Why I'm Betting on the Intersection of Business, Technology, and AI

When I applied to study Business Information Systems at University College Cork, I knew I wanted two things: stronger business foundations and real technical skills.

What I did not fully understand at the time was how useful that combination might become.

The more I study, and the more I use AI in a professional environment, the more convinced I am that some of the most interesting work is moving toward the intersection of business, technology, and AI. Technical skills are valuable. Business knowledge is valuable too. But the real advantage may belong to people who can move between both worlds and connect problems with workable solutions.

Not because I think any degree or tool makes someone safe from change. The job market is moving too quickly for that kind of confidence. But I do think the safest place for me is no longer inside one narrow lane.

Generalism used to feel like a weakness

When I started working in marketing in 2016, my knowledge and skills were still limited, but I was eager to learn. That was probably my biggest strength. I would be given a problem I had never dealt with before, whether it was organising an event, building an online community, launching a social media strategy, or figuring out a new tool, and I would work through it step by step until I found a way forward.

That resourcefulness became my biggest advantage. It made me a good fit for early-stage companies, where roles are often fuzzy and useful work rarely fits neatly into a job description.

Because of that, I specialised in… well, nothing too specific.

For a long time, I saw that mostly as a limitation. Specialists are easier to explain. “I do SEO”, “I write code”, or “I run paid ads” sounds much cleaner than “I figure things out and help where needed”. But looking back, I think I was building a different kind of skillset: adaptability, learning speed, problem-solving, and the ability to move between different parts of a business.

That kind of generalism helped me in startups. Now, with AI changing how knowledge work gets done, I am starting to see it less as a lack of focus and more as useful training.

University gave me structure I could not create alone

When I decided to go to university for the first time, my goal was to fill two gaps. I wanted to deepen my business knowledge, and I wanted to become more technical. I had always been passionate about technology and considered myself tech-savvy, but my technical skills had never properly extended into coding. Over the years, I had started a few short Swift, JavaScript, and Python courses, but none of them got me very far.

That changed during my first year at UCC.

To my surprise, coding quickly became one of my favourite parts of the course, and also one of my strongest academically. University gave me something I had struggled to create on my own: structure, deadlines, and repetition.

It also made technical tools feel less intimidating. I am no longer afraid of opening a terminal, running commands, working with files, writing basic Bash scripts, or using Python to solve small problems. I am not claiming to be a software engineer, but the psychological shift matters. Tools that once felt like “developer territory” now feel approachable.

The interface of my work has changed

In June 2026, I joined Zartis as a Marketing Specialist. It is my first time working after roughly a year and a half away from full-time work, and my workdays already feel different, even though the responsibilities do not look that different on paper.

I still spend a lot of time talking to colleagues on Slack, joining meetings, thinking about content, and working on marketing tasks. But the interface of the work has changed.

One of the first tools I installed on my work laptop was Visual Studio Code. I also installed Ghostty, a terminal app that lets me customise my setup and keep multiple sessions open side by side. Increasingly, I spend more time in VS Code, terminals, Markdown files, Obsidian, and AI tools than in traditional writing apps or marketing platforms.

That might sound like a small workflow preference, but it changes how I think. Markdown used to be my preferred writing format because it was clean and portable. Now it is useful for another reason: plain-text notes are easier for AI tools to process, reuse, and connect.

At work, Claude is central to how I operate. Zartis is a Preferred Services Partner in the Claude Partner Network, and I use Claude heavily through the desktop app and shared workflows. The biggest change has not simply been that “AI writes faster”. It is that AI lets me work with existing company knowledge and reusable workflows much earlier than I could before.

In previous jobs, onboarding into a complex company often meant spending weeks reading materials, asking questions, and slowly understanding how the company talked about its services. That still matters. But now, AI helps me get to a useful starting point faster, ask better questions, and produce better first drafts.

AI makes judgement more important, not less

Before, a lot of my time went into manual execution: researching a topic, writing a first draft, editing it, creating an email campaign, or turning scattered ideas into something publishable. Now, much of that work can be AI-assisted.

But that does not mean the work has become mindless.

If anything, it has made judgement more important. The value is no longer only in producing the content manually. It is in knowing what should be created, why it matters, who it is for, and whether the output is actually useful.

This is where I think a lot of people misunderstand AI-assisted content. If you ask AI to create something from scratch with no context, you often get generic output. But if the work is grounded in real company knowledge, existing expertise, clear positioning, and a specific audience, the result can be genuinely useful.

In my case, AI is not replacing my marketing knowledge. It is changing how I use it. Instead of spending most of my energy manually writing every sentence, I can spend more time thinking about the process behind the work: what we are trying to say, what the business needs, and how existing knowledge can become something clear, accurate, and valuable.

That feels like a different kind of marketing work. More systems-oriented. More connected to the business.

Why Business Information Systems feels unusually relevant

This is where Business Information Systems starts to feel like exactly the right course for me. The business side helps me understand areas I did not have much formal exposure to before: economics, accounting, organisations, incentives, and decision-making. The technical side helps me understand programming, databases, systems analysis, and the software development lifecycle.

I am starting to look at work less as a set of isolated tasks and more as a system. Where is the knowledge stored? How does information move through the company? Which parts of a process are repetitive? Which parts need human judgement? Which parts could be improved with better tools, better structure, or better prompts?

That systems-oriented thinking also connects with where I see myself going next. As I have mentioned in previous posts, product management feels like a natural direction for me. I like understanding users, shaping ideas, translating between teams, and figuring out what is worth building.

AI makes that path feel more approachable. I do not necessarily want to become a full-time software engineer, but I do want enough technical understanding to work well with developers, reason about tradeoffs, and build small things myself when needed. With tools like Claude and Codex, ideas that previously would have stayed vague now feel buildable.

The bet I am making

I do not think any degree or skillset makes someone “AI-proof”. AI will automate parts of marketing, reduce the need for some manual work, and may make entry-level career paths more difficult because some of the tasks people used to learn from are now easier to skip.

That is the uncomfortable part.

But I do think some skills are becoming more valuable: adaptability, technical confidence, business understanding, communication, judgement, and the ability to work with AI rather than around it.

My marketing background still matters. My startup generalist experience still matters. My university studies are helping me add foundations that I was missing. AI is becoming the layer that lets me connect those things and move faster.

I do not know exactly what the job market will look like by the time I graduate. But I feel increasingly confident that the right place for me is somewhere between disciplines: close enough to business to understand what matters, close enough to technology to understand what is possible, and fluent enough with AI to connect the two.

That is why I am betting on it.