
Many organizations struggle with knowledge silos, leading to poor customer experiences and inefficiencies. What strategies would you recommend for businesses to break down these silos and ensure seamless knowledge sharing across teams?
Ilenia’s Answer
Knowledge silos aren’t just inefficiencies, they’re threats in a customer-driven organisation. When teams hoard insights, customers pay the price: support reps unaware of a feature launch, marketers missing critical feedback buried in R&D’s Slack, sales teams pitching outdated solutions, etc. Breaking these barriers requires rewiring organisational DNA to prioritise collective intelligence over individual control. Imagine silos as organisational black holes, where data goes in, but value never escapes. To collapse them, I use my 4As framework:
Audit (Expose the Gaps)
Most companies don’t realise how bad their silos are until they map them. A healthcare client I worked with used process mining to track patient feedback. 70% of insights were stuck in middle management. The first step to fixing silos is exposing them.
Architect (Redesign Flow)
Rigid hierarchies kill knowledge flow. A fintech firm I advised collapsed silos by creating cross-functional squads (product + support + compliance), all sharing real-time customer insights via a dashboard. The result was a 40% reduction in duplicated work and faster issue resolution.
Activate (Incentivise Sharing)
If knowledge sharing isn’t measured and rewarded, it won’t happen. A SaaS company I worked with tied KPIs to knowledge liquidity, engineers earned bonuses not just for shipping code, but for documentation that reduced onboarding time. The reality is that if executives don’t push for it, it won’t scale.
Align (Anchor to Customer Outcomes)
Silos persist because teams stuck knowledge within their own functions rather than using it to improve customer outcomes. To fix this, businesses need shared success indicators that track how quickly customer insights move from frontline teams to actionable solutions. When teams are measured by how well they act on shared knowledge, silos break naturally
Silos persist because organisations reward ownership over stewardship. We need to treat knowledge like currency as its value multiplies only when circulated. The goal isn’t just sharing information, it’s building an organisation where every team’s success depends on others’ insights. In my LinkedIn Learning course, “Driving Business Growth Through Customer-Centricity”, I share strategies for dismantling organisational barriers that stand in the way of a customer-centric culture.
SearchUnify Lens
Our unified knowledge architecture connects support, sales, and product teams—so insight from any function is accessible to all. With dashboards and usage analytics, we make the value of shared knowledge visible and measurable.
With AI transforming customer interactions, how can businesses strike the right balance between AI-driven automation and human empathy in customer support and self-service?
Ilenia’s Answer
AI is transforming customer interactions, but still too many businesses prioritise automation as a cost-cutting lever, inadvertently commoditising their customer relationships. The danger isn’t too much AI, but too little intentionality. The real opportunity is designing AI as an empathy accelerator, not a deflector. AI shouldn’t just resolve tickets faster; it should make every human interaction uniquely irreplaceable.
I think AI must handle routine tasks like password resets and order tracking so agents can focus on complex, emotionally charged issues. But this is just table stakes. The real power lies in Predictive Empathy and that is using AI to surface unspoken needs. For example, a luxury retailer I guided analysed browsing patterns to detect “silent stress”: rapid page refreshes. Instead of waiting for the customer to reach out, service agents proactively stepped in: “Noticed you designing a nursery. Can our interior design partner help?” This is anticipatory care.
Beyond efficiency, AI’s highest purpose should be to make brands more human, not less. A healthcare client’s chatbot efficiently handled prescription refills but intentionally failed gracefully for mental health queries, redirecting to live counsellors with an honest message: “This is too important for bots. Let me connect you with Sarah, who’s trained to listen.” That was intentionally designed.
The best AI-driven customer support isn’t about automation for its own sake, like what I am seeing these days, but it’s about enhancing human connection, anticipating needs, and making interactions feel deeply personal.
SearchUnify Lens
Our AI solutions are designed for emotional intelligence. With sentiment analysis and escalation logic, we ensure automation never replaces empathy—it enhances it. AI should handle the routine so humans can handle the meaningful.
AI is evolving rapidly, from chatbots to intelligent knowledge assistants. What do you think the future holds for AI in customer experience and support, and how can companies prepare for it?
Ilenia’s Answer
I think AI in customer experience should shift from transactional automation to relational intelligence. We should be moving beyond chatbots answering FAQs to AI acting as a proactive collaborator, curating hyper-contextualised experiences that feel less like support and more like a trusted advisor. Imagine AI that doesn’t just resolve issues but orchestrates moments of delight. For example, a travel insurer’s assistant that rebooks our flight during a strike and negotiates a hotel upgrade before we’ve even finished reading the cancellation email.
In my opinion, AI will also evolve from assisting agents to becoming an invisible co-pilot. Companies that use AI purely for cost-cutting will fall behind those that use it to elevate human expertise. Instead of agents scrambling through databases, AI will surface real-time insights: “This customer called twice last week about delays. Offer an apology, a refund, and a VIP discount.” This will enhance human judgment, turning support interactions into seamless, proactive solutions all of which will improve the customer experience.
To prepare, companies must move beyond chatbots and redesign customer experience around AI-assisted decision-making. That means investing in predictive AI, real-time sentiment analysis, and AI-powered knowledge management, not just automation.
SearchUnify Lens
That’s exactly how we’re designing our Agentic AI Agents. They’re not bots—they’re embedded copilots, surfacing real-time insights and automating next-best actions to deliver not just answers, but outcomes.
Customers expect hyper-personalized support experiences, yet data privacy concerns continue to grow. How can organizations navigate this challenge while maintaining trust and developing top-notch customer service?
Ilenia’s Answer
Most businesses believe that they have a challenge: personalisation or privacy. There is no challenge. The key is to use data transparently and intelligently to enhance customer experiences without overstepping boundaries. Customers want relevant, effortless interactions, but they also expect control over their data. The companies that get this right don’t just comply with regulations; they turn data ethics into a competitive advantage.
The key is value exchange where customers share data if they see clear benefits. Therefore businesses must ensure personalisation feels like a service, not surveillance. To build trust, they must embrace “privacy by design”, ensuring transparency in every interaction. That means clear, jargon-free explanations of how data is used, easy-to-adjust privacy settings, and giving customers full control over their data.
In my LinkedIn Learning course, “Earn Customer Trust and Cultivate Lasting Relationships”, I explain exactly how businesses can build trust while using customer data responsibly.
Ultimately, trust is earned through consistency. When customers see that their data is used to enhance—not exploit—their experience, personalisation shifts from feeling invasive to being genuinely valuable.
SearchUnify Lens
Transparency is core to how we design AI systems. From consent-based personalization to user-controlled privacy settings, our goal is simple: make personalization feel like a service customers opt into, not something they need to protect themselves from.
Looking Ahead: Building Connection Through Intelligence
This conversation with Ilenia Vidili highlights a critical shift: in today’s experience economy, the edge doesn’t come from knowing more—it comes from connecting more. Knowledge is no longer just documentation—it’s empathy, shared. And AI is no longer just automation—it’s intelligence, applied with intention. At SearchUnify, we see the same principles play out in support: when AI empowers teams with the right knowledge, at the right time, delivered the right way, it turns service into strategy. That’s the future of CX. If you’re designing systems that marry knowledge with empathy, automation with trust—we’d love to keep the conversation going.
