From search to sense: a chief strategy officer’s thoughts on AI and employee experience
The apple after the fast
I’m Frank Wolf, cofounder of Staffbase. I spend most of my time thinking about how people make sense of information, especially at work. But recently, I had a moment of unexpected clarity far outside the world of internal communication.
I had just finished my first seven-day fast. No food for a week. And the first thing I ate afterward was an apple. It’s what some call the “apple escape from paradise” — a symbolic reentry into the world of eating.
I have never looked forward to an apple as much as this one.
But what struck me most wasn’t the hunger or the ritual. It was the way I had made it through the week.
Every day of my fast, I had long, surprisingly engaging conversations with ChatGPT. I asked it about fasting, nutrition, liver function, sugar, blood pressure — what to do, what not to do, one question at a time.
And that changed everything.
Because my search for information became a real dialogue, I ended up asking far more questions than I ever would have typed into Google. As a result, I learned more. I stayed more curious. And I stayed more connected.
That experience reminded me of something I’ve seen happening all around us: the shift from searching to sensemaking. From content to experience. From information delivery to something more personal, and more powerful.
AI is fundamentally changing how we interact with technology.
And that means it’s changing how people experience communication and information at work, and everywhere else.
We’re not in the search era anymore
For the past 25 years, we’ve been optimizing everything for search.
Information architecture. Click paths. Navigation menus. Pages and portals and panes. The modern workplace became a network of systems, each one built on the idea that people will go find what they need, assuming it’s organized well enough.
That era is ending.
Artificial intelligence has created a new expectation: not to search, but to be answered. Not to browse, but to ask. Not to find your way through an interface, but to have a conversation that delivers what you need, instantly, personally, and in context.
The interface is no longer the product.
The conversation is.
We already see it in our personal lives. We don’t visit websites to learn how to fix something. We ask ChatGPT. We don’t type long search strings. We speak to our phones. Increasingly, we expect technology to meet us in the moment, not the menu.
That same shift is coming to internal communication.
And it’s going to change everything.
Because this isn’t just about faster access. It’s about a different relationship between people and information. One where trust is built in, not earned through repetition. One where answers find the employee, not the other way around. One where intelligent systems make sense of complexity, so employees can make better decisions, faster.
The age of search was about structure.
The age of AI is about sense.
The elephant in the room: traditional interfaces are dying
Let’s talk about the real shift happening here.
Everyone’s busy talking about AI. But the elephant in the room, the quiet truth nobody wants to admit, is this:
Traditional interfaces are dying.
Not because they’re broken, but because they’re no longer enough on their own.
If you still rely on people navigating through tabs, clicking through categories, or searching a knowledge base to find what they need, you’re already behind. That’s a legacy mindset from the search era — one where users were expected to adapt to the system, not the other way around.
But here’s the nuance: structure still matters. More than ever, in fact.
AI isn’t eliminating the need for navigation, it’s becoming a new kind of user of your intranet. And like any user, it needs clarity.
If your system contains ten articles about the same event, AI won’t know which one to trust. It might try to merge conflicting content, producing answers that confuse more than clarify. That’s why organizations will need to shift from publishing for volume to publishing for structure. Think less “news stream,” more “pillar page.”
One well-maintained source of truth — with clear sections, metadata, and links — will outperform a sea of fragmented updates. And that’s the intranet model we’ve been championing all along: not an archive, but a front door. A small number of curated, actively maintained pages that people — and now AIs — can rely on.
The tools we use outside of work already understand this.
They don’t teach us how to search; they deliver the result. They don’t rely on us to navigate; they use structure and context behind the scenes to make answers feel instant and intuitive.
This is the quiet revolution happening in the employee experience. Not a redesign. Not a faster search bar. But a complete shift in expectations.
For me, the real moment of truth comes when someone — an employee, a manager, anyone — asks a question in the middle of their day and instantly gets a response that’s accurate, contextual, and trustworthy.
That’s what AI unlocks.
It’s not just about access to information.
It’s about making the right information matter, in the right moment.
At Staffbase, we’ve been thinking a lot about what makes AI implementations actually work; not just in theory, but in real-world organizations.
One study from MIT mapped it clearly: AI projects succeed when they’re narrow in scope and focused on concrete problems.
That insight has shaped our entire approach. We’re not building general-purpose AI assistants. We’re building focused tools for focused needs, places where trust, timing, and relevance matter most.
Because trust isn’t built by the algorithm.
It’s built by the experience.
The framework: trusted context, control, and reach
That’s why our approach at Staffbase is intentionally focused. We’re not chasing complexity for its own sake, we’re designing AI that solves real problems in the real world of employee experience.
But making AI work isn’t just about functionality. It’s about creating the right conditions for trust.
That means rethinking how information is delivered, how it’s targeted, and how it’s experienced. We’ve defined that approach around three essential pillars: trusted context, control, and reach.
Trusted context
Trust isn’t built with content alone. It’s built through context — when the right information reaches the right person, in the right place, with the right framing. A push notification from your manager feels different than a global update from HQ. AI needs to understand that difference.
But understanding isn’t possible without the right foundation.
AI is only as good as the data it draws from. Quality in, quality out. That’s why trusted context starts with accurate, well-structured, relevant information. At Staffbase, we’ve long helped organizations cut through the noise, establishing a single source of truth and giving admins the tools to deliver what matters to the people who need it.
Employee AI takes that even further. It monitors content continuously, flags issues, recommends improvements, and helps ensure that everything an employee sees is not only correct, but aligned with the organization’s standards and voice. That’s what we mean by agentic governance: AI that doesn’t just generate, but safeguards.
At the same time, Employee AI doesn’t treat everyone the same. It understands roles, locations, preferences, and history, connecting every employee touchpoint through shared memory and organizational context. The result is personalization at scale, not based on guesswork, but grounded in data that’s specific, secure, and trusted.
Because it’s not just what’s said.
It’s who says it, where it appears, and how clearly it fits into the bigger picture.
Control
AI is only valuable when it works in alignment with the organization it serves. Control is what ensures that companies — not algorithms — set the direction.
With Employee AI, HR leaders and communicators can define how the AI behaves, what it knows, and the boundaries it respects. That means setting brand tone and voice. It means embedding company-specific narratives, cultural nuance, and trust principles around accuracy, ethics, and compliance.
These aren’t technical details. They’re strategic decisions. They shape the employee experience as much as the content itself.
Control ensures that AI doesn’t just speak. It speaks responsibly — on message, on brand, and in service of shared goals.
Admins have the tools to fine-tune outputs for relevance, define approved knowledge sources, and set clear guardrails. The result is an AI that helps employees make sense of their world, without ever drifting from the values that define it.
Reach
You can’t build alignment if you can’t reach everyone.
Real impact means reaching employees across roles, locations, devices, and moments, whether they’re behind a desk, on the factory floor, commuting between shifts, or checking their phone between tasks. AI should extend the reach of HR and comms, not narrow it.
That’s why Employee AI isn’t just a smarter tool. It’s built on smarter infrastructure.
Staffbase has long been trusted to connect with hard-to-reach employees, through intranets, mobile apps, email, digital signage, SMS, Microsoft 365, ServiceNow, and more. These channels are already adopted, loved, and used daily. Employee AI builds on that foundation, embedding intelligence directly where communication already happens.
An AI assistant — available across web, mobile, and even voice — gives employees a single, conversational entry point to find what they need. Personalized podcasts deliver weekly updates, tailored to each employee and delivered in formats that work in the flow of real life.
Because to truly be heard, communication needs more than intelligence.
It needs presence.
What’s at stake: the risk of missing the shift
The biggest question for most organizations right now is simple:
How do we actually get started with AI?
A recent study from MIT looked at more than 300 AI projects to find the answer. And the takeaway was clear: broad, generic rollouts don’t work. You can’t just “give AI to everyone” and expect results. That approach — the same one that failed in the data lake era — often leads to confusion, inconsistency, and low impact.
What works is the opposite: narrow scope, specific use cases, clear problems to solve. The more targeted the effort, the greater the success rate.
That’s exactly how we’ve shaped our Employee AI approach.
We focus on the most essential questions employees have — the moments when they need clarity about their job, their workplace, or their company. And we bring together everything needed to answer them well: trusted data, shared context, governance, and the ability for HR and comms to shape tone, timing, and strategy.
The result isn’t generic AI.
It’s a ready-to-go, company-aligned, high-impact service that transforms how people experience work.
Because that’s what’s really at stake.
This isn’t about rolling out “more AI” than the next company.
It’s about using the right AI to solve real problems — and delivering value fast.
The organizations that win will be the ones that unlock real potential by starting small, staying focused, and making sure the entire workforce benefits, not just the ones behind a desk.
Leaders who cling to the old model — interfaces, search bars, static intranets — are building on a foundation that no longer fits the way people live, work, or think. Those systems may still function, but they won’t satisfy. They won’t feel intuitive. And they won’t help people get things done.
Employees won’t wait.
They’ll default to external tools. Or they’ll tune out entirely.
And the cost isn’t just inefficiency.
It’s lost alignment. Rising security risks. A slow erosion of clarity, confidence, and connection, right when organizations need it most.
If communication is how we shape culture, then Employee AI isn’t just a productivity tool.
It’s a strategic lever.
One that can deepen trust, speed up decision-making, and help people focus on what matters.
But only if leaders are willing to rethink how communication works and what it’s really for.
Closing reflection: back to the apple
That apple at the end of my fast wasn’t special. It was just an apple. But it reminded me what happens when your attention shifts — when the noise falls away and clarity returns. AI didn’t make it taste better. But it changed how I noticed it.
The same is true for employee experience.
The tools we use may be artificial. But the experience they create can be deeply human. When we use them with intention — when we apply them in the right context, with the right purpose — they help people focus, understand, and connect.
That’s the power of meaning.
Because with the right context, communication becomes meaning — and meaning becomes action.
This is the opportunity in front of us: not just to use a new generation of tools, but to take on a new kind of responsibility. To shape experiences that are felt, not just delivered. To help people see clearly. To guide them toward what matters.
That’s what the apple taught me.
That’s what AI is making possible.
And that’s the path forward.
