What If Every Customer Could Get Personal Attention at the Same Time?
By Norrie Daroga, CEO, CodeBaby
For as long as businesses have served customers, a fundamental tradeoff has existed between personalization and scale. The more individualized attention we want to provide, the more people we need to provide it. As demand increases, organizations add staff, extend wait times, introduce queues, or move customers toward self-service options that are more efficient but often less personal.
Conversational AI has the potential to change that equation.
One of the capabilities I find most exciting about conversational AI is something that doesn’t receive nearly as much attention as it should: the ability to support virtually unlimited simultaneous, personalized conversations. Ten people can ask ten different questions at the same time. So can a hundred. So can thousands. Each conversation can be specific to what that individual needs, without waiting for the conversation ahead of them to end.
When deployed ethically and with the proper rigor, that represents a fundamentally different way to think about scaling human capacity.
Personalization and Scale No Longer Have to Be Opposites
Historically, organizations have addressed the limits of human capacity by standardizing interactions. We created FAQs, phone trees, knowledge bases, websites, signs, apps, and automated workflows. All of these can be useful, but they often require customers to adapt their needs to the structure we’ve created.
Conversational AI offers another option. Instead of giving everyone the same information, we can let each person ask the question that matters to them. One customer may need a simple answer. Another may have several follow-up questions. Someone else may be comparing multiple options before making a decision. Each interaction can follow its own path while thousands of other conversations happen at the same time. So, scale no longer has to mean generic.
A Personal Concierge That Goes with You
Consider something as simple as finding your way through a large physical environment. Airports, shopping centers, hospitals, resorts, college campuses, and large retail stores can be difficult to navigate, particularly for someone unfamiliar with the space.
Traditional wayfinding relies on signs, directories, maps, information desks, or apps. But that’s not necessarily how people think. We don’t think, “I need to search a map.” We think, “I have 45 minutes before boarding. Is there somewhere nearby where I can sit down and have lunch?” Or “I just landed. What’s the easiest way to get to baggage claim?” Those are questions better suited to a conversation.
CodeBaby is currently piloting this type of experience with a major international airport. Travelers can engage with a conversational avatar to ask questions and get directions to restaurants and other destinations throughout the airport.
The experience becomes even more powerful when it moves from a shared kiosk to the traveler’s own device. By scanning a QR code, travelers can continue the interaction on their phones, effectively taking a personal digital concierge with them as they move through the airport.
Now consider what that means for scale. Hundreds or potentially thousands of travelers can receive assistance simultaneously. One may be looking for sushi, another for a lounge, and another for the fastest route to a connecting gate. Each gets an answer specific to what they need.
The same model can extend well beyond airports. A customer could scan a QR code in a large retail store and ask where to find a product. A hospital visitor could get help locating a department. A resort guest could ask about restaurants, activities, or amenities while moving across the property. So, the interaction scales, but the experience remains personal.
One Avatar, 8,000 Homes, Thousands of Different Questions
We’re seeing the same principle play out in a very different environment with real estate. Consider an MLS website with more than 8,000 homes. Traditionally, a prospective buyer searches listings, applies filters, opens property pages, compares homes, and eventually fills out a form or contacts an agent. The information is there, but much of the work still falls on the buyer.
Imagine starting with a conversation instead. “I’m looking for a four-bedroom home with a pool and a large backyard. What should I look at?” Or “I like this house. What else is available nearby for under $750,000?” or “Before I schedule a showing, what can you tell me about this property?”
A single CodeBaby avatar can simultaneously have conversations with website visitors asking questions about more than 8,000 different properties. Each buyer can ask follow-up questions, refine what they’re looking for, and identify the homes they are genuinely interested in seeing.
The result is greater efficiency on both sides. Buyers get personalized assistance navigating an enormous amount of information. Real estate professionals get a transcript of conversations, so they gain insights into the most common questions about a property, spend less time answering early-stage questions, and focus more on qualified prospects ready to take the next step.
When the conversation reaches the point where human expertise matters most, the prospective buyer can be connected with the right real estate agent. The technology isn’t replacing the agent. It’s helping the customer and the agent get to the point where the human relationship creates the most value.
The Goal Isn’t Fewer Humans. It’s More Human Capacity.
Whenever we talk about AI and efficiency, the conversation can quickly turn to reducing headcount. I think that’s far too narrow a way to look at the opportunity.
Every organization handles interactions that are important to customers but don’t necessarily require human expertise. Answering common questions, locating services, explaining policies, identifying products, or helping someone narrow a large set of choices can consume enormous employee time when multiplied across thousands of interactions.
When conversational AI handles more of those routine conversations, people have more capacity for the interactions where they add the greatest value. At an airport, an employee who isn’t repeatedly giving directions can spend more time helping a traveler whose flight has been canceled or a family navigating a complicated connection. In real estate, an agent can spend less time answering basic listing questions and more time understanding a buyer’s priorities, evaluating properties, negotiating an offer, and guiding a client through one of the largest financial decisions they may ever make.
As organizations decide how they want to use AI, I believe we need to think critically about what we’re trying to achieve. The temptation will be to look primarily at automation and cost savings. But that is a narrow and short-term view.
A much more interesting question is: What could our people accomplish if technology handled more of the routine interactions competing for their time? That reframes the opportunity through a more strategic and growth-oriented lens. AI can handle scale. People can focus on the expertise, judgment, empathy, creativity, and relationships that create greater value.
The real promise of conversational AI isn’t simply that a machine can have a conversation. It’s that organizations can make personalized assistance available at a scale that was previously impossible while allowing their people to focus their talent where it matters most.
At CodeBaby, that’s the future we’re interested in building: technology that scales personalized interaction without losing sight of the value of people. Because the best measure of AI efficiency shouldn’t be how many humans we can remove from an experience. It should be how much more human capacity we can create.
