Edwin Miranda Podcast Transcript
Edwin Miranda joins host Brian Thomas on The Digital Executive Podcast.
Brian Thomas: Welcome to The Digital Executive. Today’s guest is Edwin Miranda. Edwin Miranda is a business strategist, entrepreneur, and transformational leader whose career has spanned advertising, communications, political strategy, consulting, technology, customer experience, and organizational innovation. Over the course of more than two decades, he has worked at the intersection of creativity, influence, business, government, and emerging technology, helping brands, campaigns, growth systems, and transformation initiatives across Puerto Rico, the United States, and Latin America.
That realization led to the creation of Konsultora, a post-legacy firm designed for the AI era, built around the belief that the future belongs to organizations capable of continuous evolution. konsultora integrates strategy, intelligent systems, customer experience, AI, automation, and adaptive operational frameworks to help businesses navigate rapid transformation and long-term growth Well, good afternoon, Edwin. Welcome to the show.
Edwin Miranda: Good afternoon, Brian, and good afternoon to all your listeners.
Brian Thomas: Awesome. Thank you, man. I appreciate that. You’re hailing out of the Miami, Florida area. I’m in Kansas City, so I appreciate you making the time, and let’s jump right into it here, Edwin. I wanna ask you your first question.
You founded Koio, and you built a career that has moved through advertising, political strategy, customer experience, and now AI transformation. What connects those worlds, and what ultimately convinced you that the traditional agency and consulting models needed to be reinvented?
Edwin Miranda: Thank you, Brian, for the question.
For me, what connects those worlds is competition and decision-making, right? Whether you’re either building a brand, running a political campaign or, or just running a company, you’re competing for attention, preference, trust, and action. The market moves, competitors move, customers change, so the advantage comes from understanding what’s changing, making better decisions faster, right?
And adapting, so you can be more competitive. That’s what fascinated me about AI because now intelligent system can now sit inside the workflow with us of the pro- of the whole process, analyze huge amounts of information, reason across it, and help us move much faster from signal to decision to action.
We are better and quicker throughout the whole process. That can also make the experience around a product or a company more informed, more connected, and more consistent. So it, it, it brings also a better customer experience when your customer is experiencing the relationship with your product or services.
On the other hand, there was a second realization with AI. AI wasn’t only changing how companies make decisions, it was changing the economics of advertising and consulting. If you think about it today, research that used to take days or weeks can happen in minutes. Media buying is increasingly becoming algorithmic, right?
Agents can probably do a better media plan than, than two or three media planners together with the information that they have and the knowledge of the platforms they are buying into. Content can be produced at enormous scales, sometimes in infinite scales. Reporting and dashboards can be automated.
Market intelligence, competitive analysis, trends, and even the first set of recommendations can increasingly be generated almost instantly. So if your business model in advertising and consulting, it was mainly based on selling hours to produce those outputs- The economics are under enormous pressure.
So agencies and consultants, they don’t disappear, but, but they need to create value. The way that they create value for a customer has to change. We, we have to move as industries, we have to move from selling execution to building capabilities, and that means helping companies build the systems, workflows, agents, data connections, governance, and decision-making capabilities that allow them to operate in a different way.
So it’s just rethinking of the whole business model
Brian Thomas: Thank you. You certainly saw some promise with AI, and that’s what really, piqued your curiosity. You saw that this could really accelerate some things in the customer experience space. There’s, there was a lot of promise around capability, as you mentioned.
The customer experience, right? You talked about being informed, connected, consistent with that customer, and the great thing about AI that you also talked about is that media buying. Today it’s heavily algorithmic. Content can be scaled exponentially, real-time reporting, predictive analytics. There’s so much that AI has really helped businesses accelerate their go-to-market or, or their marketing, whatever that is.
It builds in a lot of productivity. So thank you. And Edwin, one of your recent signals is that enterprise AI agents are now getting identities and audit trails, an owner, a permission, data feed, a log file, et cetera, et cetera. And you frame the real answers as accountability, not smarter chat. Why is giving an agent a job ID such an important shift, and what breaks when companies deploy autonomous agents without that accountability layer?
Edwin Miranda: That’s a great question, Brian, because we have moved from generative AI, which was the first experience that customers and business got with artificial intelligence, to agentic AI. So let me try to explain that. The moment that AI moved from just answering questions to taking actions, accountability now becomes essential, right?
There’s more risk in the process. So because a chatbot giving you an answer is one thing, but an agent that can send an email, change a campaign, talk to a customer, approve something, arrive at a decision, or access company data is very, very different, right? So at that point, the company needs to know who owns the A…
just like with any employee, right? The company needs to own who owns that agent, what information can it see, what it is allowed to do, what needs human approval, and, and can we go back later and see exactly what he did and, and why he did it, right? So it’s, it’s a whole learning process. That’s why identity with agents specifically, the identity, the permissions, and an audit trail are, are so important.
I think we’re going to start treating agents less like software features, right, and more like digital workers i-inside the company. They’re gonna have a role, they’re gonna have access, and of course, just like with any employees, they’re gonna have limits. And, and there is a big difference between automation and autonomy, right?
Automation follows instructions. Autonomy can look at a situation and decide what to do next, and that will be the next shift. So the more autonomy you give a, an AI agent, the more accountability you need around it. Because, autonomy without accountability, is not transformation, right?
It’s it, it, it might be a risk. So those guardrails have to be clear from the beginning. What’s agentic AI doing within your organizations? What are the permissions that that agent is going to have? What limits in terms of judgment are you gonna give that agent? And how is it gonna interact with supervision from the human on top of, of, of the whole process?
Because the human judgment, of course, is gonna sit at the center of everything. That’s not changing anytime soon.
Brian Thomas: Thank you. Appreciate the insights. Guardrails is kind of the word of the, the week or the word of the year now. But you talked about AI, how AI has basically moved from that just general chatbot to being an agent now, and agents are doing more advanced tasks, making some decisions.
So that audit trail is so important, as you mentioned. Agents are truly digital workers inside the company so that there’s more autonomy there, but that means more accountability, and I thought that was important that you talked about that. So I appreciate what your insights here. And Edwin, you believe that while automation is permanently changing execution, human creativity, strategic thinking, and judgment are becoming more valuable than ever.
That’s a nuanced position in a moment of a lot of fear about AI replacing people. Where exactly do you draw the line between what should be automated and what must stay human, and how do you counsel leaders wrestling with that balance?
Edwin Miranda: I think th- this is one of my most favorite parts because there… I think there’s a lot of misunderstanding of that, that topic specifically.
I don’t divide it by jobs, right? I divide it by the type of decisions that are being made. If something is repetitive, involves a lot of data, follows a clear process or, or require watching thousands of things at the same times- Probably machines are gonna do more and more of that work, and they could probably do a better, a, a better job at, at doing that work, right?
And AI is not only automating execution, it is beginning to automate coordination too. Research, reporting, monitoring, handoffs, scheduling, and, and some routine decisions. But when those things becomes easier, something else becomes more valuable, right? And just like I said in the, the previous answer, and that’s human judgment.
Becomes more valuable than ever. Human judgment is just knowing what to do when there is, there isn’t one perfect answer, what the system is telling you. It’s understanding context taste, empathy, trust, ethics, negotiations, customer relationships, leadership, creativity. That’s something an AI agent will never give you.
An AI will never give humanity, right? Sometimes the data can be right, but the decision can still be wrong. So I don’t think the goal is to remove humans from the company. The goal is to remove as much friction as possible around people, so people can spend more of their time on the decisions that really need human judgment.
I think there– that where the opportunity is, is that as execution becomes easier, if you wanna call it that, judgment becomes and has to become more valuable. And I, and I think in, in this discussion between AI and human and replacing capabilities, et cetera, I, I think in my opinion, th-there’s another way to look at it.
AI can replace some capabilities, but it can also expand our capabilities and our capacities, right? If you think about it, back in the 1800s, machines didn’t make agriculture disappear, they changed how much a person could produce. The same thing with manufacturing. Automation didn’t make manufacturing disappear.
It changed what factories and workers could do. And I think AI is gonna do something similar to many industries today, and it will probably create entirely new ones. But the real opportunity for companies is, is to free up human capacity, so we can spend more time imagining better products, better services, better companies, better organizations.
So I think it’s about expanding capacity and doing more. It’s, it’s not just about replacing capacity, cost-cutting, and losing job. It’s about evolving, expanding, and continue to increase those capabilities in a very competitive environment. Because if you don’t expand your capabilities with, with the benefits that AI is giving you, your competitor is gonna do that.
So you might be thinking on doing less on cutting costs, but your competitor might be thinking on, “Well, now I can serve more customers. I can add more services. I can de-develop an expertise on a specific vertical, or maybe I can do more prototypes of products.” So it’s a key decision that, that companies today have to make, whether I wanna go, “Do I wanna expand my capabilities, or do I wanna just think short term and make decisions short term?”
But human judgment is still gonna be the most important factor on that process, and that human judgment is gonna, is gonna be what’s gonna expand our capabilities in government, in organizations, and in companies, and in all industries.
Brian Thomas: Thank you. I appreciate that. And I’m just highlight some things here, Edwin.
You talked about how today general tasks are being automated at scale now. Types of decisions that are being made today are increasingly becoming more autonomous. We are getting closer to that human decision, but as you talked about the importance, the goal here is not to remove humans because we truly need human judgment in this process, and judgment is becoming more valuable, and it’ll increasingly become more valuable over time as we start to leverage these agents.
But again, it’s not about replacing humans, but evolving and expanding that human role and that machine role so we can serve more customers at scale, but also provide that higher quality customer experience. I appreciate that. Edwin, the last question of the day, your work centers on helping companies build AI-native operational models, intelligent workflows, and real-time decision-making capabilities for the future economy.
As you look out five, 10 years, and that may be too long to look ahead here, but what does a truly AI-native organization actually look like day to day, and what will separate the companies that thrive in this transformation from those that get left behind?
Edwin Miranda: Thank you for that question, Brian. I don’t think an, an AI native company is just simply a company with more AI tools, right?
I think it’s a company with less distance between a signal, a decision, and a, and an action, right? It’s a smarter and a quicker organization. Something happens with a customer or, or in the market, the company sees that signal. AI helps understand what it means. It brings together the right information. It helps decide what should happen next.
So it’s, it’s an, a more informed organization. Sometimes it recommends an action to a person, and sometimes if it has permission, it can take action on itself. I think that’s where we’re moving. You see what happened, you learn from it, and, and use that information in the next decisions. So you create a simple loop, right?
Signal, decision, action, and learning on a continuous loop. And I’ll, and I’ll talk about that in a minute. So your, your CRMs are not gonna disappear. That’s gonna still be a tool in the future. Your financial systems are not gonna disappear or, or for that sake, even software. Your marketing platforms don’t disappear.
What changes is that you begin to have a, an intelligent layer across those systems that helps connects them and coordinate what happens between them. And, and peoples are gonna spend less time moving information from one place to another, and more time handling exceptions, making important decisions, and using that judgment.
At, at Konsultora, we, we like to call that, that destination, that future that we’re moving to business singularity. So that’s the moment where technology, AI agents, real-time data, and human judgment are working together as one intelligent system. So– and I don’t think the winners will, will simply be the companies that bought more AI first or that execute AI faster.
I think the winners will be the companies that can learn, decide, and adapt faster, that the world around them is, is going to change. So if you can become change yourself, if you can anticipate market moves, then at the end of the day, all these models or this technology, everything might be changing. But if, if you’re ad-adapting to the technology and to the right model towards the future, and you’re building that workflow, and you’re building that singularity, that’s gonna make you a more competitive business going forward.
Brian Thomas: Awesome. Thank you so much. And again, just highlighting, Edwin, you talked about this AI-native company. Obviously, a smarter, efficient, it’s a quicker company. An AI native helps keep a step ahead of the customer, assisting humans, providing feedback to improve processes and the customer experience, and you highlighted a few here, providing that real-time assistance, decision, and action.
The big takeaway for me was that term business singularity. I thought that was pretty cool. Humans and machines working together as an intelligent team. Very good insights today, and I appreciate that. Edwin, it was such a pleasure having you on today, and I look forward to speaking with you real soon.
Edwin Miranda: Thank you, Brian, and you have a, a great day, and, and thank you for listening, and thank you for your audience.
Brian Thomas: Bye for now.
Edwin Miranda Podcast Transcript. Listen to the audio on the guest’s Podcast Page.
