Why a software company made a series that is not about software

Edited for readability from the episode audio. Filler and repetition removed, meaning unchanged.

00:05
PHILIP IDESON: Hi everybody and today Art of Procurement is kicking off a brand new podcast series. It's called the Agentic Procurement Diaries and it's presented in partnership with Zycus. Now it's going to be published within the Art of Procurement podcast feed and this show is going to allow you to hear how CPOs are thinking about and advocating for their team's agentic AI journey but in their own words. We're here to talk about the project to kick us off in this series, its objectives and how we collectively believe it's going to help the procurement community. I'm delighted to welcome Aatish Dedhia. Aatish is founder and CEO of Zycus. Welcome to the show.

00:43
AATISH DEDHIA: Hi Phil, thanks for getting me on the show and we're very excited about this. We are in, I believe and I'll use that you'll see here that word again and again, we are in the midst of a revolution and in a revolution we need to as a vendor we also want to invest a lot on education of the community in terms of what's really changing, how it's changing and Phil has a fabulous community and that's the best place, it's only procurement people. We really want to get the message out and then in the series you're going to have with Phil is going to talk to multiple leaders in procurement about how they view agentic AI. This is our bit of educating the community. Thanks.

01:25
PHILIP IDESON: And we're so big on peers helping peers and taking experiences from each other because at the end of the day that's what helps you really drive, have confidence to make decisions to drive changes when you're hearing how your peers have done it as well and so that's a big part of this series is bringing those procurement leader experiences and making them as available and accessible to everybody as possible. Now before we go into some of the details of the series, I do have to ask you my stock question I ask all the time at the beginning of a podcast and that's did you find procurement or did procurement find you?

02:06
AATISH DEDHIA: Oh definitely procurement found us. Rewind back to early 2000, 2001, 2002. And we had a technology at that time and it was machine learning. We had machine learning technology for aggregating internet data and classifying it. It was that time a Bayesian classification model and so on. We had no clue about procurement but we were pitching it to a VC and we said take all the information on the internet and then classify it the way Yahoo and others would do and the VC asked can you do the same thing for procurement catalogs. I didn't know anything about procurement we went back but why not. We went we looked at it we worked POC with one of the customers and then the journey began. Procurement definitely found us but it was really the absolute right time because when we entered the age of digitization of procurement was really starting for it. In early 2000 it really started and we've been through the entire journey. And now it's another inflection point which is coming.

03:10
PHILIP IDESON: Yeah that was about the time I started in procurement as well and it was e-auctions was a starting point for us in the technology that we used and obviously things grew very slowly. It grew slowly and then started to explode in terms of the impact that technology and digitization can have on the profession and now we're at this such an exciting time for most of us. I know there's a lot of fears as well but it's a really exciting time for like what comes next because the possibilities are probably beyond anything that we can imagine. We sit within these four walls of what we think procurement is because that's what we've been taught procurement can be and now those walls are disappearing and now we're figuring out okay what can we really be when we use the technology that's available to us.

03:58
AATISH DEDHIA: No, I totally agree. What happened with the digitization wave which happened is it finally got procurement to the table. At that point procurement was viewed as really tactical and then you had in fact not all organizations even had a chief procurement officer there, VP of procurement and so on and it migrated to that but this is going to be again very different role. It's then again it's going to change how CPOs are viewed and they'll be viewed even more strategically because of AI and I'll come to that later.

04:26
PHILIP IDESON: Yeah so we talked a little bit about the last 20 years we've had automation, digitization around analytics, machine learning as you said is where you started. More recently the last three or four years now generative AI. I wonder if you could talk about what changes when we introduce the idea of autonomous agents and perhaps even a little bit before that because it's important from a definition perspective the difference between as we throw around terms like generative AI and autonomous agents.

05:00
AATISH DEDHIA: Sure. Okay good question but let me classify into two buckets and on bucket left is automation or digitization. What the software which exists as of today and which was primarily more standardization of processes, centralization of data and then analyzing and digesting those data and then obviously you had forms and workflows. What the technology automation really did it didn't automate but it's standardized. It made sure that people follow the same processes, the data is visible to everyone. Visibility became an outcome of automation. It definitely had its value over what was happening earlier. Earlier contracts used to be in drawers and now contracts would be visible with all the clauses and so on. That was one phase. Now the second phase I'll talk about is AI. It started off machine learning is and it's like I mentioned it's been a few decades since machine learning is there and machine learning was good at classifying data and analyzing data but technically gen AI is a subset of machine learning. Now again that terminology but what gen AI did was it could generate new content. It so earlier you had DeepMind. Which was in UK and they they really changed how neural networks work. It can generate data. Previously it was doing a task now it is generating information based on whatever it knows. Gen AI which started with the ChatGPT. Everything after that agentic AI is nothing but a thin layer on top of the gen AI. It obviously uses the power of the LLM but you need to harness the power of the LLMs which is where you have agentic AI. Now people harness the power of AI in two ways, first of all you add an agent. We also had the journey a few years back we said we have multiple agents sprinkled across our source to pay product. You can summarize a contract, you can generate an RFP. That is an agent. Now when you talk about agentic and agentic flow you do not start with a point, you start with the end outcome. What's the business outcome you really want to have for it? I need to buy something. Now it works backwards and lines up all the different agents which are required which is how real life work happens. You do you would identify what has to be bought, you identify the suppliers, you benchmark it, you will create an RFP. But agentic AI does that. Agents collaborate, they decide which path really to take but towards the final outcome. Agentic is a layer on top of the powerful LLMs, the frontier modules and on top of that agents doing multiple steps in collaboration towards a final outcome and that's what is agentic and people often confuse agentic with just a point agent and point agent is not agentic. An agentic flow as an analogy this plan my entire vacation where it understands your your requirements, your family's needs and what are the timings you are available and then it searches and it identifies and it books and it's ready your vacation package is ready. It's very similar to that as opposed to tell me what's a good hotel in this location. That's a point agent. With point agent you have a lot of agent sprawl which is happening but because of that people are missing the big ROI of AI. You have to start with an outcome, what's the end outcome and then work backwards to that.

08:37
PHILIP IDESON: And so when we talk more about agentic it's the coming together of all of the maybe point agents but doing different tasks but what makes it truly agentic is a system that brings all of those together so that to you it's seamless you don't know that there's multiple point agents going and doing tasks because you're just seeing the out one the outcome and it's all these point agents working together and sharing information with each other to drive a certain outcome.

09:10
AATISH DEDHIA: Yeah that's very important agents talking to other agents. They'll exchange information in a certain way. Which the other agent can understand and it can also pick which agents are really required to get to the final outcome but for you I rightly said Phil. It is transparent it will come as a senior flow you don't see the agents really handing off one to the other at the back.

09:31
PHILIP IDESON: Why is this cycle different for procurement leaders?

09:35
AATISH DEDHIA: As compared to?

09:37
PHILIP IDESON: Yeah when we talk about so as we think about digitization the different waves of digitization of procurements and as we've gone from just having access to technology to from an efficiency play to what agentic may now enable for a procurement leader and how that differs from previous waves if you will of digitization.

09:59
AATISH DEDHIA: If you look at the waves. Which have happened in my lifetime you heard obviously the mobile or the cell phone and then you had cloud and then you had before that desktop computers and so on. AI is very different in scale compared to any of those right and to put it in perspective what I feel like what we feel at Zycus this is it's once in a few centuries revolution which really happens. The closest analogy is the industrial revolution industrial revolution and you had once we had the machines coming in you had the assembly lines coming in it completely transformed the economy and people were doing different work after that people are consuming different stuff. It remade economies that remade industries and so on and what the industrial revolution did in copying what the human muscle really does. Is what gen AI is doing by in doing what the brain really does a lot of it where it can reason a lot. In terms of what it can do it can you can take a person out of college with two years experience and make him as good a category manager someone with 40 years experience managing that category if you have the right agentic flow. It's going to it's going to dramatically change. I always feel that people are significantly underestimating in terms of how AI will really remake not just procurement but it'll remake the whole world also.

11:42
PHILIP IDESON: And do you find that to be the case when you think about underestimating and also what do we overestimate you have so many different conversations with procurement leaders every day just doubling down on some of those things first of all that that perhaps the people you talk to are underestimating the impact of AI on from but then on the flip side are the things that they overestimate what they think AI can do or should I say agentic AI can do.

12:06
AATISH DEDHIA: Sure. First I'll talk about overestimating like it's it's the usual you cannot put technology on a broken process. We had we had agentic AI for intake and a customer put it on a process which says you need to get an approval for everything above $500. AI is going to do what it's what you wanted to do. If you have a broken process you so you have to not just put AI as a band-aid on top of it you need to rethink the entire process in terms of how it can really work. In fact AI can possibly decide what should be the thresholds based on how it has been purchased in the past what's the category and so on it can be very dynamic but our procurement leader is willing to take that risk. One is you cannot put technology on a broken process. Bad data AI can still handle that but a broken process is something which you cannot hide from.

12:59
PHILIP IDESON: Yeah you cannot hide from a bad process.

13:02
AATISH DEDHIA: Exactly. The process is very important because people don't rethink the process in fact if you ask AI it will redesign the process for you. It will redesign and tell you this is what the process should be based on your data which you have. Now coming to the other part like what they are underestimating and I was talking to someone and he mentioned that humans are creatures of habit and they change but they take time to change. People are underestimating how much AI can do as of today and I'll just give an example. At Zycus over the last two years using AI we have increased our efficiency by almost 45 to 50 percent which means we have half the team doing significantly more work, more products, more sales and so on. Now we are developing products writing code implementing difficult complex enterprise software. If we can get that efficiency there is no reason procurement cannot get that efficiency. I'm just using efficiency as one parameter obviously it will free up people to do a lot more strategic work which is there. People are underestimating in terms of how AI will significantly remake the entire operating model. What people are doing today they will not be doing tomorrow. People are not going to do accounts payable, people are not going to do tactical buying, people are not even going to do supplier risk assessments. They will be out working with the suppliers building relationship building relationship with the stakeholders, making judgment calls about the future which AI by the way cannot do. AI cannot for its life predict what's going to really happen in the future and humans have that instinct that judgment by talking to people and they really can do that. People are underestimating what efficiency gains you get and how will it really remake the operating model. But it's a normal cycle, you have some companies that are leading as you have a belt. Over the next 10 years I see that huge change happening within a procurement.

15:17
PHILIP IDESON: It's interesting you just put a time frame on it. I was going to put you on the spot and ask you for a time frame because I feel like it's a at this point it's not a technology problem for procurement leaders, it's a change management problem. The technology exists and technology is continuing to exist which will then enable you to do a lot of things that you couldn't do two or three years ago and so it's as much a change issue. One of the fears that I hear a lot is control losing control to an agent and I'd love your perspective on how do we govern agentic AI or how can we be thinking about governing so that the agentic AI, the agents and the system is doing the things that we want it to do, is doing the outcomes that we want but there's trust that it's not going to do more than that or that we still have that human and whether where in that process that human comes. Do you have any perspectives on how we can be thinking about that to help us overcome some of those fears and drive the change faster?

16:27
AATISH DEDHIA: Sure, there'll be two layers when in where the guardrails and as I call it will come in, there may be three layers. One is in terms of the software, the second is in terms of policy guardrails for AI agents and the third is the human in the loop. But the first I'd say one thing we have to realize is that obviously procurement is very close to finance. You're posting into a system purchase orders, invoices. And you cannot even get a few cents wrong like it has to be absolutely accurate. What you have is at the bottom there has to be a deterministic layer. For example at Zycus, a current source-to-pay software now becomes a system of record. You have the system of record, you have all the rules, you have the delegation of authority, the workflow, all of that stays in that system of record. That has to be really deterministic, it gates everything. Effectively it blocks AI from doing something really wrong. The second thing is you have when we build, so our layers which we have is we have a source-to-pay software, then you have a Merlin agentic AI on top. In the agentic AI layer, you can put for every agentic flow, you can put guardrails and policies. Do this, don't do this and so on. You can put a lot of guardrails within that. That also will keep the agent within certain boundary. For example if we get supplier responses for risk do you want to only use a supplier response or do you want to use external? External is fine but if you're getting a price from a supplier, you don't want AI to really round it off or make any changes. Those are the guardrails which you put. Now the third is we talk about autonomous agentic flows but every of our flow can be with human in the loop at any point. You can decide okay this is something which is very tactical for me to buy and I've seen AI do this again and again go ahead and do it autonomously. In the other case, you'll say okay this is the first time I'm doing this services RFP for let's say cyber security services just involve me in the RFP and when we're doing the final evaluation. On agentic sourcing, you can decide at what point the human in the loop comes in. What we do is we put guardrails one at the system level which is a system of record. Second is that the agentic thing and then allowing that control to the human to decide whether it should run autonomously or not an autonomous.

18:54
PHILIP IDESON: As part of that control, how much transparency does the human have into what an agent did audit trail or and it's as much of a to go back retroactively and understand okay these were the steps that were followed and then that helps drive the trust to know that okay those steps that were taken by an agent are the same steps that I would have taken as a human for example.

19:19
AATISH DEDHIA: Sure. What you have is one is you have the audit trail as I mentioned in the system of record. Everything is recorded what other what workflow it went through and so on and for every agent also we have an audit trail. The audit trail says that this is what the agent really did. That audit trail also helps people in understanding what is done. What cannot be done is you cannot tell why an agent did something okay so why did the agent recommend this particular supplier you can that often explainability of AI is not so easy but at least what AI gave it can definitely say okay I know the supplier told me that this is the price and I counted that the other supplier is giving at a lower price we need to give it a lower price I need to get early payment discounts for it and so on so you can see the entire trail of that in terms of what the agent really did. And then you but you still need to have that audit trail in your system of records if you try to build an agentic AI without a system of record you will fail because AI will go wrong in certain cases if you do not have that layer before the ERP. Which is really guarding everything.

20:34
PHILIP IDESON: Yeah interesting so I want to pivot just the last few minutes here to talk a little bit more about the series and lead into the rest of the series and the question that some listeners may be thinking is why is a technology company like Zycus supporting and making possible what's a pretty big undertaking in bringing these stories together that deliberately isn't going to focus on technology itself it's more about the journey.

21:00
AATISH DEDHIA: Yeah first as I mentioned we strongly believe this is a revolution. If it's a revolution as a revolutionary you need to really rally everyone around it right so we need to educate everyone about what is possible and what is not. Now obviously we are a vendor. We're going to pitch what we have in agentic AI which is why Phil we're working with the art of procurement so that you get practitioners right and they don't talk about technology at all but they would talk about how do they view AI what are the risk of AI they see what are the benefits what are the challenges what are the processes of trying out AI within that organization so one is obviously education because we have seen when we talk to CPOs they're very very curious in fact some CPOs have formed groups among themselves to say okay what are you doing about AI right so people are very curious about how everybody knows that something is going to happen right everybody knows that it's going to change so people want to hear from other practitioners in terms of what what is it they're trying what has worked what has failed and how did they go about it and so on.

22:10
PHILIP IDESON: Yeah I want to double down on that a little bit and anyone who's listened to the podcast recently probably heard me talk about this a lot but the procurement leadership that I see who are most likely to succeed are those that are the most curious and those that recognize in this current situation they don't have all the answers and so everybody is on this journey of discovery and as much as we can bring together everybody from across our community to be on that journey together the better it is for everybody because as I alluded to earlier earlier certainly my procurement career and as I mentioned it's been 20-25 years plus now procurement was a certain thing and it was just all about how do we optimize this certain thing that we do and that's what all the conversation was around but now if we continue to think like that that really constrains our thinking and it constrains how we think about the value proposition how we think about the business and operating model that surrounds it how we think about where we invest how we think about skill development and making sure the right skills are in place for when we do have agents doing a lot of work for us and those are all big unknowns at the moment so we're grateful for the opportunity to bring together some of these stories so that we can help peers or help procurement leaders learn from their peers that's really important.

23:30
AATISH DEDHIA: That's definitely very important and people need to know from others what's really how are they going about it because again like you said it will change the operating model for it so how do people visualize what's going to change when practitioners come and say this is what we visualize it which is really going to change but these are the steps we have taken now and that's very important.

23:51
PHILIP IDESON: Yeah and I'm sure you have a lot of these conversations in private with CPOs as you're talking both to clients and to those that you are getting to know are there any themes that you would pull out of those conversations or where you see right now the mindset of a forward-thinking procurement leader based on all these different conversations that you have?

24:19
AATISH DEDHIA: No that's a good point and by the way we used AI for analyzing that so what we've done is in all the conversations which everyone has across the organization with prospects and customers and we put it in the data lake and then we have AI analyzing it so what we identified is there are like a bell curve there are three segments of procurement organization or procurement leaders. One is AI hungry, the second one is AI curious and the third one is AI resistant and in fact the AI resistant over the last couple of years has shrunk to almost 15 to 20 percent now it's only in regulated industries like healthcare and so on but now coming to AI hungry, what we have seen the AI hungry ones is they are looking to do something in AI and it often stems from the board or the CEO. The board has said you have to do about something about AI, what are you doing and the CEO then ask the team or creates a fund in terms of let's try out something on the AI. The AI hungry are the ones who are you can do this frontline explorers, so they're trying out stuff. They have the management the approval, the funds and the backing to try on AI whether they're doing it internally, whether they're buying something from outside but they are the ones who are really experimenting and trying with AI and then you have the AI curious. The AI curious they know that AI is going to change something but they are often waiting to figure out what's the ROI. Obviously there's money to be invested, so the first category is given money saying do something with AI, we have gotten this initiatives. The AI curious are looking at what could be the ROI for AI. A recurring theme which is happening both in the AI hungry and AI curious is what is the AI areas we can focus on which can give us good ROI. There is a shift now which has happened because obviously AI economics also come into play, you're going to spend on the LLMs and so on. What are those areas, so we have an access which is saying what is the impact and the practicality for AI. People are trying to figure out what are the areas they can use AI for which is high impact, lower risk and so on. That's a theme that we are seeing across this AI hungry and AI curious and AI resistant, they will change and they always have a bell curve over time, that's a 10-year period I talk about it where people get converted that yes, it's applicable for me also but that's a very thin slice as of now.

27:08
PHILIP IDESON: That's fascinating, at some point in the future I'd love to unpack what those who are AI hungry and AI curious are doing and we can draw a lot of lessons I'm sure from some of those observations. Now as we wrap up I do have one last question and this is a question that we're going to ask throughout the series. The question is if we were having, you and I were speaking three years from now, what do you think that procurement organizations, what's one thing that procurement organizations will be doing that feels today like it's almost unimaginable?

27:42
AATISH DEDHIA: Let me tell you what people will not be doing three years from now which is unimaginable. People will not be processing invoices, they will not be processing tactical buys, they would not be really hiring category managers with decades of experience. All that will be delegated to AI. AI will do a lot of the tactical work for you. Now the challenge is if a lot of the work which you're doing currently is going to go to AI, your team members would be freed up. Now either you have a smaller team or you leverage the same team for different work. That's where the challenge would really lie. Once you free people up from tactical work, where are they going to spend that time? Are they going to spend time on new product introduction, working early in the cycle like you mentioned. Maybe the value proposition of procurement to the rest of the organization changes. It's not I'm going to manage supplier risk or I'm going to source for you and so on. It could really significantly change now. I definitely see that a lot of the work will be offloaded to agents and I talked about that percentage. It will start with 10%, 20%, 30%. It will go up to 50% maybe in three years. Now you have 50% more bandwidth. How are you going to leverage that? That's what the change. Other part I don't know. It depends on organization to organization, how people use human creativity, judgment, intuition in relationship building. How are they really going to change on that? People will have to start thinking in terms of how the operating model changes and what's your value proposition to the enterprise.

29:31
PHILIP IDESON: I love to hear that because for me the biggest question of today is what's next. There's obviously the journey to get there, which is the journey that all these organizations are on. As you say some are more ahead than others but then you have to prepare now for what's going to come later because otherwise you'll get to the later and then be looking around thinking okay now what's next? Now what do we do? And if you're thinking about it then it's too late because all those efficiencies that you have taken out of the system will result in my opinion in job losses because you are now having agentic systems doing the work. But if you prepare for that as you go on the journey now you have this open capacity and if you're ready for it that's where you can really drive exponential ROI. But you have to be preparing for that before you get to the point where you're able to go and use that bandwidth.

30:30
AATISH DEDHIA: Very true and I'd like to make another point because what happens is you mentioned people are experimenting and trying out stuff but people who are able to do that first will get a competitive advantage. That happens in every wave and one of the things I saw on your podcast also you often talk about what failed. Now especially for AI, it's very important for companies to fail and I'll mention why it's important. There was a book I forget by a Harvard professor, what are the right ways to fail? If you fail doing some simple stuff or collaboration it's the wrong failure. But if you fail in exploring a new area, so Christopher Columbus also had a failure and had a success after that. AI is new, so even at Zycus we have had failures as we went on the agentic AI. Two years ago we said we'll get a lot of point agents and we got it out, we didn't see the ROI from customers, we pivoted very quickly. But if you had not done that you're not being at version five where we are currently. If the same thing is true for the organizations in this AI and the good thing about AI is you don't have to buy a huge software. You can start with one flow, one agent, you just start with that and you learn from that in terms of what's happening. That adventurous spirit is what we see of the AI hungry companies really doing it and we'll see more and more companies getting to that for sure.

31:58
PHILIP IDESON: Well I'm excited to see how we continue to evolve the conversation and bring lots of stories in through the agentic procurement diaries podcast. For anyone who's listened to today, just a heads up we will be publishing the podcast likely every couple of weeks. We're here in the Art of Procurement feed as you've listened today, also on the Art of Procurement website. You can always check it out at artofprocurement.com, see the latest episode and we'll see what we uncover and explore and then share a lot of those findings from CPOs in their own words around how they're approaching and thinking about the use of agentic AI. Thank you so much Aatish, I really appreciate you joining me on the show today and I look forward to speaking to you again soon.

32:43
AATISH DEDHIA: Yeah thanks Phil it was great talking to you and we also look forward to what a CPOs is thinking about how they go about their journey. Thank you.

32:51
PHILIP IDESON: Thank you.

32:52
AATISH DEDHIA: Okay.