Andreas Welsch: 0:21

Today, we'll talk about using Generative AI in procurement and who better to talk about it than somebody who's actively working on that. Pedro Berrocoso. Hey, Pedro. Thank you so much for joining.

Pedro Berrocoso: 0:33

Good morning and good afternoon to everyone in the audience and to you, Andreas. I'm really excited to be here with you today. It's a great session, which I'm pretty sure is going to be interesting for many people here listening to us. And just to give you some background about myself, Andreas, I'm an independent consultant working primarily on two main topics, digital procurement, where I do have quite a vast background on source to pay implementations, and then emerging technologies in order to use them for process automation and digital activities, such as with AI, in order to drive as well productivity and efficiencies in businesses. Based out of Zurich, Switzerland.

Andreas Welsch: 1:07

I'm really excited that this is working out. So thank you so much for making time and spending time with us and with the community today. Wonderful. So hey, for those of you who are just joining the stream, drop a comment in the chat where you're joining us from today, I'm always curious to see how global our audience is. And I already see a few familiar names and faces here in the chat. So I know the U.S. is definitely represented. But who else has joined? That's always the question. Pedro, what do you say, should we play a little game to kick things off?

Pedro Berrocoso: 1:36

Let's do that.

Andreas Welsch: 1:37

Wonderful. All right, so this game is called in your own words. And when I hit the buzzer, even the virtual one here, the wheels will start spinning and when they stop you'll see a sentence I'd like you to answer with the first thing that comes to mind and why in your own words To make it a little more interesting, you only have 60 seconds for you answer. So are you ready for What's the BUZZ? For those of you in the audience, feel free to put your answer and why in the chat as well. So here we go. If AI were a fruit, what would it be? 60 seconds on the clock. Go.

Pedro Berrocoso: 2:12

If it would be a fruit, what could it be? So it must be a fruit which is really multi use, right? And it's helping me to be brighter, potentially augmenting as well my intelligence, or at least giving me a productivity boost, right? And one thing which comes to mind for me, because I'm an avid gym goer since about a year now, is bananas, right? Because I think bananas offer you the ability to charge yourself very quickly with energy and at the same time elevate your game when you go to the gym, right? So I'd be thinking that AI could really be a good fruit, like a banana, which helps you really to get a quick boost of energy. Of energy at the same time give, you a boost as well in terms of the intelligence you can potentially then get at work.

Andreas Welsch: 2:55

Awesome. I love that. That's a fantastic answer. So while I'm traveling, that's the only question that I have about fruits. And bananas is definitely a unique answer. So that's perfect. So then let's maybe peel back the different layers about Generative AI in Procurement. And by the way, looking at the chat, so Tom from Texas, folks from Canada, from Portugal, North Carolina, Poland, New Zealand, New York. It's awesome. Thank you so much for being with us. Now, look, everybody's been talking about opportunities for Generative AI in Marketing and Sales for a while now, right? It's always about generating, summarizing, translating text. Marketing and Sales seem to be the frontrunners, the early opportunities, the early wins. But what about procurement? Why is nobody talking about procurement? Are there no opportunities there?

Pedro Berrocoso: 3:48

Is anyone talking about procurement? I think we're all constantly talking about procurement because we're very passionate about procurement. And by the way, it's not as simple as you may think, right? And this is a lot of people have this kind of myth in their minds that doing procurement activities is relatively straightforward. And just thinking about the opportunity within the space of procurement, some analysts are actually projecting 20 billion to be unlocked by 2027. These are very big numbers, so let's not get too much derailed about these big numbers. But there are hands on opportunities within the space of procurement. Due to the fact that we have complex processes, we do have a lot of data. We do have an ecosystem of stakeholders and suppliers. who all want to be served in the best way possible. And just thinking about a CEO survey, which I saw not too long ago from PwC, procurement still remains to be one of the processes or one of the areas where there's still a lot of work to do. And there's an expectation that challenges need to be solved. So thinking about Generative AI in the context of procurement opens up an opportunity for a lot of possible efficiency drivers and as well, productivity to be to be harnessed in that sense. And I could think about Generative AI within procurement in four different buckets, right? And let's peel off that banana now by looking through these four buckets. which potentially are offering opportunities within the space of procurement. The first one is really a bucket which deals more with personal productivity. And I think we've all, and I'm guessing everyone in this audience as well, and please say no in the chat if you haven't used the solutions like Gemini or ChatGPT and maybe as well the Copilot of Microsoft to help yourself with productivity, right? And basically with that, having an ability as a category manager in procurement to do better responses to your suppliers, build conversations or let's say communication templates, build as well or translate as well text, which is for us non English speakers not always easy to understand from a sentiment perspective or rightly convey back to our suppliers with the use of some of these Generative AI solutions which are already in the market. So bucket number one is productivity hacking, right? And that is quite broadly already in use. I was reading about 75 percent of given teams are already avid users of Generative AI with this type of solutions, right? The second topic is a bit more classical, and this deals with productivity or business efficiency gains, right? Here we do have the situation that even within procurement, there is still a lot of productivity to be gained out of automating processes, but where Generative AI really excels, it's is a natural language processing or data classification or what you just mentioned before, content generation or potentially coding, which is maybe not exactly where procurement folks will spend their time. But just coming back to business efficiencies one of the classical examples is classification of data. And so thinking about that as well in the context of a buyer, they may have a lot of information which is coming out of their spent classification cube, right? That spent classification cube data needs to be contrasted potentially with some market intelligence information coming from your Bloombergs, potentially from your external market intelligence supplier, right? And with that, making sense out of this data could be as well an automation effect, which you could drive as well with this, with the help of Generative AI itself. Then we do have insights generation, right? Which is bucket number three, I would say. And that is where out of the, data, you can actually extract insights, which can help you understand better. the information which you have already pre stored somewhere, so that could be information coming out of your SAP system, which you can then contrast with your supply and demand systems as well to see if the forecasting is actually sufficiently covered with supply which you have under contract or there's gaps where you could potentially require for a go to market activity in order to get further capacity under contract itself, right? So getting out these insights which alert you about facts where you have an under coverage or let's say an overexposure or excessive potential for inventories could really be helpful. And this is where I see the third bucket of use cases. within the Generative AI space space really playing a role. And the fourth one is about user experience, right? And I think we've all been talking in the procurement space about having detrimental user experiences, and I'm pretty sure if you're a solution provider who was listening, your solution is probably not that one, right? But there's many others, right? And this is really a critical area where I've just reflecting a little bit, a bit on my history of work within the source to face space. We've all been suffering a lot. We couldn't do much. We all knew it, but now with Generative AI we have a capability, which is rebuilding a user layer on top of many different solutions, potentially orchestrated through a business enterprise orchestration solution with a data model underpinning it. Where you could really drive a better experience for users by interacting with the Generative AI solution in a dialogue, right? So this is bucket number four, where I would see as well potential opportunities. And I think you said before, why is no one talking about procurement? I'm not really sure who that is, right? But I would be thinking that this is an area where there is a lot of possibilities to unlock. And there is in my in my perspective as well, real use cases, which are already taking shape.

Andreas Welsch: 9:13

That's awesome. Thank you so much for sharing. I really like how you bucketed into those four groups. And for those of you that might've joined a little later, you really want to stay on. There were already a few good nuggets in the last two, three minutes here so I can't wait for more information that you're going to share with us. Now these four buckets provide plenty of opportunity. And I think you make a fair point that we need to elevate procurement to the same level as Sales and Marketing. When we talk about opportunities for Generative AI, because they're clearly there. Now, one of the key questions that I always get from the audience is, Hey, can your guests share a tangible example of how does it actually work? How have they made it work? How have their clients made it work? And so I'm wondering if you have one that you can share where one of your clients is using Generative AI in procurement and, but maybe some of the challenges were and how they've overcome them.

Pedro Berrocoso: 10:10

Yeah I can think of quite a few cases. I'm picking one case, which I worked on last year in detail with one of my clients from the pharmaceutical space, right? So in an area which is quite regulated and complicated and where classical solutions like RPA are just not going to work because you need to have a lot of data. Different solution capabilities really used in order to extract information properly and then make sense out of it, right? And so the case which I could think of describing here is a case in the space of supplier quality, right? And my client had this big issue that a lot of their teams team members, actually, within the space of supplier quality, they were spending a lot of time reviewing detailed audit reports from their suppliers, right? These audit reports were coming from contract manufacturers, right? These contract manufacturers, they were obviously selling products to, to, to the company I was dealing with. But obviously, as with any production process, there are defects on the way as well, which get identified and need to be analyzed and and actually assessed. So what was happening there is that the supplier quality analysts, they were spending roughly two to three hours summarizing back the details of the audit reports, which we received back from the supplier. And then we're actually caught in a ping pong of conflict resolution and kind of question resolution and, questioning of what the supplier was bringing back because the notion of what was in there wasn't pretty clear. So what we did there is actually propose propose a Generative AI model. which was going to help us ingest these audit reports. There were about 2000 a year, each of them 100 to 120 pages long, which then was analyzed by the Generative AI solution and was actually digested, was classified into the specific template sections, which we had prepared. But then out of that was compiling back a summary report, which would then help actually the supplier quality analyst to see very quickly what was the issue at hand. What was the root cause which they had identified and what methods were used? But then as well, what was the proposed action plan? And actually as well, what was the effect which was taken out of the AI action plan as well. So all of this information was then packaged nicely by the Generative AI solution brought back to the supplier quality analyst for review. So this was a human in the loop approach, which I think for most of the Generative AI use case, I'd say is still a recommended approach to go for, right? A check on really making sure that what you get back makes sense is roughly complete, because you can't really go through the 200 pages, but you can get a sense out of that and then bring that back into your system for recording so that you have proven evidence for your auditors then afterwards for them to see that you've actually done it taken taken well you have taken preventive action or corrective actions in order for it not to reoccur. So this was one of the specific cases which I worked on last year. And to be honest, one of the big challenges there at the very beginning was to really have sufficient data proportioned in the good quality for the model to be able to be trained on the particularities of the quality domain and as well the kind of language which was actually being used within the context of this work, right? So this was one of the challenges. The second challenge was then to really make sure that the quality analysts were properly trained as well to understand and screen the results coming back and without being able then as well to satisfy questions which were coming from auditors or questions which were coming from the line managers about resolution actions being taken. So really building out that template and train it is going to be really important as well, right? So these were just two of the aspects which we encountered. As part of the implementation of this particular solution. There's probably a lot of other learnings, right? But these were two factors which were really crucial.

Andreas Welsch: 14:06

That's awesome. And I think, especially putting that into perspective. If I heard you right, you said 2000 audit documents per year, right? So break that down to what, 250 business days, give or take

Pedro Berrocoso: 14:23

Right.

Andreas Welsch: 14:24

So that's somewhere between seven, eight, nine audits a day. That sounds like it's pretty significant, right? If you can accelerate this, if you can use Generative AI to do some of the legwork for you, so you don't have to read, summarize, analyze the information.

Pedro Berrocoso: 14:39

Yeah. And I think one aspect as well, which is crucial, I'd say is that your supplier as well, accepts that this is the way you're going to be actually scrutinizing as well. Some of their work, you're still going to be interacting at a human level, right? It's really important that you have human to human conversations about quality issues. So I don't think you can really just take away the human and have an autonomous kind of activity taking place here. But I think it's it's as well a recognition that with Generative AI you can have measurable impact and at the same time you can prevent then as well having product impacts as well down the line from a procurement point of view.

Andreas Welsch: 15:11

I love where you're going with having a human in the loop and not having autonomous systems yet, is what I'm hearing. But I'm curious with all that talk about, Hey the next wave of Generative AI will be AI agents and they will maybe negotiate on your behalf with your supplier, with your customer. How realistic is that? Are we there yet? When do you think we will be there? What are you seeing in the space when it comes to more autonomy, more AI agents making decisions on your company's behalf?

Pedro Berrocoso: 15:46

And this is an interesting one, right? Because it's getting buzzy, as we see, right? It's one of these new things on the horizon, which a lot of people are starting to talk about. And there's even in the audience, I just spotted Pedro Martins, for instance, right? He's actually a fanatic about AI agents, and he knows everything about it, right? But This is a field which is interesting to dissect as well from the perspective of procurement because talking about AI as a kind of autonomous negotiation capability is interesting, but it is in a nutshell something which is I think it's an evolution, but is still quite complicated. And just briefly thinking about what is currently already there, there are already solutions which are capable to provide you with autonomous negotiation capabilities of a low complexity, right? So this is really, important, right? So they are providing you with bots which can, on your behalf, contact suppliers, they can execute a script in terms of activities they need to go through, they can ask for a price, they can bring that price back, they can maybe do some comparisons, right? But after that, what they still will need to do, I'd be hoping, is that they come back with a recommendation forwarding you, back to a category manager, back to a buyer in order for it to be validated and then finally confirmed. There are obviously as well models which are fully autonomous, but they're usually following a decision tree model, right? They're quite simple in that sense and is what you currently encounter in the market. With maybe three or four providers really being quite adamant about it being the future, right? And then there's obviously the future potential area, right? This is where you now get into the space of multitasking AI agents, which in my opinion will need to be connected to an ecosystem of solutions. They need to be part of and orchestrate the platform. They need to be part as well of a knowledge graph. They need as well to connect to business applications in ways that they can really serve as microservice for you to then take actions, for instance, on negotiation activities as well. And this is where the direction is now going, right? You have companies talking about building future autonomous negotiation bots, if you wish, which can really then take take care of complex negotiations, which can maybe reason as well, which is not quite yet where we are, right? And then potentially as well take decisions on your behalf quite in a automated way, right? So in a machine buying way, as Gartner was putting it just very recently, I think this was the content of my post today, right? 20 percent of all of the revenue by 2030 is actually forecasted to come from machine buying, right? But for that to really take place, there are some hurdles to overcome. And I don't think we're quite yet there to unleash that beast without human interventions, completely into an autonomous way.

Andreas Welsch: 18:34

I think that's a great point, especially the part about human intervention or human in loop to review, to approve, and just thinking about how large organizations work and the type of change management, the type of. Concerns the type of risks. Also if something goes off the rails I could see that there's a lot of enablement, education, building trust, winning trust needed before leaders get comfortable with having agents act on their behalf or negotiation.

Pedro Berrocoso: 19:05

And I think, you're mentioning a very good point, which is trust, right? And I think trust is probably one of the topics which drives most of the adoption, right? So you need to trust the results of a solution for it to be something you want to use not just one time But you want to use multiple times, right? So from that perspective, trust is really one of these hurdles not hurdles which this is one of the topics you need to really get right in order for you then to be able to move forward with these let's say solutions which are almost autonomous in itself, right? The other thing which I think is quite important when we talk about negotiations, and it just triggered a thought in my mind, is that you do have as well some level of not just reasoning, but moral as well, right? Because if we talk about negotiations on behalf of humans, there is as well this notion that there needs as well to be fairness. And this as well, ethical considerations, which as well need to flow into the models themselves so that they're actually not just taking negotiations on the wild run, but they're taking them as a human would be actually doing in a fair way.

Andreas Welsch: 20:06

I think that's, another interesting point that I'm curious about how this will play out, right? Will, agents in a sense fight to the knife? Or fight to death to get the best outcome for you, to negotiate until they get the best price for you, and what's the expense or how do you build in safeguards that does not happen or your maybe your purchase order bought or sales order or auto bought that if you need 20 pieces that it really orders 20 pieces on your behalf and not the with an extra zero, 200.

Pedro Berrocoso: 20:40

And I think I was reading I was reading a report from a research piece which was done probably a few months ago. It was called the Negotiation Arena. So they were pitching large language models against each other giving it, giving them three models of negotiations, right? And one thing which was interesting coming back from that particular research was that the use of tactics such as cunning and insulting and pressuring was actually really leading to better results and this is just telling you how critical it is to make sure that if we unleash autonomous activities that we have human oversight and we really ensure that they're sound and safe and I'm not going to create some reputational damage potentially down the line, right?

Andreas Welsch: 21:22

That's right, yeah that, too, yeah. Now I'm sure there are a number of good ways and safeguards to build into systems, to replace variables or data with actual data from your system in your prompts, in your outputs and in these kinds of things. But I think it's an area that definitely needs a good amount of scrutiny and high quality work to make sure that things stay within the guardrails of what you expect as a procurement professional. Maybe that's a good segue to the next part, which then to me is, there are four big pillars, four big opportunities that you mentioned in the beginning. How Generative AI can, add value. There's certainly a trend towards more automation that's going on; we're it fully at the point where it's all driven by agents and that's for a good reason, so people can get used to more automation, more autonomous decision making. But I'm wondering as a leader in a procurement function, procurement organization, how can you prepare for more Generative AI, more autonomy, more, again, summarization, generation, translation type things? What do you need to do to bring your teams along on that journey?

Pedro Berrocoso: 22:38

Yeah, and this is a crucial aspect of getting let's say the adoption rate actually increasing and at the same time, the literacy levels of your organization up and running. And you, if we're thinking about procurement, there's one speciality before we then go into the details of getting your team ready, which is procurement is this one place which gets exposed. In the future a lot of Generative AI solutions, because there are customers pitching with solutions which include Generative AI. So having that literacy level is not just a skilling activity for adoption of own tools. It's as well ensuring that you stay up to date and fresh with all of what you get proposed as well by external vendors, right? And without being able to discern whether or not the solutions truly have Generative AI capabilities or they potentially need to be scrutinized a little bit more because they don't quite offer what the customers are actually telling you, or the suppliers are actually telling you. And just thinking about the activities which could help with fostering uptake and as well literacy, right? I think the simplest one is to bring everyone into one room and just explore and play, right? So this is something which we don't see many organizations doing, right? Just take an emerging technology. Think about what it actually could be providing. Do a conference room pilot exercise, right? Get everyone into a room and then just think about the opportunities which this offers and do a small pilot with that, potentially supported by an expert, which you have trained as well, right? So this is one aspect to really lose, let's say the scare, which a lot of people have from new technologies and to truly understand through the play, which you do with the tool, what are the capabilities you could do, and that could be as simple as giving out. Licenses or let's say free use of GPT solutions to a certain set of of team, players, which could then act as a champion moving forward as well. So that's one of the activities I was thinking about, and I've seen as well within the space of automation working. The, second topic is and this is usually something you do if you're connecting, let's say the vision of your company to AI or to Generative AI as a big player. for your business objectives, right? And that is formenting or capacitating people with an AI academy, which will help people to go through a structured learning path, which will help them actually to gain the necessary skills for them to not just be aware of what is out there, but potentially as well get hands on practice. And then get as well the capabilities which they need in order then to help others within your own teams, right? So an AI literacy program is something which I see as well taking place in some of the companies. One of my last clients was having this as a very broad banded program, and it actually yielded really good results. And one of my experts who was working very closely with me on the discovery program for generative was actually a champion which was so innovative that it really sparked around him a lot of curiosity for all this and it was driving a lot of good conversations then as well within the teams you know, reducing as well the level of let's say yeah maybe scare or apprehension for new technologies themselves, right?

Andreas Welsch: 25:39

That's so great to hear. I think those are three really tangible examples and especially the part about AI literacy and what you mentioned that You can be pretty sure that your suppliers are going to use Generative AI when they pitch to you. I think that's a really important insight and aspect to be aware of. Now, we're coming close to the end of the show, and I was wondering if you can summarize the key three takeaways for our audience today.

Pedro Berrocoso: 26:03

Yeah. So in my perspective, the three key takeaways are that Generative AI really has a place within procurement. So that's point number one. It does have, gives you the capability to enable productivity insights, but there's potentially better user experience. Then the second point which I would like people to take away is that you need to be choosy of where you apply Generative AI. So it needs to fit with the purpose or let's say the pain points which you're addressing. So from that perspective choose wisely your use cases so that you can then as well promote trust and acceptance and adoption of the solutions which you then undertake. Be very cognizant as well about the fact that data quality plays a very strong role as well. And the third takeaway is to get started now, right? So there's no need for hesitation. There is really a catch up to do if you haven't yet started the journey to learn about Generative AI and if you need some help. Here I am, I can as well help you maybe to get that first step going, but I just wanted to really make sure that you understand that for a procurement function having some capabilities which incorporate AI or Generative AI as a, basic skill is really crucial already for the reason I was mentioning to you earlier, which is you're going to be anyhow exposed to Generative AI solutions as you discuss with your suppliers innovations, right?

Andreas Welsch: 27:21

I really think this brings it home really nicely. Three key takeaways. Now, Pedro, I think it was an awesome session. I really enjoyed hearing from you and learning from you all the different pieces and nuggets of gold that you dropped over the last roughly 30 minutes. I think there's a lot of excellent information there. So thank you so much for joining me and joining us today and for sharing your expertise with us.

Pedro Berrocoso: 27:45

\Thank you very much. It's been a pleasure.