What Still Matters — A Final Synthesis

Twelve episodes. One question. What still matters when everything is automated? In this series finale, Dr. Marilyn Carroll synthesizes the through-line that ran beneath every conversation — governance, accountability, workforce, education, and executive leadership — and arrives at three constants: accountability must be held by a named human, trust cannot be systematized, and meaning is made, not generated. BCG's research found that 70% of AI transformation success is due to people and processes. Only 10% is the algorithm. The human architecture was always the constraint. AI just made it impossible to ignore. This episode is a challenge, a reflection, and a charge. For every leader in all 19 countries and 400+ cities, this show reaches — this one's for you.

What still matters…when everything is automated?

That’s the question we’ve been building toward this entire series.

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Transcript

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Hi, and welcome back to Two Doctors in the Twist. This is our final episode in this series, and I want to thank you all for joining me through these 12 episodes. I want to thank Dr. Jamie for continuing to do great work and to for always being there for me to talk to about different things. However, she's been out this quarter on a special assignment for work and have not been able to join us. She will be joining us in the following quarter for our next series for our summer series of Two Doctors in a Twist. And I want to thank all the many followers that continue to follow us. Those who are joined have joined in and doing things with us. Thank you, thank you, thank you. So let's get started on this final episode, okay? So in this final episode, I want to talk about what still matters. It's been 12 episodes, and one question, what still matters when everything is automated in the series finale. I want to synthesize the through line that ran beneath every conversation. Governance, accountability, workforce, education, and executive leadership, and arrives in three constraints. Accountability must be held by a named human. Trust cannot be systemized, and meaning is made, not generated. BCG's research found that seventy percent of AI transformation success is people and process. Only 10% is the algorithm. Yeah. So you may be asking, really, Marilyn? Why is that so? Well, the human architecture was always the constraint. AI just made it impossible to ignore. So this episode, I challenge you to reflect and to change or charge. For every leader in all 19 countries and 400 plus cities, this show reaches, this one's real. What still matters when everything is automated? That's the question we've been building toward this entire series. We talked about it. We've talked about governance, accountability, authority, leadership, learning, and workforce transformation throughout this process. But none of those stand alone, guys. They're all part of something deeper. And that deeper, because this is not just a conversation about AI. It's a conversation about what leadership becomes when intelligence is no longer scarce. So across every episode, you know, across every study, across every organization I've worked with, the same patterns keep showing up. Not trends, not tactics, not constraints. Things that do not change, no matter how advanced the system becomes. And if you missed everything else in the series, these are the three things I want you to walk away with. Constraint number one is accountability. Accountability must be held by a named human, not a system, not a committee, not the organization, a person. We saw this in governance, we saw it in the authority migration, we saw it in the decision accountability, and it aligns with global consensus. Huh? Well, the World Economic Forum, regulators, and governance bodies all reinforce this. AI can influence decisions, but responsibility remains human. This is not negotiable. This is not negotiable because accountability is not a function, okay? It's a condition of trust. So that's constraint number one. So constraint number two is trust, okay? Trust cannot be systemized, meaning you can't uh put trust into a system and leave it alone. It cannot be automated, it cannot be scaled through technology. Trust is built through consistency, presence, and follow-through. It requires someone with something at stake. Okay, that's why even as systems improve, trust matrix continue to decline. Because trust is not about capability, guys, it's about relationships. And relationships require what people. Machines are not in relationship with one another, okay? Let's stop it. I don't care how great you make them, how robotic you make them, they're not in a relationship with one another. Now, here's constraint number three. Meaning. Meaning, okay? Meaning must be created, not generated. AI can produce information, yeah, it can produce information, but it cannot. It cannot interpret reality in a human context, it cannot align people around purpose, and it can't carry the narrative through the uncertainty. That requires leadership. Because when environments shift, people don't need people don't just need answers, guides. Okay? They need someone to help them understand what this means for us, and that question cannot be outsourced. I'm sorry it can't be outsourced. So let's pause for a moment while I break this down to you. Before we go to hopefully, you can see as I break it down to connection here. A lot of times when companies are going through change, people are so confused because nobody explained the things to them, or they weren't listening if they were explained. A lot of times, employees were asked for will break this down, give us the narrative here. And the company said, well, I can only give you so much because we are, especially if it's a big company that have investors, stockholders, things of that nature. You have to answer to those people first before you answer to your team. And plus, if you're on the stock, you can't let all secrets get out or things get out that you're building, but you got to know what you can say, when you can say it, and how you need to say it. All right. And we may even have to go back to um etiquette. I have some etiquette books around here somewhere. But we may have to go back to etiquette to help you understand what's really going on here. We we are back in time. I find myself with these 360s and uh coaching, executive coaching, that somebody has to explain things to people to the level where they can understand it. And sometimes some things have to be outsourced. But when you're talking about the company and the processes and who can okay and not okay something, that can be outsourced. Somebody has to take accountability for that, okay? Now let's connect this back to everything we discussed. AI is accelerating decisions, information, and execution, but it is also exposing. It is also exposing weak governance, unclear accountability, fragile trust, and missing meaning. Yeah, that's true. AI has just highlighted these things for us that have been happening for many, many moons at our companies, in many companies, is exposing it. I think this last two years, we've seen more companies, more big organizations close down than we've ever seen before. The information was already there. A lot of these companies were borrowing money. Uh, they were no different than other people borrowing money and didn't have the means to pay back. Uh, a lot of retail organizations would be in the red, but they borrow more money to get them out the red, thinking they were gonna improve. But if you have a good credit rating, the companies were blowing you more and more and more. Well, the companies, the banks stopped that mess. They said, no, no, no, we can't keep doing that. We got to find a way to get our money back because the economy is changing, things are changing. If you don't pay back, it's not gonna happen. We're gonna be due all these people, we which we owe money to. We already had the 2008 collapse. Uh, we've had a lot of things that have happened. We we the reason we had stocks is because we didn't have proper governance. So as we go through, we see that we keep coming up to these things where we don't have proper governance. Well, people are saying, not just with this AI thing, you're gonna have some governance here. Whether you like it or not, we need governance because if you don't, it's gonna be a price to pay. And that's why I think countries like the uh EU has taken a step back and said, you know what? We're gonna give you some guardrails and let you know that these things are going to have to take place before we believe in AI completely and these systems that you're putting in place. And this is exactly what we defined earlier as the AI exposure effect. AI reveals what systems were previously previously able to hide. So the goal is not to keep up with AI, the goal is to build systems that can hold what AI reveals. So this brings us to the leadership decision at this moment. And so let's make it this personal. A AI leader is in a moment of uncertainty. AI provides the analysis, data is available, options are clear, but the decision still feels heavy because it affects people, careers. Sound familiar? Outcomes, and the leader has a choice. Do they defer or step forward and say, This decision is mine, I made this decision, and I will stand behind it. That moment right there, that's leadership. Because you stood with the decision that was made. You didn't hide behind, you didn't throw it off, you didn't transfer it to somebody else. And that's the one thing AI can't replace. You can't say I made that decision because AI has no stake in the game. It was built using data. Data that you still have to know something about in order to trust the data that's there and to trust the outcomes or say whether the outcomes are correct or not. So we didn't we hadn't changed anything other than we have a speedier way of doing something. We can put things in and get them done. We went from Lotus to Excel, from spreadsheet to Lotus to Excel, to now AI can do all of that. We've gone from writing on paper to uh putting it in word perfect to word to now AI. Okay. We've gone from what were the PowerPoints over whatever the case was, all these tools we use to operate and run our business. AIS just scaled all of that so we could put it in the system, okay? Just like we went from the phone in our home, and people complain about a lot of stuff right now, but we went from the phone in our home, the dial-up phone, from the well, we started with the operator, Ma Bell, uh, Alexander Graham Bell and Ma Bell, as we used to call it, or I heard it was called. Went from calling that operator and transferring that call to the call automatically goes through and rings to our home. We had phone lines in our home. We went from the phone lines that were dial up to the key punch that we punched the numbers, and that was better. We went from that to cell phones that we could use anywhere, anytime, any means. And those cell phones also changed to our computer in our hand. Yes, these little gadgets in our hand that we carry around, where we once had everything from uh we had cambers in our hand, we had boombox, we we now have Pandora, we had the maps, and now we have the maps on the comp on the phone. We had TV that we had to watch in our home to we have TV streaming services on our phone now. We went from we started something called social media where we could communicate with some everybody through Word documents or texts, little messages we could send across the universe. We didn't have to pick up the phone anymore, hold that thing to our ear while we talked, right? We went from the calculator to from paper to the calculator. We've gone from weather that we have to watch TV for to weather that we can get on our phone. We went from making reservations, having to call up somebody to make a reservation for us for an airline, bus, or whatever, to using our phone to get that done. We have everything on this phone. We can throw a party with our phone from music we get from whatever we uh subscribe to. We went from a DJ in person to having a DJ on our phone. We've gone from all those things and we didn't complain. So now we have this AI and we want to complain. We've been using too much stuff in the universe. We've been using the water systems and all. We've been using all of that, but in order to get this done, we are going to have to up the game and use more water and things of that nature. Well, we probably should have thought about this a long time ago. And now yes, now we're thinking. Yes, we are thinking now. However, we can get things done faster. We can spend, as I stated earlier on another um podcast, we're now able to spend our time back with our families if we want to. We're able to move out of the city back to the country instead of being all condensed in the city. We're able to move to the countryside, grow our own vegetables again, take care of our families, spend time teaching our children how to do things that they're going to know how to need to do if they lose electricity, then we have to go backwards again because we've used too much and killed our own systems that we operate on. Yes, this is these are things. But we took it took all of this to get us to, all of that to get us to this point. And the one thing I can say is using AI has made my life easier. Yeah, it has. Next thing I have to do, whether I want to or not, I must be a part of the equation solving for how much electricity AI uses and how we can better use the system, get what we want from it, but not have to penalize our environment. That's all of our responsibility. We must think, don't whine, don't complain, be a party to the solution. We have a lot of smart people in this world. We need to come up with a solution to these challenges that we are experiencing. No, the people that built these things did not think about them the first time, but those of us with wisdom and responsibility and capability, we must think about them. Okay? We must come up with a way to resolve these problems that we're having and these foreseen things that we see we're stepping into if we don't. Our water supply has been a mess for a long time. We need to fix that. So, what does this require of you from you? Three things. Stop deferring. AI is a tool, not a shill. Be visible in your decisions. People need to know where accountability lives. Make meaning for your people. Don't just provide direction, provide understanding, because leadership is not about control, it's about responsibility. So as I bring this to the close, this 12 series, AI will continue to evolve, guys. Systems will become more capable, and organizations will become more efficient. But three things will remain: accountability, trust, and meaning. And the leaders who understand that will not be replaced. They will be required. And so my final call to action for you is this question. After everything we've discussed, I would like to know from you what kind of leader do you want to be in this moment? Where are you still deferring? Where do you need to step forward? And what are you responsible for that only you can carry? Because the future of leadership would not be determined by AI. And all of us are a leader in our own right in some way. Again, the future of leadership would not be determined by AI, it will be determined by the people who choose how it is governed. AI scales intelligence. Again, it does not scale character. That part, it's yours to build. Character. We must institute that character in our lives, in our children, in our processes, in what we do. We have time. AI has given us back some of that. Our most precious commodity is time. And we can use that time wisely or we can be wild and frivolous with it. But things are going to change, whether we like it or not. What we have to do is be a part of the effective governance and solutions that come with that governance process. I want to thank you for being part of this series. I appreciate you. And I look forward to seeing you out there. Yes, I would love for you to buy the book or just listen to the series, something, and keep the conversation going. You can reach me on LinkedIn and there a lot of times, uh just about every day. And or researching Chronicles. Of higher ed, or some of these other periodicals that are there, Harvard, Business Review, all of these things I take a look at. The Economist, all of that. I'm very interested in what goes on and happens in our world and how it transpires before those that come in behind me. My children, my grandchildren, their children, so on and so forth. My neighbors, my friends, my church members, all of that. That matters to me. And it should matter to you too. Your lineage, your legacy, what you're leaving. Thank you again. And I appreciate you joining me on Two Doctors and a Twist. Take care.