Ivelisse Arroyo

Ivelisse Arroyo Marketing & Business Operations Consultant. LinkedIn Top Mentoring Voice. Posts in English & Spanish.

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27/08/2026

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Ten years ago, I was already writing about this and published in several media outlets in Puerto Rico.In May 2016, Prime...
27/08/2026

Ten years ago, I was already writing about this and published in several media outlets in Puerto Rico.

In May 2016, Primera Hora published an article I wrote titled “¿Conectados o desconectados?” about children’s exposure to technology and the internet.

At the time, my children were young, and because much of my career was already connected to the internet, digital marketing, and social media, I had seen enough of the online world to know that unlimited access wasn’t something I wanted for them.

My husband and I made a deliberate decision to limit their exposure to technology and keep them off social media. They didn’t begin using social platforms until they were around 17–18, when they were old enough to make those choices themselves.

During those years, I also used my work in content marketing and PR to talk about this issue through local media, sharing guidance and tools to help parents establish healthier boundaries around technology.

Fast-forward exactly ten years.

Meta has agreed to pay up to $17 billion and implement stronger child-safety measures on Facebook and Instagram as part of a landmark settlement with states over allegations involving social media addiction among children and teens.

Seeing this news feels incredibly full circle.

I don’t believe technology or social media is inherently bad. I’ve built a significant part of my career around digital technology and understand its value.

But children are not simply smaller adults.

Parents have a responsibility to protect their children online, but technology companies have a responsibility, too.

We need better safeguards, greater transparency, more accountability, and tools that help parents protect their children while preparing them to live in a digital world.

Ten years later, I’m glad to finally see a ray of light.

Perhaps we’re finally moving beyond “Parents need to control their children’s access” and asking the equally important question:

What responsibility do the companies building these environments have toward the children growing up inside them?

You can also read it digitally via El Vocero de Puerto Rico>>https://www.elvocero.com/uncategorized/ni-os-en-verano-conectados-o-desconectados/article_b4626320-6fd9-5080-afc6-ef2fee1724e3.amp.html

Read the news article about Meta>https://www.pbs.org/newshour/nation/meta-reaches-17-billion-settlement-with-states-in-landmark-trial-over-teen-social-media-addiction

Prompt engineering was never going to be the most important AI skill for .Context engineering is.We’ve spent the last f...
25/08/2026

Prompt engineering was never going to be the most important AI skill for .

Context engineering is.

We’ve spent the last few years learning how to talk to AI.

Now we need to focus on something much harder:

What does AI actually know about the business when it acts?

Salesforce identifies context engineering as a major enterprise AI trend for 2026: prompt engineering optimizes the question; context engineering optimizes the conditions under which the question gets answered. (salesforce.com)

That distinction matters.

An AI agent supporting Marketing doesn’t just need a good prompt. It needs to understand the customer, lifecycle stage, previous interactions, consent, opportunities, business rules, processes, and which data it can actually trust.

Where does all that context come from?

The operational infrastructure underneath it.

CRM. Marketing automation. Customer data. APIs. Governance. Processes. Documentation. Ownership.

Suddenly, all that “boring operations stuff” isn’t so boring anymore. 😏

Salesforce reports that 76% of data leaders say governance hasn’t kept pace with AI. (salesforce.com)

And that’s where I think companies risk getting agentic AI very wrong.

We’re asking what AI agents can do before asking whether our businesses can provide the context they need to do it correctly.

AI cannot retrieve a business rule nobody defined.

It cannot follow a process nobody documented.

It cannot resolve ownership nobody established.

And it cannot understand a customer when five systems disagree about who that customer is.

We already know what happens when humans operate that way.

Now imagine automating it. 💀

This is why I don’t believe AI makes Marketing Operations less relevant.

It makes the real purpose of MOps harder to ignore.

The next evolution of MOps isn’t simply operating the technology.

It’s designing the environment the technology operates within.

Prompt engineering teaches AI how to answer.

Context engineering gives AI enough understanding to know what that answer means to the business.

That’s a much bigger job.

So maybe the question organizations should be asking isn’t:

“Are we ready for AI?”

It’s:

“Is our operational infrastructure ready for AI to understand us?” 👀

I’m curious how other MOps, RevOps, and data leaders see this shift. Are we prepared for context engineering, or are we about to give increasingly capable AI increasingly messy context?

Challenge my perspective in the comments. And if this conversation needs to happen inside your organization, share it with the person leading your AI strategy.

I just published a new article on Substack about something I believe deserves a much bigger conversation: what it means ...
22/08/2026

I just published a new article on Substack about something I believe deserves a much bigger conversation: what it means to be a woman leading technology and digital transformation in 2026.

Technology has transformed enormously. Some of the leadership dynamics surrounding it haven’t.

Women are still navigating expectations around directness, authority, power, and how we’re “supposed” to show up in the room, especially when our job requires challenging established ways of working.

But digital transformation isn’t simply about implementing better technology. It requires people, behaviors, and leadership to transform with it.

We cannot build tomorrow’s organization with yesterday’s leadership behaviors.

I’d especially love to hear from other women working in technology, transformation, operations, or adjacent fields.

What has your experience been?

Have you ever felt pressure to soften your leadership style to make others more comfortable?

Read the article and share your perspective in the comments.

I genuinely want this to be a conversation. 👇

Link to article in below in the comments.

The other day, I saw a post from a CEO on LinkedIn sharing his definition of success: building a successful company.And ...
17/08/2026

The other day, I saw a post from a CEO on LinkedIn sharing his definition of success: building a successful company.

And there’s nothing wrong with that.

But I believe success is deeply personal.

For my husband and me, success looks like this:

Our 17-year-old son, Sebastian, starting his freshman year of college today. ❤️

Sebastian has Level 1, inattentive type, and learning disabilities.

This picture may look like a normal back-to-school moment. To us, it represents 15 years of advocacy, therapies, tutoring, financial sacrifice, uncertainty, and figuring things out without always having a roadmap.

We just kept going.

For years, he struggled in educational environments where he often felt misunderstood. Today, he’s starting fresh at a university that welcomes neurodivergent students.

After freshman orientation, he came home and told me about his day and the people he met.

Sebastian may not show excitement the way a neurotypical person might expect, but then he said:

“Mom, I felt that for the first time, something was only for me.”

That sentence meant everything. ❤️

He spent the weekend preparing everything for his first day.

He’s not just starting college. He’s beginning the life he’s been waiting for, studying computer programming and video game development. 🎮💻

Success isn’t always money, titles, companies, or climbing the corporate ladder.

Sometimes success is watching the child you once wondered would become independent walk into college at 17 and begin building a life of his own.

Today, my husband and I can look at each other and say:

We did it. ❤️

This is our definition of success.

And Sebastian is just getting started. 🚀

AI Watermarks Could Become an Accessibility Problem. I’m going to say something that may be unpopular:The “AI wrote this...
14/08/2026

AI Watermarks Could Become an Accessibility Problem. I’m going to say something that may be unpopular:

The “AI wrote this” conversation can become discriminatory when we assume everyone has the same ability to organize and express their thoughts.

I have ADHD. I often speak my brainstorming ideas into AI and ask it to organize them. I provide the context, the ideas, the perspective, and what I’m trying to communicate.

Sometimes my thoughts come faster than I can structure them. Sometimes my speech delivery stumbles. AI helps me turn what is already in my head into something coherent.

I also use it when I’m frustrated or emotional, to slow down my impulses, organize my thoughts, and make sure what I’m communicating actually reflects what I mean.

And this isn’t just about me. 🤷🏻‍♀️

My neurodivergent children use AI to organize study outlines, prepare for tests, and structure information.

My son with AuADHD can use class transcripts to create notes because simultaneously listening, processing, filtering information, and taking notes can be challenging.

A 2025 study of 124 students with disabilities, including ADHD and autism, found that generative AI can support expressibility, planning, and learning, particularly in writing. ( ScienceDirect )

So yes, let’s talk about academic integrity, plagiarism, attribution, and responsible AI use.

🗣️ But let’s also talk about accessibility.

If someone uses AI to generate an entire paper they don’t understand, that’s one thing.

If someone has the ideas, knowledge, experience, and perspective but uses AI to organize those ideas into a form others can understand, that’s something very different.

AI hasn’t replaced our ability to think, our ideas, or our voices.

It has helped us use them.

For neurodivergent people, sometimes the hardest part isn’t thinking.

It’s translating the thinking into the format everyone else expects.

Maybe the question shouldn’t always be:

“Did AI write this?”

Maybe we should also ask:

“What barrier did AI help this person overcome?”

Accessibility should be part of the AI conversation, not an afterthought. 😏

Organizations say they want change. Until change shows up. 👀Throughout my consulting career, I became known for taking o...
13/06/2026

Organizations say they want change. Until change shows up. 👀

Throughout my consulting career, I became known for taking over projects that were delayed, derailed, over budget, or politically stuck.

What I discovered is that fixing a broken project isn’t primarily a technology problem.

It’s a people problem.

The longer dysfunction exists, the more normal it starts to feel. And the person brought in to challenge it often becomes the least popular person in the room.

In my latest Substack article, I explore:

⚠️ Why turnaround leaders are often labeled “aggressive”
⚠️ Why resistance is the biggest obstacle to transformation
⚠️ Why results and popularity are rarely the same thing
⚠️ Why organizations struggle to let go of what no longer works

If you’ve ever led change, rescued a failing initiative, or challenged the status quo, I’d love to hear your perspective.

📖 Read the article here: https://open.substack.com/pub/ivelissearroyo/p/the-cost-of-being-the-person-who?r=4biqm2&utm_medium=ios

📬 Subscribe if you enjoy conversations about leadership, business operations, transformation, MarTech, RevOps, and the realities of driving change inside organizations.

Everyone wants the AI-powered business headline. Very few want to do the operational work required to make AI actually f...
14/05/2026

Everyone wants the AI-powered business headline. Very few want to do the operational work required to make AI actually function. 🤷🏻‍♀️

Today at the SME Puerto Rico, “Digital Innovation Forum”, one interesting slide discussed was The 6 Dimensions of AI Market Strength:

👉Commerce Availability
👉Discoverability
👉Trust & Authority
👉Empathy & Message Fit
👉Behavioral Adoption
👉Reinforcement

And while these dimensions sound great in theory, the reality is:

None of them scale without operational maturity.

AI cannot thrive in organizational chaos.

AI needs:

✔️ clean data
✔️ governance
✔️ defined ownership
✔️ connected systems
✔️ standardized processes
✔️ operational accountability
✔️ structured customer journeys
✔️ clear business rules

Without that, AI simply automates confusion faster.

This is the part many organizations are still avoiding. The hard work.

We are no longer in the “AI theory” stage. We’ve passed the inspirational panels, the hype of AI information, or ChatGPT, Claude, Gemini, and the endless prompts conversation.

Yes, that’s important. Yet, at an organizational and business level that’s too surface level. We’re in a more granular and advanced ex*****on level.

The real competitive advantage now is ex*****on.

🗣️And ex*****on requires businesses to build the operational foundations and capabilities necessary for AI to work effectively in real-time environments.

The truth is:

🤖AI is not replacing operational discipline.
🤖AI is exposing which organizations never had it.

A company with fragmented systems, undefined processes, poor CRM hygiene, and siloed teams will not suddenly become “AI-driven” because they bought a platform or they say they are using AI.

The question is: Are you doing the hard work? Are having the hard conversations about data? Because without robust data AI will not work.

Technology does not fix operational dysfunction. It magnifies it.

The organizations that will truly win with AI are not necessarily the ones with the most AI-driven tools.

They’ll be the ones with:

👉the clearest structure.
👉the healthiest data ecosystems.
👉the strongest governance.
👉the best operational alignment.
👉and the ability to execute consistently across teams.

That’s the conversation businesses need to start having now.

Not:

“How do we use AI?”

But:

“Is our organization operationally capable of supporting AI at scale?”

Automatic Reply: 🌸 OOO: Mother’s Day Maintenance Mode Activated. Happy Mother’s Day!
10/05/2026

Automatic Reply: 🌸 OOO: Mother’s Day Maintenance Mode Activated. Happy Mother’s Day!

AI doesn’t replace expertise. It exposes who actually has it. 😬The reason I love ❤️ technology is because it reminds me ...
06/05/2026

AI doesn’t replace expertise. It exposes who actually has it. 😬

The reason I love ❤️ technology is because it reminds me of accounting.

My educational background is in Business Administration, majoring in Accounting. What I loved about accounting was its precision. There was clarity.

Things either balanced or they didn’t. ✔️❌
Problems had structure. You knew where to look, how to validate, and how to confirm whether something was right or wrong.

Before accounting, I studied foreign languages and literature. 📚🌍 I loved it too, and honestly, it still shapes how I write, communicate, and understand the world. It expanded my perspective.

Yet perspectives are wider. They can be many and unpredictable.

But accounting gave me direction, predictability, and accuracy. 📐

It taught me that behind every result, there’s logic. Behind every discrepancy, there’s a reason. And behind every solution, there’s a process.

Like technology. 💻

That’s why I eventually ended up loving and . ⚙️

Technology felt familiar because, traditionally, systems were deterministic. If something failed, you could trace the issue. You could debug it. You could find the error. 🔎

In many ways, it was pure logic and applied mathematics.

But AI is changing that relationship. 🤖

Today, AI gives us answers with confidence, but not always with accuracy. We call it “drift.”

And unlike traditional systems, it often won’t show you where the error is. You have to know enough to identify it yourself.

That’s why domain expertise matters more than ever. 🧠

The future won’t belong to people who simply know how to use AI tools. It will belong to the people who understand their organization’s operations deeply enough to judge whether the output is actually correct.

Humans are no longer just users of technology.

We are becoming its auditors. 🕵🏻‍♀️

In the current AI hype era, the most valuable skill may no longer be getting answers…it may be knowing which answers to trust. 🙃

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