Answer Engines: The New B2B Playbook with Usman Khalid

B2B is going through a quiet revolution, and it has nothing to do with a new CRM or a shiny new channel. The biggest change is how buyers seek truth: they’re stopping the endless clicking and starting to ask AI for the best answer for their specific context. If your company isn’t structured to be that answer, you may not even make the shortlist.

We’re joined by Usman Halid, CEO and founder of Centric, to unpack what “answer engines” really are, how retrieval augmented generation (RAG) works in practice, and why these AI-native interfaces are collapsing the traditional B2B sales funnel. We also dig into what AI systems do when your data conflicts across pages or internal systems and why “verified, consistent information” becomes a competitive advantage, not a nice-to-have.

From there we get tactical: how to rethink your website as your most important storefront for answer engines, why master data management (MDM) is suddenly urgent, and how emerging connectors can open a path to agent-driven buying in procurement, renewals, and standard RFQs. We close with clear recommendations for B2B leaders to treat answer engines as a real sales channel and align marketing, engineering, and digital transformation around a single source of truth.

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Transcript

The Quiet B2B Revolution

Jim 0:04

In B2B, we're living through a quiet revolution. One that isn't being led by a new marketing channel or a new CRM or even a new category of software. It's being led by a shift in how people seek truth. For decades, buyers navigated. They clicked through websites, downloaded PDFs, skimmed through case studies, and they waded through endless funnels designed to nurture them. But that era is ending. Today's buyer doesn't navigate, they ask. And the systems that win are the ones that answer. We've moved from search engines to answer engines, from linked list to synthesized clarity, from here are 10 options to here's the best option for your specific context. AI native interfaces like Copilot, Chat GPT, Perplexity, and increasingly enterprise grade platforms like Centric are redefining discovery, evaluation, and vendor selection. They're collapsing the traditional B2B funnel into a single conversational moment. This shift isn't cosmetic, it's structural. It changes how companies position themselves and how they structure knowledge, how they compete, and ultimately how they grow. And today we're joined by someone who's been building at the center of this transformation. Usman Halid, CEO and founder of Centric, is one of the leading voices shaping the future of answer intelligence in B2B. His work sits at the intersection of AI reasoning, enterprise knowledge architecture, and the new buyer expectations that are emerging across every industry. Usman isn't just observing the shift, he's engineering it. So let's dive in. This is Answer Engines, the new B2B playbook. Usman, welcome.

Usman Khalid 1:56

Thank you very much, Jim. And it's a pleasure to be on your podcast. I'm a big fan. I listen to your podcast, find it very knowledgeable. Thank you very much for uh bringing me in as a guest. I would love to talk about the topics and share the knowledge that uh I'm learning right now on a day-to-day basis.

What An Answer Engine Does

Jim 2:15

Let's first talk about the anatomy of answer engines. You know, what is an answer engine? What does it actually do and how does it operate?

Usman Khalid 2:25

Oh, so that's a really good question. So basically, right in the beginning when ChatGPT 2.0 came out, so it did not have access to the web. So it was just answering based on pre-trained data. And the way it uh basically answers on the pre-trained data is it just tries to predict the next word that should come. But now lately, what we have seen is that the reasoning has become really more intelligent and it uses something called RAG, which is retrieval augmented uh generation. So what it does is on the fly, it goes and it different answer engines have their own search engines behind them or search APIs behind them, and they pick up a couple of answers. And and interestingly, Jim, uh this is this is quite interesting that they just read the first 60 words of the web page before they decide whether to chuck it in the bin or use it in the answer. So uh so as an example, Chat GPT most likely, so none of them actually disclose which engines they are using to do that search, but ChatGPD is widely known to be using Bing, and Claude is widely using widely known to be using Google search APIs behind uh for their RAG searches. And Google Gemini, we all know what they are using.

Why Answers Beat Search

Jim 3:54

And when it comes to answer engines, why do they outperform uh search for uh business-to-business uh complexity?

Usman Khalid 4:03

Excellent question. Uh so so, Jim, basically, so so let's go back to what actually search has been throughout these years, right? So, why why were people using the search engine? So they would be confused about something. They would go like, all right, I have to talk to this computer. I have to get the knowledge that I want to know. And they would synthesize a search. So if you remember like five years ago or 10 years ago, if we were going like, what is the best CRM system out there? So instead of searching it like that, we would go like, ah, so what CRM system is good for this or that? It wouldn't be a full natural language question to uh the search engine. And we would start clicking the top five, top ten. I was one of the most excited people when the web browsers invented these multiple tabs instead of multiple windows, because you just go right-click, open it, and so on and so forth. But the whole pretext, the the reason we were behaving like that was just to get a simple answer. That what is there, right? What so well, so so now the interesting bit is whenever we talk about answer engines, so there are two schools of thought. One is the answer engine is just a category of its own. The other bit is it's the new human computer interface. It's more efficient than clicking through different web pages, than clicking through workflows. Uh, and so the new computer interface, like the interface of 15 years ago, was the web browser. The interface for the next 10 years is gonna be chat-based. And right now, we are seeing the foundational models behind it. In the future, we are gonna see more and more connectors behind those, but more a lot more people, and and it is very natural as well, like just chatting to your computer, more and more natural than just manually searching and opening the web pages and then figuring out, you know, where the respective information is, right? So, so from that angle, uh, you know, if we start thinking of all these answer engines or the chat interfaces as the new human computer interface and start thinking about how to utilize it best for B2B promotion, would be the right thought process.

Enterprise RAG And Data Truth

Jim 6:34

Could you go into uh some detail on Centrix model, how it operates?

Usman Khalid 6:40

So Centric basically uh for its enterprise models, we actually uh deploy using Azure. So so there are a couple of things now, right? So the first thing is um we we work as consultants for our clients, right? We have built internal models for some of the largest corporations across the globe. Um but what the way we do it is the first thing is the data needs to be accurate and truthful. It cannot be like your one system is saying that uh the width of this product is six inches and the other one says it is eight or ten or twelve, right? So that becomes a data problem. And as soon as AI gets confused about something, it's not gonna show that up in the results. The second bit is whenever we talk about sovereign uh models or enterprise models, 90% of the time we just talk about utilizing either the open source models and putting them behind the enterprise firewall and using a really rich RAG interface. So enabling them to synthesize the data that is available from within the enterprise, right? Uh so and and training a model specifically for a given enterprise, like except for the really the Fortune 10 or the Fortune 50, as of today does not make sense. By next year, it would start to make sense. Because companies are so some of the companies out there are planning to have their virtual employees trained on their existing employees. So, you know, when we come to when we go to the office, open our email, see the stuff, work in a certain manner, yeah, maybe take a coffee break, come back, start working on presentations and stuff like that. So the model would actually be trained based on those bits. And Mark Zuckerberg uh recently he was asked a question uh in an open town hall that uh what type of tracking is happening on the uh on the employee phones? And he did not give a straight answer. So which means that there is a there is a massive rumor in the market that all the Facebook provided phones to their employees are being tracked based on their behavior on the phone. So so from that angle, the models themselves are evolving very, very fast. Uh, and as as you might be aware, you know, the the next version of ChatGPD might be better than Claude, the next version of Claude might be better than ZDOT AI, so on and so forth, and Kimi, and you know, and we have to look at it from a global perspective on the race in terms of developing the most advanced model. And these models are gonna be specialized, uh, as I believe, as we move forward. We are currently in a world of generic models, and we have already started seeing offshoots happening like codecs, like uh clawed code, um, etc.

The Funnel Flattens Into Chat

Jim 10:02

There are many that say that traditional B2B funnel it is basically dying, but my belief is that AI is actually forcing the evolution of traditional B2B funnel. Am I correct in that assessment?

Usman Khalid 10:18

Oh, uh so uh have you read that uh Forrester report about the new B2B funnels? That uh so basically the whole traditional B2B uh funnel from awareness to consideration to uh basically uh going you know uh evaluation and then purchase. So the first part, which is awareness, now people just describe their problem. Previously, they need to they they need to be aware of what the solution could possibly be. So, as an example, if your problem is that you are unable, you you want to uh basically have more automated sales, or you want to keep a customer data in a structured format, the way you would do would be you would have to get aware somehow that there is a category of softwares named CRMs that exist, and then start searching from there. But now it's basically you go and you tell the problem that, oh, my problem in my company, or I have this set of data, I do not know how to manage it, what needs to happen, right? So the whole problem statement and uh the solution recommendation is to a certain extent coming from AI. And there are so many studies around that that two things are happening in this regard. So one is there on an average B2B sale, there used to be 13 people involved in that decision from the client side. Now that number has come down to 11. So that's the first change. So now less people are involved. The second bit is that there used to be right in the beginning of the requirement gathering phase, people would uh the buyers would call up the vendors and ask their help to define that problem statement. To and and by defining that problem statement means like, all right, so you are a CRM company or you are an ERP company, come and define the problem that I currently have so that I can go to the management and grab some budget, right? So that's the second part. So it's not happening anymore. AI is synthesizing the answers, so it is basically your coworker, right? And it is only, by the way, one more thing that is that I firmly believe AI is your coworker that can only be as good as you are at your job. It cannot be better than that because your prompting skills and so on and so forth, and your reviews and the way you're gonna prompt, it cannot out, it can do things more efficiently, but from a final end uh output perspective, it cannot be better than you, right? So so so when we look at that part, that the whole funnel, the the top part of the funnel where the person needs to get the awareness and would come to your website and so on and so forth, and then part of the funnel would be that there would be certain playbooks, you would let them download certain things, it would be Get it so that this becomes an MQL, and then you can further enrich it, all of that is gone, right? And what is important right now is instead of uh so getting like on top of organic search results is still super important, don't get me wrong, you know, because we do not want to uh start the migration process before all our buyers move as well, but more and more buyers are staying within the AI ecosystem. Like right now on Google, uh, 65% of the searches do not end up in a click. So people look at AI overviews and they're done. Or they are just getting information at that level. So if we talk from that perspective, all your structure, the way you are giving the information out about your either product or service, it becomes extremely important to uh to synthesize it in such a manner that it is easy for AI to not only absorb but to but to think about your buyer because your buyer is going to come up with what are the features it has. But the very next question that they have is uh what is the security and privacy of this solution and can I actually trust this company? So all these things need to be well formed, well structured within every sort of uh fed in every page so that the AI can pick it up in that right context. So it is collapsing, it is collapsing, it is flattening. So the funnel looks like you know a pretty flat one right now. And and it's only just gonna go further uh and further flat because as you might be aware, Salesforce just this month has released its whole e-commerce agents. By e-commerce, I mean B2B e-commerce as well. So Salesforce is doing that, OpenAI uh work is is doing something like that from a procurement angle. There is another company called Leo. They have just raised $30 million from A16Z, uh, which is a very known VC to uh uh their their success rate is much higher than regular VCs, yeah. Uh that are basically rebuilding the procurement layer for the enterprises. So the buyer behavior is definitely changing. Where it's gonna land at at the end, we can sort of guess right now, uh, with a fair degree of accuracy, but it still is a fast-changing landscape.

MDM And Website As Your Storefront

Jim 16:19

Yeah, now that you've gone through and really detailed the B to the new B2B playbook, um, how does Centuric help enterprises in in competing in this answer first market?

Usman Khalid 16:33

Excellent uh question, Jim. So um whenever we look from a business, so sort of a revision revenue generation perspective, right? The the biggest value that uh or or the biggest showroom or a shop that an organization has is their website, right? So you have to basically restructure the website. That is definitely one part. The other part is uh, as I mentioned earlier as well, so there is something called master data management. That's a category of softwares uh where you basically make sure that all your internal systems talk to one system and you synthesize all your product data or in the and and make it so it basically becomes the Bible or the the absolute true form of what your organization does and then publish it from there. So those systems are called master data management. We do implement that, and that's the highest demand right now that we are seeing. So the companies that are planning to go on the AI route, what we are seeing is they've they have like potentially like employed certain consultants or so on and so forth, but they are coming back with specific MDM RFPs and RFQs to us and going like this is our problem, this is what we want to implement. Our data does not talk the same language. We have errors in pricing, errors in specs, errors in practically everything, yeah, uh across the systems. We want to make sure that all of it is one. So uh, because if you provide um, you know, absolute true source, which would be your organizational website, and show AI multiple different answers for the same question, AI would just completely omit you. Go, like, all right, I cannot trust this person, right? They are saying it's a hundred bucks, now they are saying it's 150, now they are saying it's 200, right? So so I can't I can't really, you know, like as a good custodian to whoever is asking me the question, I cannot possibly show this data to them. So that is uh the first part. And uh whenever we talk about that interface, so so the way companies are exposing their information right now, and I'm I'm gonna also talk about how they are gonna be exposing their information in the future. Um right now, as of today, it's through the website. That's what they give to the world. It's public, what they do, how they do it, whatever they want to expose. So for the answer engines to come and uh you know, uh crawl your website and get to know information about you is through that. And obviously, third-party forums like Reddit, Quora's, so on and so forth, but those are primarily used by AI for the verification purposes, because it, you know, like if you have customer test testimonials on your website versus on Quora, people are gonna trust Quora a bit more because it's a it's a third-party website. Um the second bit, what's happening in the future are the MCP connectors uh for different organizations, right? And and we have started building those MCP connectors as well. And we are Claude partners, uh, but as you might have noticed, that they just started their claw uh Claude or Anthropic has just started their partnership program. We are one of the companies part of that program. Um, and uh MCP connectors would be the way uh where you can expose more deeper information, like even opening up support tickets with your company. So it could be a post-sales play. So this is where people, so so whenever we talk about answer engines, we also have to think about you know, it's an answer engine today, but it's an interface tomorrow, right? So people are gonna just interact with their computers using that.

AI Agents Take Over Procurement

Jim 20:50

Earlier, you had mentioned with B2B, the reduction in the amount of um uh of uh people involved in the process. Um when it comes to AI agents, um, what's your prediction? Are they gonna become ultimately AI agents become a primary interface between the buyers and the vendors?

Usman Khalid 21:11

Oh uh Jim, uh I think there would be two types of buying. Uh and uh but and basically whatever the companies and and I I'll give you uh a real example from the market right now. So so let's take the example of Microsoft. Yeah. Uh and Microsoft Partner Network, one of the biggest partner networks across the globe. Uh so uh they have two types of partners. One are just reselling licenses, so the prices are sort of known. The discounts based on volume purchases are sort of known in the market. Um, and those are pretty straightforward purchasing. So you want to purchase. 10,000 Windows licenses with Office 365, so on and so forth. You throw out an RFQ, you already are aware what Microsoft list prices are. You know you are buying 10,000 licenses, you expect a 25-30% discount on top, which uh is sort of the standard. So all of those buying is is gonna move to agents, right? So where the end user is not buying a solution, it's the procurement buying a solution and negotiating. So where where basically technically everything is qualified, it probably is a renewal and so on and so forth, and only the procurement department is involved. Because you don't see IT heads getting involved, go like, ah, I forgot to renew my licenses. That's procurement's job now, right? Uh so that that level of agents we are gonna see within the next six months. So get ready about it. And because procurement, because I believe every human wants to do less work, and this is a good thing, right? Not a bad thing. Uh, so they would try to offload this low-value work of picking up the phone, calling up guys, hey guys, we want to renew the licenses, what's the price this year? Calling up the other vendor, staying on hold for five minutes while the receptionist finds where the salesperson is. So all of that is going on that. So companies should definitely build out their MCP connectors. If if I had like 500 products to sell, SKUs to sell, I'd build it tonight. I would not even wait for the next week. So, because that would give those procurement teams the ability to just go, like, all right, you want the prices, here are the prices, here is the official proposal that you can basically put in whatever your procurement cloud, right? So, so those are going agents within this year. The other part, the other type of sales have been consultative sales, right? So where the the final pricing, the effort estimation, or even the final solution is not there with 100% clarity. Like a simple website project, yeah. You might be thinking you need 10 pages, but in the end, you might need 12 pages, right? So this is where the the final touch of an expert is gonna come into play. But is that expert a salesperson or a subject matter expert? And that is what the question would be. So is so traditionally, and I used to be a solution architect in Oracle like 15 years ago. So we were like the trusted advisors to the client. So we were told that, okay, you know, like your job is not to sell more, your job is to make sure whatever is being sold is technically qualified to solve the problem of the customer. While the sales team that we were working alongside, their main role was to build that relationship, to make sure that you know they are sort of aware of what's happening in that account, so on and so forth. Right. So I believe that technical architect role is here to stay. But that sales role for just a massive outreach, SDR role, uh, which is sales development reps, they send emails the whole day, phone calls, so on and so forth, those roles uh are those roles will have to do higher value work, right? Building a relationship, you are not gonna give me a $5 million contract just because you like me. I need to be, you know, representing something of $5 million value, right? So so that that needs to be set in place. So consultative sales, humans would be part of the loop. Right? Regular sales, licensed renewals, hardware, you know you want 5,000 GPUs from Nvidia. You don't need to talk to a human for that. Yeah. And what you detail. Oh, go ahead.

Jim 26:13

I'm sorry.

Usman Khalid 26:14

No, so so I'm saying so humans still need it, but for higher value jobs, instead of building relationships, understand your product, understand the value, understand how it uh how that value applies to different industries and sectors so that you can talk the talk when the time comes. Because the customer would already have done the research and would come to you with and fully known that who your top two, three competitors are and what are their peak points because AI would would tell them everything. Yeah.

Jim 26:52

And what you've detailed uh throughout our conversation here clearly points out that the companies that are going to win are going to be the ones that you know answer the best, they're the fastest answers. And they're also answering with verified information, truth, knowledge, uh, and that's going to be super critical. Let me ask you this question related to uh you yourself and also related to centric.

Making Answer Readiness A Company Job

Jim 27:18

You know, how do you convince uh companies that are looking at B2B to get out of the mindset of it as a marketing, uh a marketing vehicle, B2B sales, to being strategic for their company?

Usman Khalid 27:34

Yeah, so so Jim, um whenever we talk about sales or revenue of a company, we tell the company on day one that it is not just a sales department's job. It's the whole company, and especially in the age of AI, it's the whole company that has to take it forward. If you have a very engineering heavy product and you just let marketing develop a website without providing them the right content, yeah, it's not gonna do its job, right? Uh so whenever we talk about so so now there are so many different surfaces where you need to make sure that that you're on spot. As we were mentioning, like MCP connectors, building those is not a marketing job, right? It is an engineering job, right? So that your your company's products are available with the right data. MDM master data management is a digital transformation job, right? It's not a marketing job, right? Uh so that department gets involved. And then finally, whenever a customer is actually doing the research, yeah, on you and your competitor, you need to be aware of that. That is product marketing and engineering job, right? That's not your typical brand marketing or the central marketing team's job. So the whole company needs to be involved in in this phase of uh GTM, which is go to market, and make sure that the information that you are providing out there is of value and solves real problem. And you might want to cater to like the real problem statements as well. It also really depends on what type of a product you have. So if you have a niche product like um uh something to do with rockets and I don't know, but I don't know, let's just say rockets because there are practically five companies out there, right? So so if they are gonna do their problem statement, right, out there looking for a vendor, you need to talk about, okay, I have CNC lathe machines that can have the accuracy of 0.001 millimeter or whatever those ranges are, right? Because that's that's a critical decision-making factor over there. Um and to make sure that they are able to find you, you need to make sure that your case studies are out there in the right format, your uh different layers of interaction. So as I mentioned previously, website was your interface tool. Now your application itself could be an interface tool.

Jim 30:17

Yeah.

Usman Khalid 30:18

Uh the way when people say SaaS is dead, I sort of agree with that. Uh but I I would say um your SaaS is gonna be used by your agents. So so so there would still be certain value for the solutions that have been built over these years, uh, in terms of whether those are uh you know, like sales outreach or CRM, HubSpot type and or other elements, but maybe your agents would use that. And I I basically have been talking to a lot of people, and uh, Jim, I believe 10 years from now or five years from now, 10 years is too long in the age of AI. So you will have a humanoid at your home, but if you have to iron your clothes, if if the humanoid has to iron your clothes, you'll have to pay someone $499 a month for that skill set. So so that MRR though is gonna go into that skill set. If you want your humanoid to be, you know, like be able to look at the physical invoices and put them in a nice spreadsheet. Somebody has to provide that skill set for your humanoid, right? And then when you talk about uh other SaaS companies, especially where uh, you know, like Href and Sembrush and these type of companies, where they are basically data brokerage SaaS companies, right? They still have uh a play, uh, I believe, because they're gathering all that data. So far, they have been selling it through web interface. Now they have to sell that through the chat interface as well. And uh there is a possibility that in future a lot of these SaaS companies are gonna go into API pricing, then monthly pricing because those gates have been opened by the foundational AI companies. You know, when we pay 20 bucks or 30 bucks to open AI or Claude and so on and so forth, they lose money on our subscription by a massive amount. They want us to use their API-based pricing because that is profitable. And Claude, uh, so Anthropic just released those numbers. So for every dollar in API pricing that you spend on Claude, 56 cents out of that is compute, and the rest becomes gross. And of course, by the time it comes to net, it's practically zero right now, but there would be margins there.

2026 Playbook And Final Actions

Jim 32:58

In uh in closing out this episode, uh, we can clearly say that the you know the future of B2B is an answer-driven world. Let me ask um this question of you. Uh, when it comes to B2B leaders for the remainder of 2026, what's your recommendation? What do you believe that leaders should be doing to stay ahead of everything?

Usman Khalid 33:21

Two things. The first thing is look internally and see whether your organizational data, especially related to that data that you share with clients, is there a mess or not? If it's not, you are already ahead of 90% of the uh companies out there. If it is a mess, get it fixed. The way to fix it is uh through the category of solution called master data management. So so fix it, but bring that category of solution within your organization. You need it. The sooner you are gonna get it, the better it would be. Without doing this part, you are just gonna be uh you know getting behind and behind with every passing day. So that's the most critical part. The second bit is the way you are comfortable with different sales channels so far, that the sales channel, oh, I have a physical sales channel, my people go out there, I have a call center, they give a phone call, right? So on so forth. And you have a website, and so uh treat answer engines as a new sales channel. If you are gonna say, oh, you want to thrive in the coming, uh and I'm gonna use the word months, right? Because every day you are lagging behind, you you are lagging behind by a lot because everyone else is accelerating, right? And in this age of AI, every industry is gonna be rebuilt. Insurance companies are gonna be rebuilt, healthcare systems are gonna be rebuilt, your local workshop, uh auto mechanic workshop is gonna be rebuilt, yeah, with AI first. So if you're not gonna do it, someone else will do it. So, from a B2B marketing leader perspective, Answer Engine is a new channel that you have to take seriously. It's not getting away. 65% of the people that come to Google are not clicking on anything. So before you spend tons and tons of money on your uh PPC, just remember 65% of the traffic never clicks that. They just take the answer from the answer engine. So take that seriously and make sure while you are optimizing everything for AI, do not give it um information that conflicts. So this is where your MDM comes in. So that's the foundational part. If you haven't done the foundational part, please go to your digital transformation head, please go to your CEO, please go to your CIO and tell them to do it. You need it, right? And and by the way, the the good thing about MDM is it does not come out of the marketing budget, it comes out of the digital transformation or CIO budget. Yeah. So get that done and then basically just treat it as another sales channel. The way you, if the organization spends $10 million on sales teams, it should at least spend you know 10, 20, 30% of that on figuring out how to be ahead on this new interface. And and by the way, uh there are so many studies out there. Uh, I do not want to quote all of them, but uh by that time, so 80% of the orders are already produced, but are already given to the people that could show up in Answer Engine results, right? So the clients have already made up their mind before they even reach out to you. So when we talk about uh and and I believe this massive change, and obviously, since these studies are pretty new, yeah, that data is still somewhat questionable. It's not like hard, fast, you know, like I one person has done that research, and you know, like we all agree to that, you know, you might take a different set of people and the research results might be different. But I believe maybe in the future, the role of salesperson in an organization is gonna change massively. And marketing and sales, uh, and and we have already seen that with RevOps. You know, all the new trendy companies are calling it RevOps instead of marketing and sales. So so they they have merged it. Uh, and we are just gonna see more and more of that.

Jim 38:01

To learn more and also take action, I'll have uh Centrix uh website uh in the description. Uh Uzman, thank you so much for this opportunity to have a very fascinating conversation with you.

Usman Khalid 38:14

Thank you very much, Jim. It's a pleasure and looking forward to having these chats more often.

Jim 38:20

That would be great. All right, everyone. Thank you for joining in this episode. Uh please make sure that if you found value in this episode and you have colleagues uh or friends or connections that would also get value, please share this with them. And I really appreciate everyone's support and following of the digital revolution with Jim Kunkel. Thank you, everyone.

Usman Khalid 38:43

Thank you.