DUE Incorporadora

Eduardo Mota

Digital Change Authority

With more than 20 years of IT experience, Eduardo Mota has delivered technology solutions across banking, food production, IT and services, retail, government, and healthcare. He brings 16 years of management experience and a business-oriented approach focused on results and performance.

His expertise includes complex IT operations, strategy and budget management, governance, process modeling, project management, and industry standards. Known for his leadership, flexibility, and relationship-building skills, he brings a practical perspective to aligning technology with business needs.

There Is No Finish Line Anymore

I've been in technology leadership long enough to watch the same pattern repeat itself. Every time a new wave arrives, someone tells me this one is different, that once we get through it, things will finally settle down. They never do, and after twenty-two years in this role, I've stopped expecting them to.

Somewhere along the way, I let go of the idea that digital transformation is a project. It isn't. It's simply how companies work now. The ones still treating it like a program with a kickoff and a closing party are the ones struggling today.

That changes what leadership actually means. The old change management playbooks, urgency, coalition, communication, and freeze, still have value, but they were written for changes with a beginning, middle, and end. What we need now is something harder to build: an organization that's simply good at changing, full stop.

I don't just want teams that can make decisions without waiting for permission. I want people who've stopped being surprised when the ground moves. In my last two performance reviews, I put "ability to learn" right next to revenue targets on the scorecard because if my team only adapts when I tell them to, I've already failed.

About AI: We've Seen This Before

I'll be blunt about AI: there's a lot of noise out there, with prophets of doom on one side and hype merchants on the other. I sit somewhere in the middle, mostly because I've lived through this movie before.

I remember when the internet was supposedly going to put every CIO out of a job. I remember the cloud panic around 2011, when half the board thought we were handing our data to strangers. Mobile came next, then Big Data. Each wave followed roughly the same script: euphoria, resistance, inflated promises, disappointment, and then, quietly and without much ceremony, the companies that kept their heads simply got on with it.

AI is following the exact same curve. Which is good news, actually, because it means we already know what to do.

We've learned the lessons, mostly the hard way. We know why pilots die in the lab. An initiative without a real business sponsor goes nowhere, which is exactly what happened to a chatbot project we invested almost eight months in a few years back, with nobody in the business actually asking for it. Resistance usually isn't irrational, either. People resist what they don't understand or what scares them.

Hype doesn't survive a budget review. When someone brings me an AI proposal, I ask the same question I'd ask about a new warehouse: What problem does this solve, and how will we know it worked? If the answer is "it's transformative," we talk more. If the answer has numbers, we move.

AI sits in the same portfolio as everything else we fund. It gets prioritized, governed, and measured the same way, and I don't care how impressive the demo looked in the boardroom. No pet projects living outside the strategy.

Never Automate a Broken Process

If I could leave one lesson with anyone running a transformation, it's this one, and I learned it the expensive way.

I've watched it happen more times than I can count. A company takes a messy, bloated process and puts smart technology on top of it. What do they get? The same mess, just faster, and often more expensive, since now they're paying for the software, too. It's the classic trap of paving a path you shouldn't be walking in the first place.

So the order of operations is fixed, and I don't negotiate it:

Question the process first. Map it out, then challenge every single step. If it doesn't earn its place, delete it. Don't automate it; kill it.

  AI doesn't fix a process. It makes a good one great and a bad one worse.  

Agree on the metrics before anyone signs a contract with a vendor. This is the step almost everyone tries to skip.

Only then bring in AI, whether that's automation, language models, or prediction, as an accelerator for a process that's already sound.

Watch what happens, learn from it, and scale only what actually works.

AI doesn't fix a process. It makes a good one great and a bad one worse. Skip the first two steps, and you'll end up with beautiful demos and nothing to show for it on the balance sheet. I've watched at least three clients make this exact mistake, and it was expensive every single time.

Three Things a CIO Actually Does

People ask me what the job actually is these days. Honestly, it comes down to three things.

Connect technology to the business. Not "align with." Connect. Sit with the CEO and business leaders and figure out where AI genuinely makes money, saves money, or keeps us out of trouble. Everything else is noise.

Make it safe to experiment. People are scared, and they've all read the headlines about AI taking jobs. If your teams think the new tool is here to replace them, you won't get adoption. What you'll get is polite compliance in meetings and quiet sabotage everywhere else. Address the fear out loud, and address it early.

Set the guardrails. Data privacy, algorithmic fairness, transparency, all of it. It's not bureaucracy; it's self-preservation. One bad regulatory fine or one story in the press can erase years of efficiency gains overnight.

Two Decades In

Twenty-some years in this role have taught me one thing above everything else: the technology was never the hard part. The hard part is building an organization that treats change as the work itself, not as some interruption to it.

AI is powerful. It really is. But it obeys the same laws every wave before it did: value comes from discipline, not novelty. Rebuild the process first, let the technology make it faster, and build a company where the next wave doesn't scare anyone because they've already ridden the last five.

That's the job, as far as I can tell. Some weeks, it feels less like leadership and more like staying upright on a boat that never stops rocking, which, I'll admit, still beats the alternative.