Andreas Welsch: 0:21

Today, we'll talk about supercharging your business processes with collaborative AI agents. And who better to talk about it than someone who's actively working on that. Bernhard Ritz. Hey Bernhard, thank you so much for joining.

Bernhard Ritz: 0:33

Hello Andreas, thanks for having me on the show.

Andreas Welsch: 0:35

Awesome. Hey, why don't you tell our audience a little bit about yourself, who you are and what you do?

Bernhard Ritz: 0:39

Sure. I'm the CEO and founder of Ainzel, which is an enterprise AI platform that adds virtual employees, AI agents to businesses. I worked for 22 years for SAP. A couple of years in Germany, later here in the US. And then I joined an SAP partner to build up their North America business. And around 18 months ago, I started Ainzel, so I started my own company.

Andreas Welsch: 1:04

That's awesome. I'm really looking forward to our conversation today. You've shown me Ainzel a couple of weeks ago, and I was so excited to see these collaborative agents and what it actually means. Looking forward to our conversation. And also don't forget to pick up the AI Leadership Handbook on AILeadershipHandbook. com. So you can learn how you can successfully implement AI in your business. Because it's not just all about tech. With all of that out of the way, What do you say? Should we play a little game to kick things off?

Bernhard Ritz: 1:35

Okay.

Andreas Welsch: 1:36

Wonderful. So hang on. This one is called In Your Own Words. And when I hit the buzzer, the wheels will start spinning. When they stop, you'll see a sentence and I'd like for 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 your answer. And for those of you who are watching us live, drop your answer in the chat and why too. So are you ready for What's the BUZZ?

Bernhard Ritz: 2:02

Let's go.

Andreas Welsch: 2:03

Okay, here we go. If AI were a movie, what would it be? 60 seconds on the clock.

Bernhard Ritz: 2:10

Movie, that's an easy one. It's Inside Out. You probably know the Disney movie, where these little figures are thinking about you, your different emotions and so on. So that's a great parallel thing to, AI agents. If we had the point where we have them reasoning and think, so all these little different aspects of your life together, collaborating, so perfect comparison to AI agents.

Andreas Welsch: 2:41

I love that. That's wonderful. Definitely on message and theme for the show. let's jump right into it, right? You already mentioned agents working together, but maybe even before we talk about them collaborating, what does it even mean to bring agents into a business process? I think agents have been the hot topic this summer. But what does it actually mean in concrete terms when you do that?

Bernhard Ritz: 3:11

The way I look at this is, and a lot of people ask me and say, okay, AI agents, there's a lot of technology involved. And I tell them, step back, don't look at the technology, look at what they do for the business, these AI agents. And I always compare it with virtual employees, which is scary for some people. Some people say, Oh no, they're just augmenting, they're not real employees and so on. But step by step AI agents working towards this idea of. being part of the team, being a member. Now there are these little virtual helpers that are built on generative AI. They started with very simple tasks can you improve this email? And then it went to, can you write this email? Can you run this email campaign? Can you manage my email inbox for me? So step by step these little helpers got better and step by step we're integrating them deeper into our business processes. As I just described we use them to augment what we are doing and now they are starting to take over single activities, single steps. They're very knowledgeable, they are trained in certain domains at an expert level. They are fast, they respond with information in seconds that would take us minutes and hours to compile. So very helpful, affordable, knowledgeable trained little helpers. And this is actually how the name ANZL came along. I thought, how can you name these little helpers? And in Germany, there is something called Mainzelmaennchen, which is a German TV show. And I tried to find a domain name that fits to Mainzelmaennchen, these little helpers, and I came up with Ainzl. And later recognized, boop, there is AI at the beginning of it. Yeah.

Andreas Welsch: 4:58

I love that analogy. I've been wondering, too. Now, when you introduce more of this autonomy, into your business process. I'm sure that there's some challenges that you will introduce with that as well, right? I think in business, it's already tough enough if you have a team of human workers and employees, getting them to communicate, getting them to collaborate and agree on terminology and what is the goal and how do we break this down while still benefiting from everybody's individual experience and background. How do you see this evolving in business when we introduce now. AI agents as a software component that can do some of those little more complex tasks than just if then else at this time.

Bernhard Ritz: 5:43

You brought up an interesting point and this is language. I think the beauty of large language models and the underlying vector databases also, they bring a lot of flexibility. To things that AI agents can react to. If you think about traditional applications, right? You have databases and they have strict fields and you need to provide the information in the exact format required so that it can handle it. With AI there's ontologies, there's vector databases that do similarity searches, things like that. So you can have a very flexible way of entering information and the AI agent is still able to, handle it. So I think that's a great advantage. You said autonomy, obviously that's the big point. The more the AI agents take over in terms of functionality and, parts of the business processes, the more autonomy they will get to do things independent. And this is where also the risk is, where the oversight needs to kick in. About hallucinations, about bias, about privacy, security, compliance, I said they are virtual employees. And if you play that model, then you see virtual employees, they have an NDA, they have an employee contract, they need to follow code of business conduct. So for the AI agents, we need to design them the same way. And I think this is also the difference from enterprise AI platform, which takes that very serious in comparison if you feed information into a large language model and it's working with you, but this oversight component that you expect in an enterprise platform is probably not there. Information goes out there, information is shared that shouldn't be there. So enterprise platform dealing with these AI agents and the collaboration between the agents, is the go to solution in this case.

Andreas Welsch: 7:39

That's, awesome that you mentioned this because I think a lot of times that part is, underestimated or maybe not even covered. So I was thinking about that a little more the other week after our conversation and I realized, for example, in a lot of organizations, HR is actually absent in these discussions, right? It's technologists defining what should these new agents, these new digital workers look like and how should they behave? And what are the policies we want to need them to abide by? So I think there's another opportunity for technology leaders to bring in. HR experts and say what do we need our AI agents, to abide by how do we need to ground them in what documents is there a single source of truth, ideally, like there's for employees, or is it okay if every department defines it somewhat similarly, but has the autonomy. I think there's a lot more, to cover there. Also on the human to human collaboration with your HR team, as you're defining that. But what are you seeing? What do these agents actually bring to processes? How does that work if they work in a collaborative setting? How can I envision that?

Bernhard Ritz: 8:55

I think the simplest comparison in AI terms is these agents generate something like a chain of thought. In a traditional home environment where you have a ChatGPT, you ask something, you get a response, it has a memory that follows what you're doing. But here it's like this multi agent systems. You have a bunch of agents trained in different, in this case, business roles, somebody who's a compliant agent, a finance analyst, an industry specialist, you name it and they start to figure out certain topics and answer questions. So instead of one prompt that gives you an answer, You run a full, call it a conversation, a discussion between these agents. They are contributing to the conversation. They are reacting to each other's answers. So this guy said this. Hey, the finance analyst said this. Hey, entrepreneur, what do you think about this? Yeah, and so you run a discussion. You run a very complex chain of thoughts from different perspectives. Design based on the role, and some of these agents are trained with internal information or external information. So if you have somebody who is trained on your own information, they bring perspective of the company. Stuff based on customer material, or let's say you're a pharmaceutical company and you have 20 years of information in clinical trials, you convert this in a chatbot, you bring him into the conversation and suddenly you're bringing that knowledge into a broader conversation with a compliance officer, with an entrepreneur, with a financial specialist. So the idea is you can put, that's my philosophy, people often say, oh, is it is AI here to make things cheaper? I say it's a mix. It's more affordable, definitely, but it's also you can put more efforts into each task. And this is exactly this chain of thought. So imagine every question that you answer, every step that you're doing, you do a little workshop around it. Let's figure this out, right? Let's have a one hour conversation as a group how we solve this. How can we customize this to this specific customer so it makes a lot of sense to them? Let's run this chain of thought. Let's have a conversation from different perspectives. I think you get the picture that I'm drawing, right? It's a, little mind dimension, these little angels that are figuring out stuff. And that's also something that a lot of people say reasoning, can AI reason? Single prompt reasoning is getting much better. No question about that. But if you run this chain of thought and they have some guardrails around which direction they are going up, what are the key questions they should answer? Instructions that they're following, reasoning why they do a specific task. That gives them a lot of guidance around how the team of agents then generates responses.

Andreas Welsch: 11:42

Now, I think that the part that you mentioned around accomplishing more in, in the same amount of time or having a more in depth discussion and evaluation of of options, I think that's a key aspect that I haven't seen a lot of people talk about in, in that sense. It's not just about how can you become more efficient, meaning how can you reduce the mundane things, but what can you accomplish in the same amount of time now that we can scale it and we can have all of these virtual experts. come together and have that discussion, which would us, or which would take us an hour, two hours, half a day, right? Great.

Bernhard Ritz: 12:23

I go back to what I said before, if you look at this model of virtual employees I developed a strategy framework for AI together with William Faye, and we went in and said, how would things change? How would your business processes change? If you could put 10x the effort into what you're doing. Imagine you have 10 times the resources to do something. How would it change? And this goes to some stuff that I've also seen from you. You you have to reimagine your business processes. If you can customize. Things much more than as of today, if you can put much more effort into it, the result is, different.

Andreas Welsch: 13:01

Yeah, absolutely. And I see Josh has put a comment in the chat. We're going to see a need for leaders to manage two different workforces, humans and AI agents. I think that's spot on, right? I think in, in many cases, As leaders, we need to be prepared to also now guide agents and give them feedback. And also think more critically again when we're presented with a proposal, whether our team members have used AI to generate that. And again, we don't know how they prompted it or how what the instructions were for, agents to create something, but. If it's on us to make a decision and say, should we go left? Should we go right? With these options, right? We need to think a lot more critical about that as well, which I believe is getting more important, but curious what you're seeing.

Bernhard Ritz: 13:58

There's an interesting aspect that you brought up, right? This is this oversight of what goes into a problem. Then do we understand why the system is answering the way it's answering? And I think multi agent systems have an interesting advantage. You're not just seeing the result of, here's the answer, it's 42. It's more like you can follow that conversation between the agents. Ah, this is what they have argued about. This is what one agent asked the other agent, and then if you run some monitoring on top of this, and you say is this compliant? Can I see some bias in these questions and answers? Then you have much more You have much better transparency of how a decision is made and how we came to a certain point instead of just responding with the 42.

Andreas Welsch: 14:40

That's a great point. And I think also comparing that to spending an hour or two in a room behind closed doors and coming out with an answer, you also don't know that the exact conversation flows, but here you can actually audit it or take a look.

Bernhard Ritz: 14:56

It's a good point. Looking at Josh's question we need to manage two workforces. I think a good start is if we say, okay, let's apply the same standards that we have for humans to the AI agents, as I said, right? If we have a, code of business conduct, we don't wanna see anything in these conversations that doesn't need be, code of business conduct, things like that everything that goes on. So the human standards is a good starting point, and then we need additional measures for oversight on top.

Andreas Welsch: 15:26

Great point. Yeah. I think that'll become only more important as more and more businesses are exploring AI agents and how to deploy them and do that in a way that it is compliant. We've seen that before with machine learning where algorithms have a different optimization function, basically, and optimize for that one outcome, but it can have adversarial effects and negative side effects to what you actually want to do. So to your point, grounding them in. Here is the binding document that you need to abide by and then leave your guardrails. I think that's only getting more and more important. Now, I'm curious, when you use systems that have multiple agents collaborating, you can see The conversation flow, basically. What did one say? What did the other say? How did they arrive at this decision? What's really left for humans then to do in terms of decision? And where do we still need people in that process?

Bernhard Ritz: 16:28

There's probably a short term answer and there's a long term answer, right? You remember 12, 12 months ago, people said the humans are the creatives and AI agents are not. I guess we are now over that point where we see a lot of creativity in AI agents and how they bring together topics that are typically not together and the new outcome is quite creative. I see functions or job roles that are easier to handle by AI agents. So you're probably not a software developer anymore, but you are a software architect and you're orchestrating, but at the same time we see that more and more these AI agents climb up the ladder to more complex tasks, more complex roles. Yesterday they coded, now they're architecting solutions. Tomorrow, who knows? Do I see a limit where I say AI will never be able to X, Y, Z? Actually not. I don't see it. It's more a question of how do we deal with these capabilities. And this is, I'm going back a little bit to AI strategy, where I say this gives you new capabilities, you have to rethink the way you do business, you have to rethink and reimagine your business processes, as we saw with this HR question, you have to rethink what are the skills required in your company in this new way. And you have to rethink the market as well, because it's not just you who has these new capabilities, all the other participants in the market, your competitors, your customers, your suppliers, you name it, have it, have the same capabilities. Could they suddenly substitute your products or services? And so we can do this in house with AI. We don't need company expert. We don't burn out to do this. Same for you. You probably asking the same question. Can I do stuff in house that I haven't done? So that goes to the strategic idea. It's we see the technology. Technology has evolved significantly over the last two years and now more and more the business aspect shines.

Andreas Welsch: 18:29

Now, that makes me wonder if you have your agents, your multi agent systems in your own company. Your customers, your partners, your vendors, they do the same thing. Where's this going? Do you envision a future where Agents of different companies then collaborate, much like we would collaborate with our suppliers, with our partners, with our customers and say, what products do you need? When can we actually build or ship them? What material do we need to source? Again, collaborate with with the partner or with the supplier. Where's this going and where, does it stop or where does it end if it is?

Bernhard Ritz: 19:11

You're already drawing the next generation, Andreas. Quite interesting. So it's a marketplace where agents from different companies start to collaborate. You have a little workshop going on with your customers and suppliers. Interesting thought. I haven't thought about it, but why not? We're not there yet. So we're still in the process of company internal agents that are collaborating. But what you can do today is, you can put agents into the role of customers and try to get test certain things you could put an AI agent in the role of a competitor. And see how they react to certain activities that you're doing. Again it's, crazy how fast the whole thing develops. I like the idea of intercompany agent collaboration. I haven't seen it. Here's a business opportunity for somebody on the call.

Andreas Welsch: 20:01

That's true. Now, I obviously see it as, and you're most likely seeing this too, all of the large vendors in the market have announced that they're Some sort of agent strategy, agent features, whether it's Salesforce, or Oracle, or SAP, or Microsoft, and many others. But I also see them building their capabilities very tightly. into their applications, right? It's all about creating, on one hand, more value, on the other hand, more lock in, if you will. But what I haven't seen a lot of is interagent, or not interagent operability, but basically interoperability between these different solutions. Because in a business process and in a company, you most likely don't just have one vendor wall as much as Mentors would love that to be true. So I think there's another opportunity when it comes to integration, if you have an HR workflow and there, there are some budget questions. You can see the difference between, say, Workday to SAP. What does that integration look like? But I think there are also advantages, right? If you're not locked into any of these verticals, if you do have an open platform. What are you seeing there?

Bernhard Ritz: 21:15

I think a lot of companies are in a position where they try to find out What's a good starting point for us with AI? How do we get started, right? And when you look at your business system, your salesforce, your ServiceNow, your SAP, your Oracle, you name it, yeah these vendors are adding these agent capabilities to their solutions. So they will handle part of the processes or the processes within these systems. What I also saw is that they are now open to connecting to other systems. Salesforce agent connecting to an SAP system and vice versa. So there's some level of openness, but not to the point, probably how a third party could, do this. When I look at Ansel, obviously I say, yeah, we are connecting to multiple systems and you have this third party that can independently orchestrate it, the capabilities that I see from the different vendors. Everybody goes into the same direction of this agent and what we discussed, how they have evolved and how they will evolve. It's just a question of what's the orchestration framework for all of these agents and how flexible and how open is it to the different vendors. And again, it will be an evolution. The vendors, the current vendors have a big advantage because their processes and their solutions are already implemented in companies. Why wouldn't you start with just adding AI capabilities that these vendors come? But then when it comes to the interoperability between the systems, that will be an interesting situation how this works over there.

Andreas Welsch: 22:47

Now, let's bring this back to one of the earlier points that you made, that ideally we start with viewing agents like a human worker, right? When it comes to policies and guidelines. Now imagine Again, your HR department and your finance department and your sales department all saying, here's the scope of what I do. If you want to talk to me again, you need to fill out a form or you need some kind of orchestration or integration. So I know what I need to do with the information that you give to me, or even worse saying, All I can do is, this little box, don't come to me for anything else, right? To your point, I think that's the next evolution that we see and that we will need to see. We it's fine to have silos when it comes to business systems, but for business and the process that goes horizontal, it doesn't really matter if it's vendor one or two or three. From a business point of view. So I think there's another big opportunity. And like Milind is posting in the chat here, right? Perhaps we need to develop standards or open systems that allow intercompany agent collaboration and even interdepartmental collaboration, I would say. Now, we've, covered a lot of ground in, in, in the last 25 minutes. I'm curious where are you seeing things go? What's your recommendation for leaders looking to learn more about AI agents and starting on this journey?

Bernhard Ritz: 24:15

I think we touched some of these points. So step back and look at this as a business capability and what does it do to your business, and most companies have experience with. Little projects, little pet project from the IT department or some other departments, how to use AI. I haven't seen a lot of companies who really stepped back and said, okay, how do we reimagine our business? How does this influence our position in the market? So there's a bigger picture to this. And especially when you have this picture of these virtual employees and you can reimagine, then that's a good metaphor to do that. When it comes to the technology, a lot of companies have. Started with internal chatbots, where they have trained agents on their own data, their proprietary data. That's the starting point, that's probably the pre version of an agent, yeah? Look at existing AI agent frameworks, and take a look if there's something, like an instant platform, that helps you to orchestrate this, agent communication. Other than that, we're still in early stages, we're just at the phase where, We are adding AI to the business processes. Companies need to look how they handle this, oversight, this compliance. I think topics like hallucinations, they're starting to go away because there's more and more done in terms of, okay, give me the sources. Please validate this with sources. So hallucination, in my opinion, is something that goes away in the next 12 months where we have chain of thoughts and all kinds of processes that, that help us to overcome this. But when it comes to. Topics like, the bias and giving more autonomy to the AI agents and taking over bigger parts of the business processes, I think this will be some of the challenges and things we have to look at when we go step by step into this AI ready world, AI enabled world.

Andreas Welsch: 26:10

No, that, that sounds exciting. I can't wait for hallucinations to go away because if we starting to put LLMs and Gen AI into so many critical places and having the certainty that does what it says and says what it does is really important. Now we're getting close to the end of the show, and I was wondering if you can summarize the key three takeaways for our audience today.

Bernhard Ritz: 26:32

Take a business look at AI. Yeah. Think about re imagining your business and your market situation is one thing. Learn to work with AI agent frameworks, because they're the evolution of large language models. It's not about individual promptings anymore. But it's trained agents in certain domains who are really world class experts in what they are doing and a whole bunch of them collaborating together to figure out stuff. Companies have to get their feedback in learning this new way of doing business. Okay, there's a whole, I take an individual contributor and I put this virtual team around him and now he's a manager of a virtual team and has suddenly all this capability available to him. And the third one is, yeah, all of these. changes to, to let's say autonomy. How far do I go? How do I step by step unleash AI and do I even want to unleash it? How does a company first want to proceed with these capabilities in a responsible and ethical way? I think that these are other topics that should be considered.

Andreas Welsch: 27:38

Awesome. For sharing that and for summarizing. our discussion today. Folks, for those of you in the audience, if you would like to learn more about AI agents, at least on a high level recently released two courses on LinkedIn learning that help you get started with AI agents and put in the basics of what it is all about and where the opportunities and the challenges are. And I thank you so much for joining us and for sharing your expertise with us. It's been great having this conversation with you and learning from you as well, where you see things be today and in the future.

Bernhard Ritz: 28:09

Thanks for having me on the show.