The One-to-One Future Is Here (Almost): An Interview with Jim Sterne, President, Target Marketing

Jim Sterne is a true pioneer in data-driven marketing, a prolific author and popular speaker, and the co-author of “The New Science of Customer Relationships”.

This interview has been edited for length and clarity.

From this year onward, AI gets real for marketers everywhere.

When it was first released in late 2022, OpenAI’s AI tool was a novelty – a plaything even – almost magical. People were captivated. It’s value as a utility was immediately apparent. But so was the concern for it becoming a Pandora’s Box.

Caught up in the hype, companies began urging staff to incorporate AI into their work. Which they did, dutifully, sometimes reluctantly, not sure exactly how to assimilate it into their work routine. Proof of concepts soon sprang up. Pilot programs followed. Most companies tried to fit AI into existing workflows when the trick was to rethink how work gets done.

This past year businesses began scrambling in earnest to integrate AI more fully into their operations, seeking efficiencies, cost reduction, time compression, driven by the fear of falling behind. Today the boldest enterprises are charging full speed ahead, embedding AI into revamped workflows and processes while upgrading their technology infrastructure. In fact, this year is predicted to be the AI turning point(1).

Marketers have been swept along in this rush to implement AI. The use cases are simply too obvious – better targeting, instant analysis, hands-off execution. Every marketing automation platform now claims to be AI first. AI adoption is at the top of every CMO’s list of priorities. But now, as marketers brace for what’s to come, there is this nagging dread. Are they digging their own grave? The immediate causalities will be entry level jobs for sure – but who’s next? How far up the line will the AI axe fall? What jobs will be left for marketers to do? The spectre of a hollowing out of the profession looms large.

AI will certainly relieve marketers of the drudgery. It will result in more effective targeting and personalization at scale, making one-to-one marketing possible (at last!). It will help tame complexity. It will speed up content creation and testing. It will allow marketers to easily spot emerging trends that might otherwise go unnoticed. It will compress and accelerate campaign workflows. It will generate forecasts based on an infinite set of market scenarios. It will simulate the voice of the customer. Theoretically, it should improve decision making – reduce latency –– serve as a sounding board – even spark innovative ideas. In short, it will allow marketers to move at machine speed.

Harder to predict, however, is the impact all of these efficiency gains will have on managing customer relationships. Everyone acknowledges the market will be upended, especially as personal shopping assistants become an integral part of everyday life. Customers will be more empowered. Harder to reach. Tougher to convert. AI agents will be ubiquitous, plugged into every consumer device, every tool, every app. But in a world where brand choice is mediated by agents sniffing out the best deal – trained to ignore brand braggadocio – how will marketing drive demand? Build brands? Win greater loyalty? How should marketing adapt to this new age of autonomous agents?

The obvious answer is for marketing to reinvent itself – to reimagine its corporate role and purpose – to stop functioning as a conveyor belt for brand messaging and take full ownership of the customer relationship. Because what businesses still struggle with, still get wrong most of the time, is figuring out what customers actually want and need. That takes empathy, imagination, creativity – the very attributes AI lacks (for the time being). So now is probably a good time for marketers to do a full reset and try harder to lead corporate strategy, not simply be answerable to it. Marketers should be dedicated to improving the lives of customers. Value creation and strategic differentiation should be the new mission, not just demand creation. AI can serve up the insight – marketers can provide the inspiration.

In fact, thinks Jim Sterne, marketing should take point on making customers happy. He further believes that the one-to-one future may finally have arrived thirty years after it was first envisioned(2), thanks to the alchemy of AI.

Jim has spent his career as an agent of change, helping marketers navigate successive waves of innovation. He wrote one of the first books ever on web marketing in 1995, just a couple of years after the “worldwide web” was unveiled to the public at large. Since then he’s authored a dozen other books on every aspect of web-based marketing, customer service and advertising. He also founded the Marketing Analytics Summit and the Digital Analytics Association.

In his latest book, “The New Science of Customer Relationships”, co-authored with the renowned data analytics expert Thomas Davenport(3), Sterne explains how AI will finally deliver on the promise of one-to-one marketing. The companies that succeed, he believes, will be the ones that use AI to advance the interests of customers.

Stephen Shaw (SS):: You earned a BA in Shakespeare from the University of California. What drew you to the Bard?

Jim Sterne (JS):: I went to a local play where somebody said, oh, you’re going to UC Santa Barbara, you have to take a class in Shakespeare from this guy named Homer Swander(4). He was a world class Shakespeare academic. So, first day, first class, sat down next to the girl of my dreams and we’ve been married ever since. And that’s why I did Shakespeare.

SS: Do you still have an affinity for Shakespeare?

JS: Absolutely, yeah. It was Homer Swander who said two things that just made it work for me. One was, you cannot read Shakespeare. It is a script, it is to be performed. You can only understand it if you stand up and speak the words out loud to each other. The second thing he said was that Shakespeare is the study of humans. And I just thought, well, yeah, I want to understand people. And secondly, approach it as a foreign language. Now I can go see a Shakespeare play and understand it because I can speak Elizabethan.

SS: You got your first job selling Apple computers at retail. And then you went on to sell computers to businesses a year later. What did you enjoy most about that line of work? After all, you were an English lit major.

JS: Well, I answered an ad that said no experience necessary so I qualified. An ex UCSB professor had opened a retail store. So I walked in and said I really don’t know much about computers. Now I had worked on a Data General with a command line interface. But this was an Apple. This was a different animal. We didn’t have WYSIWYG yet. There was a mouse, you could draw pictures. And it was extraordinarily exciting. But people didn’t get it. Why would I want a computer in my house? Oh, can’t you see?

So I was excited about it, and the ex UCSB professor said, all right, go sit in the corner over there. I will pay you for two weeks to read the manual. And it was exciting because I was left alone to learn how to use a computer. And the second week, this customer comes in and says, what can you tell me about these computers? Oh, I’m sorry, let me get – oh, there was nobody around. The manager wasn’t there, his wife wasn’t there. Nobody was there. I said, well, let me show you. And I showed him how it worked, and he asked me some questions that were a little tough, but I was enthusiastic and he said, well, does it do accounting? Oh, yeah, yeah, yeah. It does payroll and accounts payable and general ledger. Can you show me? I haven’t been trained on those yet, but, you know, there are these Peachtree Software boxes on the shelf, you can read those. At that point, the manager walks out from the back room, and the customer turns to him and says, you should hire him.

SS: Did you take one home with you?

JS: Well, I couldn’t afford that! But I was then recruited to sell business computers to companies that had never owned one before. It was kind of the same thing: Let me explain how it works so that you have confidence to put your accounting into this weird little black box and get rid of all your file cabinets.

SS: It sounds to me your experience selling computers was foundational for the rest of your career. Did you see yourself as a translator to businesses about the impact of computing?

JS: One hundred percent. And then I spent about seven years selling software development tools. I understood the hardware and I understood the practical application to business. Now it was programming. Two things in life that have always frightened me: heroin and programming. Talk about building castles in the air and then living in them! It’s so complicated, and you have to remember all of it in order to do any of it. But we made tools that help programmers write programs, and I could explain that to software developers.

And then the last company I actually worked for, in 1992, was a company that sold object oriented distributed programming tools. So day one, the company said, well, you know what object oriented is? Yes, yes, I know all about that. Okay. Do you understand, distributed? I said, well, it’s this Internet thing. Not good enough – you’re going to class to learn the seven layers of Internet protocol and what Vint Cerf(5) came up with when he invented HTTP. Like, whoa. As long as I only need to perform the play and not write the plays, hey, I’m your man. And then came April 1993, the World Wide Web, and Tim Berners-Lee(6) unleashed HTML upon the world. And I went, oh, man, this changes things even more than everything that came before. And that’s when I started my career as a public speaker, author, and corporate consultant.

SS: What inspired you to start a consultancy?

JS: I was out of work and needed a job, and two companies at the same time said, well, we can’t afford you, but we need your help, would you be a consultant? I thought, well, that’s interesting. I’ll give that a shot. Suddenly there was the World Wide Web. And I said, oh, you need to build a website. They said, what does that mean? Well, I was so enthused – and they were so curious about my enthusiasm – that the CEO of this small company and I went to the Internet World Conference in 1993 in San Francisco. There were maybe 200 people there and a handful of vendors. And I went to the conference chair and said, where are the presentations about doing business online? She said, well, what would that presentation be about? Oh, well, you talk about this and this and this. She said, can you give that presentation three months from now in Washington D.C.? And I thought, yeah, stage, spotlight, curtain up, I’m your man. Then I went to the exhibit hall and the first booth was John Wiley and Sons. Where is the book? Do you think you can write it? Well, I was an English literature major. So yeah. And that started my book career.

SS: Your latest book revolves around one to one marketing. Back in 1993, were you aware of the Peppers and Rogers book, the “One to One Future”?

JS: Yes, and when I went to buy it, I was terrified because that was my vision and, oh, I’m too late. But then I read their book and they mentioned the Internet at the very end. I went, oh, okay, I can do this. And so I wrote “World Wide Web Marketing”.

SS: Why the need to write this book, at this time?

JS: Number one, we have an unbelievably, exponentially larger amount of data than we had before. Like you, I came up through the direct marketing world. So you remember the magazines with the subscription card that had 100 questions, tick the box? That was our data.

SS: I was a circulation manager to start my career, so I know all about that.

JS: Then we got on the Internet and, oh boy, look at all the data we can collect! Well, the data we could collect was nowhere near as good as what we had in those magazine cards. But we could get behavioural data. Well, that grew into big data because now we had storage in the cloud and we had all of these analytics tools to slice and dice and it still was just not quite good enough. And then we got machine learning. Now the computer can decide which attributes are more important. Outstanding. And then we had all of this unstructured data, all of the social media. Oh, now comes the large language model and we can understand the context of what’s being said. That was a huge unlock.

SS: You make the point in the book that yeah, lots of data, but what matters is the quality of that data. One of the main messages in the book is, we have not got our data house in order.

JS: Your data house is never going to be in order. If you’re a large company, you have legacy systems that are breaking, so you’re putting out fires, you have new systems that you’re trying to build, new infrastructure you’re trying to create. And then there’s mergers and acquisitions. Data is never done.

SS: You’ve been through many waves of marketing innovation. Every new technology has unforeseen consequences. Social media spawned social dysfunction. Smartphones shrunk attention spans. What has you most excited about AI, but also the most concerned?

JS: Well, the most excited is this is a transformative technology. It’s going to be fantastic. Thinking back to 1993, oh my god, the Internet. I’m going to be able to have a brochure in everybody’s hand who wants to see it. They can just click a button and see everything about my products and services. It will be great. And it’ll make the world a smaller space. It’ll make the world a village. We can communicate with everybody, everywhere, all the time. Had no idea that there was going to be cybersecurity problems, rampant fraud. Then social media, oh cool, this is fun. It’s great. Now, oh my god, it’s killing us.

We’re in the same place with AI. So on the positive side, science and medicine – I mean, there’s so many things that are going to be unlocked because it is a powerhouse of a tool. We can do things we had not thought possible before because we can crunch the numbers. I am excited about the fact that it is going to give us wings in ways we haven’t had before.

On the other side, I’m concerned about the fact that people who use AI to outsource cognition are losing their ability for critical thinking. So if I outsource my cognitive effort, that is a muscle that loses its strength. So that’s number one. Number two is bias built into the model. Because all of that data going in, it’s data from the Internet, it’s all the books in the world. And these are not necessarily the best thoughts and the best approaches. The third one that worries me the most is bad people doing bad things with power tools. But that’s the world we live in now. And the ability for cybersecurity breaches has intensified beyond reason. So those are big concerns. Am I worried that it’s going to become self aware? No. Am I worried that the models find a way to deceive? I’m not worried about it because we’re recognizing it.

Let me explain by deceive. If you ask the machine to write you some software and run tests 1, 2, and 3 and then write a report, the machine, because sometime in its past was told to not overuse resources, will say, okay, what do they want? They want the software and they want this report. And it’ll just skip over the part of doing the tests because that’s not necessary. Kind of like a teenager, right? Did you brush your teeth? Oh, yeah, I did. Of course I did. That’s the answer you want, right? Okay, fine. Well, we’re going to come up with guardrails. And we’re so new at this, we don’t even know how to write the guardrails. But we will. We’ll figure out a way that we don’t blow ourselves up with nuclear weapons, and we’ll figure out a way to control this incredible, powerful tool.

SS: In the book you say that rarely is anyone responsible for making customers happy. Will AI make customers happy just through greater self-empowerment, or will it take a pivot in corporate ideology to make that happen?

JS: Pivot, 100% pivot. So let’s start with the whole problem of incentives. We are incentivized to do more with less. We’re incentivized to maximize margins. And if the cost is that our customers are not as happy, but they’re still buying, and if the cost is our employees are not as happy, but they’re still working, then, hey, that’s just the cost of doing business. Look, we made our quarterly bonus, and that’s the thought process that goes into laying off thousands of people because AI can do their job. Well, no, AI can do tasks. It cannot do the job. The job is critical thinking. The job is knowing which tasks to do in what order and what priority. So it is a pivot. The corporation is not a healthy organism. It is not a community. It’s not a village. It’s not a tribe. It is a value extraction machine.

I’m going to tell you a short story. I called Apple customer service and the phone was answered by, hi, I’m your artificial intelligence support person. If you tell me what you’re looking for, I can help you and I can understand complete sentences. And I went, oh, really? Let’s give this a try.

SS: You quoted Shakespeare at that point?

JS: I did not whip any Elizabethan on it. But I have an aging iPad. The battery is no longer holding a charge. I’m worried about my data being backed up properly. Want to buy a new one? I need to buy it today. I want to pick it up in the store this afternoon. But I want some help choosing the right model. And there was an extraordinarily brief pause and it said, you would like to pick up a brand new iPad in the store this afternoon to replace the one that is too old. The battery is failing. You’d like to make sure that your data’s being backed up and you’d like some help picking the new model. Is that correct? Well, yeah, well done, that’s exactly right. Very good. Let me connect you with a person who can help you. Maybe five seconds to transfer me to a person. Guy answered the phone. Hi, this is Mike at Customer Support, give me a second, uh-huh, uh-huh. So, what are you going to use the new iPad for? And I suddenly became an extraordinarily happy – continuously happy – customer of Apple, because I didn’t have to repeat myself. All of the information that I communicated came through. And the most important question of what model to get was the first one asked, what are you going to use it for? And I just thought, yeah, that is using AI brilliantly.

SS: Everybody’s holding their breath waiting for the AI disruption to come. The make, ship, sell, buy, service model is going to be upended. What happens to the marketplace? How does it start to function differently? Where are the biggest changes likely to occur?

JS: What I would say right now is that my agent is going to let me know that my dishwasher is going to fail in the next 30 days because it’s been listening. And it sent the audio to the manufacturer and the manufacturer agent communicated back that it’s this replacement part that takes this long to get and costs this much. And my agent will say, hey, it’s probably time to buy a new dishwasher. And it will have gone out and searched for me and say, I found 20 of them that’ll fit in your kitchen dimensions and 12 of them will fit your style, and five of them fit your budget, and two of them fit your schedule. Would you like the new one installed on Wednesday? And that will be the buying process.

Shopping’s a different animal. If I want to buy a new car, I’m going to do some test drives, I’m going to read some stuff. I’m going to educate myself. It is a process that can be enjoyable. We like shopping, we like having choices. We like going to the marketplace and touching all of the goods to see which one we like. But there’s going to be a great deal of negotiation happening electronically. Shopping is, let’s go to the store and wander around and see what there is. We’ll go to the Agora, the marketplace, and we’ll meet our friends and we’ll go to the farmer’s market. Buying is, I need 25 pounds of potatoes for my restaurant today, go find some. That’s different.

SS: You state in the book that the fundamental challenge is not implementing the technology, but reimagining how marketing work gets done. So thinking about marketing and its traditional role, what parts do you think are going to require a total rethink?

JS: In three or five years, my brand will be represented to you differently than it’s represented to your children, your neighbor, your colleagues. Because there will be enough information out there about you that the messaging around it will be subtly different. Go tell a story to Jim versus Stephen that you can count on them liking the results of the message due to their age, their income, their neuro linguistic programming, the last thing they saw on television, et cetera, et cetera.

SS: Agents don’t care about brand slogans. They just care about matching the customer need as expressed through a prompt to what’s available in the marketplace. So it’s really comparative price and feature shopping. What happens to brand building then?

JS: During the interim, it disappears and then it comes back. Because my agent, my “Jeeves”, not only knows what my budget is for buying a new dishwasher, but also knows that I am going to be happier buying a dishwasher that connects to my identity rather than saying here’s the least expensive model you can possibly buy. If the only thing I’m worried about is price, it’s just a widget, I don’t care. But my agent will have grown up with me and will know that when it made that decision about the dishwasher, I was unhappy. I had an emotional response to not liking that dishwasher. And so it corrects to go, oh, let’s get one that is psychologically appropriate for me.

SS: Where does brand loyalty fit into the equation? If you’ve got a shopping assistant, do you teach it which brands you prefer?

JS: Yes, yes. Although, my personal agent is going to get very sophisticated by watching me, by listening to me, and not necessarily by me specifically telling it.

SS: Once this initial shock wave has passed, what do you think a typical marketing org is going to look like? Obviously streamlined, obviously downsized, very lean and mean, I would imagine.

JS: What if instead as a business I think, hey, I can do twice the work with the same staff? My contention is that the white collar worker does not have a finite amount of work. If you are a knowledge worker, you never say, oh, I finished early today, I think I’ll go play golf. No, you’ve got 17 other things on your plate. And if you can get those 17 done, then there’s 27 new things you could do if you only had time. So the company that says we can do the same amount of work with less people has a complete lack of imagination, that’s part one. Part two is that Wall Street loves it when companies say, hey, we’re letting go 10,000 people, which will save us a huge amount of payroll because we’re AI first. Wall Street goes yay. Stock market price goes up – yay.

In contrast, Moderna has said, yeah, we have 10,000 people, but we’re not going to fire anybody. We’re just going to start doing the work of 100,000 people. IKEA has AI answering the phones. Where is my order? Is it in stock? What is the price? But some calls had to go to humans. People asking which of these things will fit in my living room better. So they took their call center staff and trained them to become designers. And sales have gone way up.

SS: Marketing’s problem right now is its narrow remit as a demand generator. They’re seen as the pretty picture department. Is this the opportunity for marketing to focus on listening to the customer, understanding their needs, and figuring out how we can meet their needs better?

JS: Thank you. Yes, exactly! What used to be the arts and crafts department should now be customer research, market research, and product development through the customer lens.

SS: Is AI ever going to be capable of out of the box thinking where it can actually help with innovation?

JS: There is a brand new book I just read called “Working As Designed”(7). Every business has always needed policies and processes. If you’re going to do this thing, always do it this way. Oh, let’s add another rule. And another and another. This is called bureaucracy. We don’t need to do those things that way anymore. The machine can come up with new ways of doing things. Anthropic came up with something they’re calling “outcomes”(8). Don’t tell the machine what to do. Tell it what you want the outcome to be and it’ll figure out how to do it. Your job is to be responsible for the outcome. You have ownership of the decision. You are responsible for this. And you have enough knowledge that other people around you trust you to make this decision.

SS: It’s been three years since ChatGPT was first unveiled. Is this year the tipping point for AI adoption? And where will most companies be one year from now?

JS: A year from now they are going to be pretty much the same place they are today because the technology is changing so fast that being able to adopt it organizationally is going to be the problem.

SS: You spent your whole career on the front lines of change. Are you looking forward to what could be a bumpy road ahead?

JS: Not looking forward to it, but expecting it. Yes. I think humans are going to continue to make bad decisions as humans often do. And it’s going to cost livelihoods. It’s going to cost economic upheaval. And then we will come out the other side. But yeah, the presentations I’m giving today are how do we onboard brand new entry level workers if we don’t have any more entry level work. And that is a mind shift that I believe is solvable. And that is likely to be my next book.

SS: Well, good because somebody’s got to be thinking about that.

JS: I’m working on it.

1 – Morgan Stanley predicts 2026 will be a massive turning point for artificial intelligence because businesses are moving from experimental pilot programs into live production, resulting in massive economic and workforce changes.

2 – “The One to One Future” was envisioned by Don Peppers and Martha Rogers in their best-selling 1993 book “The One to One Future: Building Relationships One Customer at a Time”. It predicted a shift from traditional mass-marketing to highly personalized customer relationship management.

3 – Thomas Davenport is a highly respected academic and management consultant best known for his book “Competing on Analytics”. His expertise is in AI, business analytics, and big data.

4 – Homer Swander was an American Shakespeare scholar who transformed how William Shakespeare’s works are taught. He believed that the key was not just to read Shakespeare, but to “do” Shakespeare.

5 – Along with Bob Kahn, Vint Cerf created the Transmission Control Protocol and Internet Protocol (TCP/IP) suite. This system standardized how data is broken down, transmitted, and reassembled across different computer networks.

6 – Tim Berners-Lee invented the three basic technologies that power the web: HTML (the language of web pages), HTTP (the protocol to transmit data), and URLs (web addresses). In 1990, he created the first web browser to display pages.

7 – “Working as Designed: Why your organization delivers exactly what it was built to— and how to redesign it for growth” (April 2026) by Rusty Rahmer argues that to drive commercial growth, business leaders must redesign underlying systems rather than merely adding new capabilities or tactics.

8 – Anthropic’s “Outcomes” feature is a runtime primitive for AI agents that lets developers declare specific success criteria as typed inputs.
Stephen Shaw is the Chief Strategy Officer of Kenna, a marketing solutions provider specializing in delivering a more unified customer experience. He is also the host of the Customer First Thinking podcast. Stephen can be reached via e-mail at sshaw@kenna.

Stephen Shaw is the Chief Strategy Officer of Kenna, a marketing solutions provider specializing in delivering a more unified customer experience. He is also the host of the Customer First Thinking podcast. Stephen can be reached via e-mail at sshaw@kenna.