Scaling & Driving Generative AI Adoption for Enterprises with Guillermo Miranda

Thomas Kohler:
Today’s guest, Guillermo Miranda.

Exactly. And I think if this is solved, really helpful, but let’s say salary data, right? HR has access to salary data. If companies also do performance ratings, HR has access to performance. Now, when technology comes in and technology is accessing the income data and the performance data of people, individuals, it should be safe and secure. And I think it also needs to be very carefully trained because I think this has really big, big impact on a person’s life. But if the technology is just playing around and making decisions on that, this can be dangerous. Right? So how do you think about the sensitivity of data and what do you think needs to be accomplished there? And where should it maybe stop and where do you need to be very careful about certain things you do with it?

Guillermo Miranda:
Yes. So again, we call it copilot because it’s an extension to get things better. We don’t call it pilot. The pilot is the human being that is making the decision. This is additional insights to have more context to do better decisions. The whole topic of data and the sensitivity and the process of security is something that needs to be embedded in how you are designing the future. And yes, like in HR, that is performance. There is salary data that needs to be treated carefully.

There is personal data in a health environment about people. There is tax data with the tax agencies. There is a lot of sensitivity about data. Protocols are important to be as part of a framework of AI governance that companies should have clarity. We, as an AI company, generative AI platform, we have good protocols. We already have a framework of how to manage security, how to manage AI. What is the purpose of aih that simple? Clarity is important. The purpose of generative AI in the platform of Atlas Copilot is to enhance the powers of human beings.

It’s not to replace human beings, it’s to enhance the power. And that guidance already helps you to package everything else in data. The data belongs to the client, and that’s a principle. From that, everything starts. We are not using data to train agents. We are not using data to do things without full anonymization. And so if you have clarity in the framework, then you can execute. And here is where it is important, how the characters that are creating the future have this clarity of values and clarity of purpose.

And each company should have, like we have clarity on why you are using genetic AI, how you are managing the data and the risk. You go to our website and you will find those Q and A’s there very clearly and guiding our day to day. When we onboard a new employee. This is part of our process. When we discuss with clients, we discuss how to do it. A very clear example, we have a client that came to us and said, hey, I want to eliminate all my HR partners, help me to do it. And we very kindly said, look, our platform is not a platform to replace, it’s a platform to be a copilot. Let me explain you. If what you want is to eliminate roles plainly and upfront, then you will need to do something else. We are not here to help that purpose.

Thomas Kohler:
We talked about AI and his perspective on the future, on the past, and what he’s currently building with Atlas Copilot. And he saw big, large enterprise, global companies and more than 30 years in HR and has a lot of curiosity and hunger still to just build something new and is now doing a startup. So really interesting insights, perspectives and tune in.

Thomas Kohler:
Hi Guillermo, looking forward to this conversation about AI. But first, talk us through what you did in the past and why you founded Atlas Copilot.

Guillermo Miranda:
Absolutely. Guten Morgen, good morning, good afternoon, wherever you are in the world. So let me start with a confession. I am a lawyer. I started my professional life as a lawyer. Then I did an MBA. And then I have a corporate career, a very typical corporate career with IBM and then with Boeing.

I was a CHRO in the digital space. I was a chief learning officer. I was a chief talent officer. And then I decided that I want to be on the other side of the equation, on the side of the equation that you create the innovation. And this is how in the summer of 22, we did a change. And I became more of an advisor of unicorns and a co founder very recently. And the fascination is with the product and how a product, a technology, can help you to change your life, can help you to accomplish things that you were not able to accomplish before. And that’s what we are trying to do here with Atlas Copilot is to put the power of generative AI in the hands of HR professionals, to elevate their access to business acumen, to ideas, to insights that you don’t need to pay somebody else to get you, that you don’t need to spend hours researching in Internet is everything in front of you. And that’s what we are trying to accomplish.

Thomas Kohler:
How can we imagine that in a practical example? What would be a typical use case?

Guillermo Miranda:
Oh, absolutely. Look, the typical use case is the tool that I always wanted as an HR professional. So I have to do a presentation to the management board in the next week, and I have to present our plans to career acceleration for top talent. And we have a program, an initiative that we want to sharp, but we also have to present to the management board some of the market situation to position why you are doing it this way instead of that other way, etcetera. So I will use Atlas to give me context on the market, to research from experts that already did it, other practitioners. So it’s not a theoretical idea, is other thro that already did it. And then I will use also at last to help me to refine the. Usually when you go to a presentation, you have an executive aspect and then Atlas will help you to prepare the executive aspect and I will feel much more prepared, yes.

Thomas Kohler:
Yes, I think that’s a smart way to support and enable, because I think there are several principles out there that are really powerful. For instance, structuring information in a certain way that it’s really simple to understand. And if you have a certain pool of information or data and you have different stakeholders, you need to display and frame the information in a different way that it’s relevant for them and in their language. Right. And I think if a technology is trained in that way, it can get super excellent in it and also maybe fast in just preparing a draft and then maybe a human even needs to adapt and modify it. Right. That you also have the personal touch and that everybody, everything is really fine tuned. But what I saw is that a lot of, first of all, HR professionals, for instance, they’re not able to structure thoughts in a way that the stakeholder or a senior manager or an executive understands it from their perspective.

That’s, I think what I saw often now, 90% are not able to do that, or not even aware of the impact of doing it. And then that’s the problem that you never have the chance to influence. And I think that’s so important to train this skill. And the second is when you are able to have this skill, the question is, how do you gather the right information that people believe you, what you try to push in terms of a business case, for instance. Right. Because I think it’s also about timing and it’s about receiving the message at the right time with the right context. Right. And therefore, I would be super interesting to understand how do you make sure to get the right data and where do you get the data from?

Guillermo Miranda:
Yes. Look, you are absolutely right on how to position the ideas and how to present it to have a proper business conversation. And this is part of the challenge that we are trying to help and support from Atlas. The first thing is because the content of Atlas is made of all the materials, webcasts, podcasts, part of the content comes from HR leaders, which is one of the founders of Atlas. You will have realized examples of other experts in HR, other Chros, chief talent officer, learning officer that are explaining their own ideas. So you will have firsthand insights on how to present and how to explain. And then we also have experts in the platform like Dave Ulrich, like Chester Elton, like Marshall Goldsmith that have mastered the auto of presenting and putting in context an idea. And you will have that already curated for you and then several open source resources that provide market insights.

So we have a process of curation of the data that then is part of the enrichment of the LLM and how the users can access things first, that are not in the Internet. These are things that are already curated for them. Second, you feel at home because this is a platform that is made by HR professionals. For HR professionals with fantastic product like Chat GPT is just the open world. Chat GPT is made forever. So yeah, it’s good. It helps me, I use it as well. But it does not give me this feeling that I am at home with other HR professionals.

And that’s very important, is part of the user experience and more importantly, it’s part of how the content is tailored to the task. So it’s not a lot of generic content that can sound smart. It’s very well curated content that can help you to prepare and to be ready to execute in the context of the people equation in a business environment.

Thomas Kohler:
In case you like my show, please subscribe. I would really appreciate it.

I also see a video on your website that there is a live call of people from different companies and also a live summary. And I find this really interesting because I was just at a sales executive event in Dina where there was said that it would be interesting to have a product that sits live with you in the call and knows the product really well when doing a sales call or a qualification call. And then for instance, when you need certain information about the product, let’s say you’re selling a technical product, right, which is a bit complex and has different variations. And then your customer has or potential customer has specific questions and you are just the person that really gets the deal, has the relationship, but not maybe the indeterminate product knowledge you would have, maybe a copilot that really knows the product inside out. And then you just ask live in the call, hey, what is the pricing under that circumstances? What would be different options? And then the technology is calculating that instead of, for instance, a sales engineer, for instance, right. So this was a use case where they said this would be helpful and this would be interesting to have. And I see that you are doing already something in that direction. So what do you think your product can be used for in live calls? Because the summaries look really nice.

Guillermo Miranda:
Yes. So look, the idea is that you get these extended powers by technology in the flow of work the way that you are doing your day to day. So in the very specific case that you mentioned, part of the value proposition of Atlas Copilot is to have participate in all these webcasts and podcasts that we do with HR leaders. And there is going to be a streaming, with a genai agent in the streaming. So it can help you to summarize, it can help you to give you hints of what is going on in the call as well. But as important as that, the agent can surface in the environment of teams, in the environment of slack. So if you are having a conversation with a business leader, you are an HR person having a conversation with a business leader, talking about an initiative in teams on Slack. You can call Atlas.

Atlas will read all the previous conversation and start giving you insights and says yes, based on this discussion that you have, let me show you some examples that in your Industry make sense and the other companies did. Or these are the two ideas that you need to decide or confront. Or this is a better example for this because it will be able to understand context. And that is very important in the. In technology, because it’s not just the assistant that spells back an answer. This is an agent that is able to understand context and that’s one of step forward. Technology will continue to evolve, but this is always important to be at the leading edge, experimenting there. And this is what we are doing with atlas.

Thomas Kohler:
And now I think I’m really interested in the personal story behind that, because you were in HR, in big corporates and in advising roles, but you just saw a lot over the past years, right? And what was the trigger of going down that route and now founding your own company for that.

Guillermo Miranda:
The trigger was curiosity. And the trigger was the aim to share with more people what you can help to accomplish. So, curiosity, in order to explore the limits of how you can reinvent the ways that you do. The people talks about the future of work like ideal, a concept. So the future of work is here. The future of work is already happening. And the way that you can use technology to accelerate your output, to improve your productivity is something that I’ve been always interested. I have the privilege to work for many years with a large company like IBM, where technology is the day to day.

IBM put technology to solve business problems, and that’s what I learned. And I have the privilege also to interact with several clients that gave me different point of views, etcetera. And then I worked with a big aerospace company where you have also the privilege to be in the day to date and to see how technology is reinventing a very large manufacturing environment. Engineering, manufacturing environment. So from those learnings is where I took the curiosity and the interest to share and the opportunity to be at the edge of how we are reinventing things is something that is priceless. And that’s what drives my energy and my effort to say, hey, let me show you how this can be done. Hey, let me share how this technology can help you in your day to day. Hey, let’s collaborate and work differently to reinvent the future. And that’s the big motivation behind, if.

Thomas Kohler:
You want, when you look at it long term, how many jobs will be created, how many jobs will be changed, and how many jobs will be eliminated? Do you have an idea about or an opinion about that?

Guillermo Miranda:
Yeah, there are very good studies that have been done with good basics. So there is a study by the World Economic Forum, there is a study by McKinsey, there is a study by Deloitte. And the numbers are in the millions. And the numbers are in the millions, both for reinvention, for new jobs and for jobs that are no longer going to be necessary in that context. But like any change that have been in history driving the way that we interact as a society, there is going to be transformation, and there is going to be transition. I think that what we need to understand is that every single person will need to learn how to interact more deeply with technology, and that’s on one side and a skill. And we have all learned how to use excel, how to use chats, how to use all these things we are learning. So AI is going to be an acceleration of those components.

And it’s not just for the professional worker, it’s also for the frontline worker, because all these things are coming in our mobiles are coming to our life in a day to day, are coming to the schools are coming to universities, one of the more legacy, archaic institutions are universities. Universities are going to be deeply transformed because this is not about transferring knowledge. This is about teaching how to use opportunities. And I think that’s an important component. So bottom line, we all need to learn how to work with technology. We all need to be open to what is the change that is coming. There is a very good study that I would love to share with everybody that attends the podcast from the Stanford University media lab and basically says the mindset is one of the most important things to embrace technology. You can be either a pilot or a passenger.

If you choose to be a pilot, you will have control of how you are recreating the future. If you choose to be a passenger, you are going to be a passive victim of what the driver is doing in your life. That’s very important in terms of mindset. Mindset makes the difference and that’s the way that we should face this transformation and this change in our society for good. This will create a lot of opportunities, but we need to be open mind to embrace those opportunities.

Thomas Kohler:
In case you have any feedback or anything you want to share with me, please send me an email on thomas@pplwise.com or hit me up on LinkedIn. And in case you really enjoy the show, please subscribe. I would really appreciate it.

Yes, and I see now, I totally agree with you. And I see now that a lot of companies are playing with it. They are testing, but they are not implementing. And I think this is also still down to, it’s quite complex still to use it in the right way, because I think just doing a prompt that gives you something valuable is not so easy. Right.

You need to really play around and you really need to understand how to prompt. So prompting itself, I guess, is something that is a skill and you can develop, of course. But I think once maybe the technology is that holistic that you don’t need to type something in somewhere and it’s more obvious around the context that the technology understands. You are currently, for instance, in the car, then you maybe should not prompt, right? But maybe you should just talk and the context that you’re in the car should already be there, and the context of why you are in the car should also be there. So you don’t need to give all this information. Hey, I’m in the car, and I’m now going from, I don’t know, Berlin to Munich, and this is what I want to do. And I have an appointment there. And now please help me figure out my schedule because there’s traffic time or so on. Right? It should be all there already. And I think once we are at that stage, it’s getting really powerful and really disruptive.

Guillermo Miranda:
Yes, the context is everything for questions. Context is everything for what you want to accomplish. As a lawyer, I can tell you from my experience that when you are working in cases, when you are working in contracts, context is extremely important to get the outcome that you are looking for. And technology can help us in different aspects of our life. The example that you described is a daily life example. And consumer brands like Apple and I am sure Samsung will come very rapidly with artificial intelligence integration in your phone, in your smartphone. That is going to be part of this context and will understand. Oh, I know because of your agenda where you are.

I know because of the gps that you already halfway. I know because of your meetings schedule that you need to arrive in less than 30 minutes. I know that the road is crowded here. So I start to reroute. I start to send an email and say, hey, I run in five minutes late. All these things that can create a hassle for us today because I am driving, I am trying to send an email that I have to drive, can be done and can be extensions of our daily life. The same way in a professional environment, you can have a lot of help from technology. If you are a frontline worker and you are in a construction site, there is a lot of stimulation, there is a lot of risk management that needs to happen and it can be provided with technology.

Same in an office. There is a lot of context where you are preparing an output and the interaction, not necessarily the prompt, not necessarily needs to be done in a so complex way because your base technology will already understand the context. So, yes, this is part of the future that we are all shaping together. And with Atlas, what we want is to have that future shape well tailored for HR professionals, made by HR professionals, and be able to elevate the profession. In many contexts, HR is understood as an administrative. You are the police to make the guidelines and you are not the business person. That helps to impact positive the clients. If you have the insights to do it, that will be better, faster and more accurate. And that’s the extension of power that we want to give to HR professionals.

Thomas Kohler:
Exactly. And I think if this is solved, really helpful, but let’s say salary data, right? HR has access to salary data. If companies also do performance ratings, HR has access to performance. Now, when technology comes in and technology is accessing the income data and the performance data of people, individuals, it should be safe and secure. And I think it also needs to be very carefully trained because I think this has really big, big impact on a person’s life. But if the technology is just playing around and making decisions on that, this can be dangerous. Right? How do you think about the sensitivity of data and what do you think needs to be accomplished there? And where should it maybe stop and where do you need to be very careful about certain things you do with it?

Guillermo Miranda:
Yes. So again, we call it copilot because it’s an extension to get things better. We don’t call it pilot. The pilot is the human being that is making the decisions. This is additional insights to have more context to do better decisions. And the whole topic of data and the sensitivity and the process of security is something that needs to be embedded in how you are designing the future. And yes, like in HR, that is performance. There is salary data that needs to be treat carefully.

There is personal data in a health environment about people. There is tax data with the tax agencies, there is a lot of sensitivity about data. And those protocols are important to be as part of a framework of AI governance that companies should have clarity. We, as an AIH company, generative AI platform, we have good protocols, we already have a framework of how to manage security, how to manage AI. What is the purpose of AI? That simple clarity is important. The purpose of generative AI in the platform of Atlas copilot is to enhance the powers of human beings, is not to replace human beings, is to enhance the power. And that guidance already helps you to package everything else in data. The data belongs to the client, and that’s a principle.

From that, everything starts. We are not using data to train agents. We are not using data to do things without full anonymization. So if you have clarity on the framework, then you can execute. And here is where it is important, how the characters that are creating the future have this clarity of values and clarity of purpose. And each company should have, like we have clarity on why you are using generative AI, how you are managing the data and the risk. You go to our website and you will find those Q and A’s there very clearly and guiding our day to day when we onboard a new employee. This is part of our process.

When we discuss with clients, we discuss how to do it. A very clear example. We have a client that came to us and said, hey, I want to eliminate all my HR partners, help me to do it. And we very kindly said, look, our platform is not a platform to replace, it’s a platform to be a copilot. Let me explain you. If what you want is to eliminate roles plainly and up front, then you will need to do something else. We are not here to help that purpose.

Thomas Kohler:
I totally understand. What do you wish for the future? When you look into AI, do you have maybe a prediction?

Guillermo Miranda:
Yeah, the prediction is that we need to be eyes wide open into the future. I think that this important attitude and mindset, what I see is a way that can be complicated and convoluted if we are just acting by instinct and by reaction in a way that can be much better organized with a better impact on society. Here I am not talking just about business output of more profit for companies. I am talking about the positive impact on society. And that requires a very intentional purpose and a very intentional way to operate. That’s what I see as the future. I trust human curiosity. I trust human ingenuity.

This is why we are playing at the leading edge of technology, because we have an intention and we have very clear values.

Thomas Kohler:
Thanks. Thank you so much for participating. I really enjoyed it and have a nice weekend.

Guillermo Miranda:
Same for you. Great weekend. And in the US it’s 4 July weekend next week. So happy holidays for the US based people.