Lee Latimer

Change is never easy — but it’s almost always for the better. With the expected merger between Fifth Third and Comerica, a lot of people are asking what’s next. For me, this kind of change is a reminder of how much opportunity sits on the other side of uncertainty. I’ve spent most of my career in identity, security, and cloud architecture — helping organizations stay resilient as technology and business models evolve. What I’ve learned is that real growth happens when we lean into change, not away from it. This merger brings a lot of possibilities: new teams, new systems, new challenges — and that’s exactly where innovation starts. Whether it’s rethinking how we handle access, modernizing our cloud environments, or finding smarter ways to use AI to automate and protect, these moments push us to build better. I’ve been spending more time lately exploring how AI can simplify what used to take days — from risk analysis to access certifications — and it’s exciting to see those ideas move from theory into practice. Change forces reflection. It makes you ask where you can add the most value, how you can grow, and what new skills will matter tomorrow. For me, this next chapter is about doubling down on what I love most — designing secure, scalable systems, mentoring others, and staying curious about where AI can take us next. Here’s to embracing change — and turning it into opportunity. #Leadership #Change #AI #CyberSecurity #IdentityManagement #CloudArchitecture #Banking

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COBOL was created in 1959. Sixty-five years since its inception, it's still powering... • Trillions of dollars in daily financial transactions • Core banking systems • Payroll engines • Government processing systems Most institutions don’t replace or rewrite it. The foundation still holds, so they're able to build around it. COBOL works because it is (mostly) human-readable, built around real business logic, stable under heavy load, and portable across systems. Leadership at its best can modernize and evolve while maintaining the systems that already work. As tech leaders, we love greenfield systems. Clean diagrams. New stacks. Fresh abstractions. But abstraction has killed more startups than legacy code. The world still runs on COBOL because uptime beats novelty every time. And that's the part every engineering leader should pay attention to. Full breakdown on what modern software teams can learn from a 1959 language in my newsletter. 🔗 https://lnkd.in/e4vyDmrJ

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When the C-suite loses sleep over IT, the problem isn’t technology. It’s trust. That was the situation I inherited: outdated hardware, an inability to scale, and a C-suite that had lost faith in IT. The answer wasn’t just new tech. It was project management, board-level communication, and risk management from day one. By bringing the team and stakeholders with us, we delivered a WAN and data centre migration with zero downtime - and improved incident response by 40%. In the process, we cut system downtime by 70% and rebuilt trust in IT. Tech is replaceable. Trust isn’t. And leaders who can translate complexity for non-technical stakeholders will always deliver the most business value. #ITLeadership #OperationalResilience #FinancialServices #Dubai #DIFC

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I recently sat down for an interview where I emphasized something that still surprises people: the best CIOs I know aren't the ones who can code or architect the most sophisticated infrastructure. They're the ones who understand your business better than anyone in the room and can articulate how technology directly impacts revenue, margin, and competitive positioning. A CIO is unique as you need to understand IT, that is what got you the CIO position, but you also need to understand each department as well as the manager and THAT is what will make you, hopefully, an executive and not just a manager with a bigger title. Here's the hard truth: most companies treat the CIO as the head of IT. That's a setup for failure. A great CIO isn't managing servers and helpdesks, and honestly they shouldn't be as they will have meetings, collaboration, and business communication which will take up most of their time. A great CIO is a business strategist who happens to work in technology. To get there, future CIOs need to invest in understanding each business function as deeply as the people running them. Know your finance organization's margins, cash flow cycles, and cost pressures. Understand sales' pipeline velocity, deal complexity, and customer retention challenges. Comprehend operations' efficiency metrics, supply chain vulnerabilities, and scaling constraints. This isn't optional knowledge. This is foundational and if you don't know it, and I would say you probably don't, ask questions that surprise executives that you want to know. Until you understand where technology intersects with each business area's biggest pain points, you can't help but create strategy that matters. The CIOs who drive real transformation are fluent in the language of business. They don't talk about cloud migration. They talk about how cloud migration reduces capital expenditure while improving time to market. They don't discuss data infrastructure. They discuss how better data capabilities unlock revenue opportunities and competitive advantages and they know their audience and can read a room. They know how to talk to the audience they are addressing, NOT above them. Board members and Executive's, if you want a CIO who simply manages IT, you'll get exactly that: managed IT. If you want a CIO who shapes strategy and drives business outcomes, you need to understand that role differently and find that candidate that will be a great CIO that can set direction. A great CIO can see where technology enables transformation. They speak the language of business because they are business leaders first. They don't take no for an answer, and they continue to push technologies that are business movers, even if rejected and takes years to get accomplished. The role of a CIO is to lead. As much as many organizations want them to just manage IT, that isn't the roles responsibility. If that is how you see CIO, stick with having an VP of IT, you aren't ready for a CIO. Thoughts?

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Why I Care About Automation (And It’s Not About the Cost) Automation isn’t just a time-saver — it’s a multiplier of clarity and creative potential. Yes, it reduces operational overhead. But the real gain is this: it frees up your best people — the few who raise the bar, solve the hard problems, and define what excellence can be. Their time isn’t linear. Every hour you free up for them compounds across decisions, systems, and standards. And when automation reduces headcount, it adds a second advantage: fewer decision-makers. That means faster cycles, less drag, and sharper execution. It also creates resilience. You’re not building a system that depends on memory, improvisation, or the presence of specific individuals. You’re building one that runs — well and predictably — even when people leave, teams scale, or complexity grows. And by standardizing decisions and flows, automation improves signal quality. Less noise. Cleaner metrics. Sharper feedback loops. Which means better judgment and faster learning. Combine all of that —agility, leverage, repeatability, and clarity — and what you get isn’t just efficiency. It’s a higher-functioning system. Not just better output. A better operating state.

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For years we’ve heard: “AI will eat software.” But enterprise software spend will hit $1.2 trillion this year—up 11% YoY. AI isn’t killing software, it’s making the moats deeper. ✅ Winners: Entrenched SaaS platforms embedding AI (Salesforce, Workday, ServiceNow, Microsoft, Adobe). ❌ Losers: Overpriced point-solution SaaS and “AI-native” startups promising full replacement. The real asymmetry? When multi-agent AI systems emerge—and the incumbents that own enterprise workflows are positioned to win. Read today’s H.E.A.T. Formula breakdown: 👉 https://lnkd.in/eBHBJxUh

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This is a useful dashboard if you are considering what models to use for your agentic architecture implementations. Having the cost profile is handy as well. This is obviously no substitute for experimentation, but useful to have a *more* objective confirmation of what you are experiencing, or perhaps a useful guide on what to play with when getting started. Full link below.

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