Seeing the Whole Chessboard

Susan Evangeline Bagh joins Richard Lowe (The Writing King) on Leaders and Their Stories for a wide-ranging conversation about strategy, technology, and the mind of a polymath.

A global strategy and technology executive with 25 years across banking, payments, and financial services, Susan explains how a person who sees the whole chessboard reads a company, why she thinks most of the AI boom is hype, and how to keep your own judgment sharp in a world built to think for you.

Susan Evangeline Bagh is a global strategy and technology executive who has led enterprise-scale transformation across financial services and technology, holds multiple patents, and describes herself as a polymath, someone who sees the big picture and connects the dots others miss.

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Full transcript of the interview follows.

Meet Susan Bagh

Richard: Hello, this is Richard Lowe, I’m the Writing King, and this is the Leaders and Their Stories podcast. I’m here today with Susan Evangeline Bagh, a global strategy and technology executive with 20 years leading enterprise-scale transformation across banking, payments, and financial services. She’s the person boards call when they have a vision and need someone to turn it into something that actually ships.

She works at the intersection of product, technology, and corporate strategy, translating things like AI and data infrastructure into competitive advantage. She holds multiple patents that she’s gained along the way. She describes herself as someone who can see the whole chessboard. Today, we’re going to trace how she learned it. Susan, welcome.

Susan Bagh: Thank you so much, Richard. I appreciate you having me here, and I look forward to our conversation.

Richard: We’re gonna have a great one. So, 20 years is a long arc. Why don’t you take me back to the beginning? Where did this start, and was the strategy always the plan, or did you back into it?

Two Paths in India

Susan: Well, it started 25 years ago, actually. So I have 25 years in financial services now, and started back in India, where I was born and raised. So I’m multicultural, multilingual, and multi-many other things. I’m a polymath as well. And I grew up in India, in a very strong Christian household. My parents are both Anglicans and Evangelicals, and I went to Catholic school, so a very global environment.

At the end of the Indian education system, there are two paths in your life. You either become an engineer, or you are a doctor, and the rest are all losers. That’s how they define education and career in India. And it’s very competitive. So I decided to choose the engineering path.

Susan: Right around 10th grade you get to choose your subjects. I chose mathematics, physics, and chemistry, and you’re supposed to give an entrance exam, and it’s highly competitive. Twelve hundred to one seat, and very few women make it through. I was one of them, in one of the schools, somewhere in the middle. I gained entry into engineering, and then you compete again for two semesters before you’re granted your choice of lane. Based on my performance, I was given electrical engineering. And luckily, my dad was also an electrical engineer, so I kind of followed his path, subtly.

From Engineering to IT

Susan: After graduation, I tried my hand at the same firm where my dad used to work, an electrical engineering firm, and I did not like it at all. I wasn’t cut out for it.

Richard: Right, I understand totally.

Susan: And it’s definitely not a good place for women in India. So I decided to go the tech, IT route. My goal was to come to the US. That was my sole goal then, to migrate to the US. I’d seen many friends and neighbors whose kids had made it here. I said, okay, let’s try this. And I got through. So I took the IT path, and since then it was just IT and technology. I started with a consulting firm on the financial services banking side, and gradually climbed the ladder, business analyst, business systems analyst, project manager, program manager, enterprise program manager, VP of strategy and planning, then into the office of the CTO, and here I am today.

With that consulting firm, I had the opportunity to consult in the Philippines, in Manila, which was a very large project. And it was right at the time of 9/11. One of the designers of the World Trade Center electrical fittings was one of our clients. I was on the 28th floor of the hotel when it happened.

Richard: So you were near the towers?

Susan: Oh no, I was in Manila, watching 9/11 from there. And one of our clients was the man who designed the electrical systems.

Richard: Gotcha. I watched the towers fall on TV, out in California. It was a bad day.

Susan: It was very scary. Even in Manila it was scary. They had some attacks right after in the Philippines. In hindsight, it seems much more frightening, but it was managed very well.

Richard: There’s a book called Touching History about the FAA side of 9/11. I tear up when I read it. The whole story of the airline side, they grounded every single plane, and they didn’t have the authority to do that. They just did it.

The Intersection of Three Worlds

Richard: Okay, so you said you work at the intersection of product, technology, and corporate strategy. How did you end up in all three?

Susan: There’s a pattern you’ll see in my entire history: I have a very eclectic background. And I did not choose it. It was a function of how the cards were dealt to me. When you’re in a consulting environment, they throw you into different programs. I was with American Express for a very long time as a consultant. They’d throw me into different projects, so I got to do a lot of work, as a business analyst, project manager, program manager, some product management, and then some strategy work in technology.

I was with them almost 13-plus years across India, the US, and the UK, and I managed around 300-plus projects and programs across different business units. Right after I graduated from Thunderbird, from the executive program, I met one of the leaders at Amex, and he became my sponsor. He started throwing me into high-end programs, top-10 global programs at the time. I spent my first 15 years on the execution side only, then moved into technology strategy, and corporate strategy evolved through it in the last seven or eight years.

Seeing the Whole Chessboard

Richard: Now you describe seeing the whole chessboard. When did you first realize you could see it when others couldn’t?

Susan: In hindsight, as a kid. I was a smart kid, so my parents put me in school early. They’d bring me books, and I would sit down and read the entire book, chapter one to the end. I was good at all subjects, so I had a holistic view of everything. I didn’t realize it then, but as I progressed I realized I do certain things really well and I’m not very good at extreme details. I can go into details if I need to, but it’s not my strength.

At American Express, I was leading all these programs back to back, probably eight business units in six years, very intense, very stressful. It took a toll on me later. People would ask, how did you do this? And I’d say, I have no idea, it just happened. I’m an expert generalist. I know 80% of almost everything, or I’ll figure it out. So I see the big picture.

Susan: After my Amex work, I went through my first dark night of the soul after my first gig with Wells Fargo in 2013. People were hunting me down, they wanted things from me. They thought I had some secret knowledge or tool or software. That’s when I started digging into it, and I came across the word polymath.

Discovering the Word Polymath

Richard: What does that mean?

Susan: A polymath is someone good at multiple subjects. Leonardo da Vinci was a polymath, because he was good at many things. And they’re whole-minded. Most people are whole-brained, but they use more of their left brain or their right brain. There are about 2% of people in the world who are whole-brained, and I’m one of them. So it all connects: why I don’t like going into details, why I see the big picture and connect all the dots. Day one, I can come into an area and figure out how everything connects. It’s by design, I guess.

Richard: I guess I’m a bit of a polymath too, now that you mention it. Look at my website, it’s got articles about AI all the way to photography. I’ve been a photographer, I’ve known celebrities, gone into writing, all kinds of stuff. And the details, I usually outsource, because I’m not interested in them unless it’s something really interesting.

Susan: I’m a big-picture person, a top-down person, so I like strategy, anything enterprise or ecosystem related. People would advise me to be an SME, a subject-matter expert in one area, and I’m not interested. There’s no fun doing the same thing over and over for your whole life. I find it really boring. And you can take a perspective from the financial world and apply it to the healthcare world. Everything is connected. The 2008 financial crisis wasn’t just about finance, it was across the globe. As a whole-picture person, I like to know all the connecting pieces and how they fit.

Richard picks up this thread in two pieces: What Is a Polymath? (And Why It Might Describe You) and the personal I Am a Polymath. What Does That Mean?

The AI Hype in Three Horizons

Richard: So you’re involved in lots of emerging tech. Is modern AI really changing the world, or is it mostly hype?

Susan: I wrote an article on the hype two years ago, and it’s kind of coming true. For me, AI is a technology, just like any other. There have been revolutionary technologies for decades. It’s not new. We went through the data cycle for a long time, DB2 databases, then business intelligence, then data lakes. AI has a couple of aspects. There’s GenAI, the ChatGPT side, which is mostly connecting text and coming up with something logical, and a lot of it doesn’t even make sense. For people who can’t make sense of it, it seems great. Then there’s the AI/ML level, the advanced AI, and that’s where the real innovation would be, but to reach there is a long journey.

More on this framework: The Three Horizons of AI: How to Tell Hype From Value.

Susan: A lot of the current hype is hype, because very few people understand what’s going on. I look at any new technology in three horizons. Horizon one is immediate, people just replicate what already exists. Horizon two is a little further out, new models, things that don’t quite exist yet. Horizon three is where the value is, the cutting edge, things that don’t exist today, new business models, new inventions. Most people right now are in horizon one. Everybody’s just recreating everything, here’s a way to write a document, here’s a way to pull text out of a PDF. People have been doing that for a long time.

The Energy and Infrastructure Reality

Susan: Across the infrastructure side, everybody’s jumped in, data centers, chips, but they’re not stepping back to think how this plays out at the ecosystem level. There’s a need for energy, and there will be an energy crisis when a technology consumes ten times more energy than a normal Google search. Energy comes from water, coal, or nuclear, so now we’re exploring nuclear, but nobody’s thinking about how to cut the cost down. They’re already creating data centers and energy capacity for, say, ten gigs’ worth. Tomorrow, technology will change, AI will evolve, and you’ll realize you only need one gig. You’ve built ten because of the hype. That’s a loss.

Richard: And going back to the infrastructure, one problem we have in the United States is not just energy but getting it from A to B. The transmission lines are old. You’ve got to create a nuclear plant, figure out where to put it, deal with the heat from the data centers. It’s 107 degrees here in Florida right now.

Susan: It’s global warming, for sure. I’m in Phoenix. This time of year it’s usually around 115. We had 115 one day last week. Today it’s 99, that’s pretty good. So this is exactly why I say you need a holistic view. You have to see the impact of all the different things, not just East Coast versus West Coast. The people worried about AI are usually in tech or finance. There’s a whole sector of people who don’t know anything about it or don’t care. The impact has to be assessed across the entire country and world. Most decisions right now are happening in a vacuum.

Why Transformations Fail

Richard: I’ve done several digital transformation projects, and they always need to start with people. If you start with technology, you’ve started from the wrong end. It’s people, processes, and technology.

Susan: And strategy.

Richard: And strategy. So what do you do with the people when you get rid of everyone moving stuff into an Excel spreadsheet? A lot of big companies decided, well, you just get rid of them. But that’s not the right solution. The right solution is to retrain and repurpose them. I think that’s the more ethical thing to do.

Susan: Not just ethical, it’s sustainable. You lay off a person who spent 20 years in risk management, they know the systems in and out, and then you build systems in AI that don’t know how it all connects. You use that functioning model as a base and evolve from there. In the corporate world, people make very short-sighted decisions. It’s all about now, how can I prove my budget, my ROI, my impact. They don’t care about the impact to the next business unit in the same organization. It’s blinkers-on thinking, incremental band-aids and patch-ups, and by the fifth year they realize it’s not what they expected, so they need another transformation to replace it.

Richard: One big company tried to transform their entire multi-billion-dollar company all at once, and it failed miserably.

Susan: 75% of transformations fail every year, according to McKinsey, and I think it’s much higher. It should be business transformation, top-down and purpose-driven, then it trickles down to digital. Not, I’m going to make all my systems bright and shiny and add AI to everything. AI alone is short-sighted, because today’s version of AI won’t be tomorrow’s. The key, like in finance, is diversification. You don’t put all your eggs in one basket, or one vendor. There could be cyber attacks, security gaps. Organizations that think in five- and ten-year horizons will be the successful ones.

Richard expands this into a full argument in Why You Don’t Put All Your Eggs in AI.

Richard: My backup strategy has three layers, three different backups, three different vendors. None of them are expensive, and if one fails I’ve got two more. Data is important. I have 980,000 photographs I’ve taken over my life, and it’s backed up a lot. I almost lost it once when a disk drive failed and I had to rebuild it by hand. Don’t want to do that ever again.

Susan: And storage evolves, too. Old hard drives become outdated, and you can’t connect them to modern laptops. How do you retrieve the data?

Richard: Backups saved me. I lost a disk recently, but I recovered it. It took a few days because it’s terabytes of data, but I got it back. I did not want to lose those photos again, ever. Or the thousands of videos I’ve taken.

The Pivot to Business

Richard: You said you’re navigating a shift right now, from technology to business. Tell me about that.

Susan: I’ve been trying that for a while. Since I graduated in 2008 from Thunderbird’s executive MBA program, I wanted to go to the business side. But the powers above me saw me benefiting in technology, so they kept me there. I’m good at both. I can see both sides, and I’m visionary, so I can create new business ideas. I’ve built business plans and strategies for organizations. Right now, I’ve done tech a lot, managed across the enterprise, and it’s passe to me. How much more can you do the same thing? It doesn’t excite me. I need something new to explore.

So I started exploring finance. I began stock trading a while ago, taught myself online. I’ve explored geopolitics as well. I think I’d make a good investor, some people have said that. I wanted to shift into corporate venture capital when I was at Wells Fargo, and they didn’t allow it. Now the universe seems to be pushing me toward investing. If I want to marry my past and my newfound passion, wealth management seems like an obvious growth area. There’s huge potential, and I understand the business, technology, and financial aspects.

Richard: You mentioned geopolitics. That’s one of my passions. I wrote a series of eight books on it, the Enemies of You series, at enemiesofyou.com. It’s a planned series of 20. There’s one called The Enshittification of America, that’s a real word, by the way. And The Emasculation of America, and Turn Off the TV, Get Off Your Ass, and Do Something, about how smartphones have made people not think as much. And two books that go hand in hand, The Birth of the Augmented Human, how AI can be good for you, and the opposing one, The Death of Thinking, about how AI undermines thinking when people use it to think for them instead of acting.

The Dumbest Generation

Susan: That’s very true. I think the next generation is becoming less competent. I like to call it the dumb, dumber, dumbest version. We’re creating the dumbest version of future generations. If they rely so much on AI and other tech, which may not last either, what are they going to do? We’re at a crossroads. Their thinking capacities have diminished drastically. People lack critical thinking, just basic critical thinking.

Richard: What is critical thinking? Most people don’t even know what it is. They just take whatever meme comes out on their phone and say, oh, that’s true. And it has no bearing in fact. That’s how so many weird things happen. People believe cranberry juice will solve their diabetes because they read it on the internet, then they buy it from the person who’s just trying to make money, because they don’t do any critical thinking.

Susan: That’s happening everywhere. Last year, because of my financial situation, I had to take a job at Home Depot. It was very eye-opening. I got to interact with all these kids under 20, and it’s mind-boggling how they think and process information. It’s amusing and shocking at the same time. It made my heart sink, because the future generation is getting dumber, and it’s not just here, it’s a global phenomenon.

AI Is a Tool, With Limits

Richard: My book The Death of Thinking is about that, and The Birth of the Augmented Human is about the other side, where if you use it right, your thinking improves. An example: if you use AI to write your book for you, that’s one path. If you use it as an assistant to help you write your book, that’s a different path. Better to get it to help you, like you’d hire a VA.

Susan: It’s a tool. I see it as a tool. It’s actually helped my thinking, it gives me impetus to think in directions I hadn’t considered. Earlier I’d Google and get ten sources and connect the dots myself. AI does that for you. But you have to use your common sense to analyze what it gives you. You can’t use everything blindly. I see it as a glorified Google search. And AI has a life cycle. It’s all based on data, first and foremost. The data has to be right, accurate, and have context. Without context, AI connects all the text and builds you a story, and that story could be wrong.

Susan: You have to keep feeding AI new data for it to improve. If you only have a limited source of data, AI stagnates after one or two iterations, and that’s when it starts hallucinating. If you see it hallucinating, you have to stop. And there’s another aspect: you don’t know how it’s processing information, or you have no control over it. We’re using AI in decision-making now, agentic AI, and I don’t know what decisions it’s making. I don’t want AI shopping for me. It happened the other day, I was on a home delivery app selecting items, and before I knew it, everything was in my cart and the order was placed, and I couldn’t modify it. That was scary. I didn’t even touch anything.

Richard: What’s interesting is I’ll tell AI, write this for me, and then ask, where did you lie in here? And it’ll say, this paragraph, I lied here and here. Then I say, fix all those lies. Where else did you lie? Where did you subtly lie? It’ll tell you. And it’s best to go to another model, if you did it in Claude, go to ChatGPT and say, fact-check this. Different brains. I tend to use Claude, I find it the best model for what I do.

Susan: I don’t use a lot of AI. It’s like technology, I don’t use a lot of my cell phone. I probably use less than 5% of my smartphone’s functionality, because I want to keep using my brain.

Richard: I use it all day long, for all kinds of stuff. But I use my brain too. I’m using it as an assistant, not as a take-me-over.

Consequential Thinking

Richard: Well, we’ve been going about 45 minutes. This has been a fun conversation. Any final words, and where can people find you?

Susan: People can find me on LinkedIn, linkedin.com/in/susanbagh. That’s the best way to reach me. My only final words are, we should use our critical thinking and consequential thinking. Most important, use consequential thinking and think through things holistically. Look at it from an integrated angle rather than just one piece, in every area of your life. If you take that integrated view, you’ll have a better view of things, and it will help your decision-making a lot.

More on this idea: Consequential Thinking: The Executive Skill Nobody Teaches.

Richard: There’s a rule I got from geopolitics called the rule of unintended consequences. If I make this decision, what could happen? That’s an important way to live, because you’ll have consequences you can’t see.

Susan: Infinite. And we live in a time of uncertainty, VUCA times. You won’t have the full picture or all the data points, but you’ll be well-informed enough to make a good decision. Looking at things from different angles always helps. Our current political and economic scenario reflects the short-term view we have. We ought to take a long-term view across the globe. If we had a 10-year plan for our country, we’d get much further, instead of changing strategy every five years with a new government.

Richard: Did you use a word there, VUCA?

Susan: VUCA. V for volatility, U for uncertainty, C for complexity, A for ambiguity.

Richard: I’ve heard that before. Okay, thank you. It’s been great having you on. Thank you for the interview.

Susan: Have a good rest of your day.

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