Why humans matter in AI-driven business analysis

When I started my Digital Skills: Artificial Intelligence, Accenture Certification, I expected to learn how to talk to machines. Instead, I learned how to listen to people.

New perspectives on the role of human insight

I am an Associate Member at Harvard Business Review, a Professional Member at BCS, The Chartered Institute for IT and a Member of the IIBA. In addition to my business analyst role at Swedbank, I lecture on business analysis at Vilnius University, deliver business analysis foundation certification training at BKA Upgrade Yourself, connecting human-centred thinking with digital transformation.

Like many professionals working in digital transformation, I pursued AI upskilling not to follow the trend, but out of necessity. The certification I selected covered natural language processing, machine learning fundamentals, ethical implications and practical use cases —but behind the technical layers I encountered something deeper: an invitation to explore human responsibility in a digital world.

The irony of being forced to reflect on how humans often fail to process nuance through learning how machines process input wasn’t lost on me. Where AI is binary and structured, human work, especially business analysis, thrives in ambiguity.

Emotional intelligence and AI

As I worked through the modules, what surprised me most wasn’t the technical depth, but the emotional exposure.

I began to feel a sense of displacement. Was I becoming less relevant? Would AI perform my role better, faster, cheaper?

And then it hit me: that fear was data too. It was telling me something valuable, not about the future of work, but about my own mindset. I realized that emotional intelligence is not separate from digital skills  — it’s an essential part of them. The ability to reflect, to doubt, to reframe, to empathise, these are the real ‘soft’ skills that remain undigitisable and make human centred analysis vital even as we enter a new technological era.

Balancing technology with human insight

Throughout the certification, I kept returning to one question: where do we, as human professionals, still add value? The answer, again and again, was in the interpretation — the meaning and decisions behind the data.

One of the most powerful moments in the course came not from a technical lecture, but from a discussion on algorithmic bias. We were asked: if a model mirrors society’s inequality, who is accountable?

The answer, of course, is: we are.

It’s tempting to view AI as a ‘neutral’ actor that simply reflects the data it's fed. But business analysts know better. We understand systems, context and consequences. We understand that a flawed input leads to a flawed output, even if the formula is mathematically correct. Anyone can prompt an AI tool, but it takes an analyst to ask the right question at the right time in the right context, and to challenge the assumptions behind it.

We must resist the narrative that AI replaces thinking. On the contrary, it demands better thinking from those who guide and govern it. 

As Kitty Hung emphasises in her reflections on AI and BA practice: ‘We must ensure that ethical considerations are built into every stage of problem-solving, not treated as an afterthought.’  

This means that ethics becomes part of design, not a checkmark on a risk register. In the age of AI, this becomes ever more critical, because systems no longer just automate; they infer, predict and influence. That’s why human-centred analysis is essential.

Why humans should shape AI

Completing the certification gave me knowledge, but, more importantly, it gave me clarity. I began to see that the real story of AI is not about replacing humans, but about revealing what is most human in us. It affirmed that business analysts are not merely collectors of requirements, but stewards of outcomes that serve people responsibly. And it reminded me that leadership in the digital age is not measured by how tightly we control systems, but by how bravely we navigate the uncertainty they bring.

It is our role to ask:

• What is this system doing?
• Who does it serve?
• Who might it exclude?
• What unintended consequences might arise?

These are not technical questions. They are ethical, organisational, and shaped by what it means to be human.

AI as a mirror of organisational maturity

The way an organisation engages with AI often reflects its level of cultural and operational maturity. As highlighted by the Harvard Business Review, many organisations that fail to scale AI do so not because of technology, but due to a lack of cross-functional integration and strategic clarity.

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Some adopt AI as a shiny new tool, rushing to automate without understanding the impact.

Others take the time to question: What problem are we solving? Is automation really the answer? What value are we creating — and for whom?

As Karl Wiegers notes, ‘Requirements are not about what the system does. They are about what the user needs.’  

These questions are not just strategic; they are profoundly analytical. Business analysts are in a unique position to raise these issues early in the conversation. Our job isn’t to resist change, but to ensure that change is meaningful, aligned with organisational goals, and built on clear understanding. This includes anticipating risks, clarifying requirements, and involving the right stakeholders at the right time.

Human skills are digital skills

The World Economic Forum identifies analytical thinking, complex problem solving, and emotional intelligence among the top skills for the future. These are not just buzzwords. They are signposts pointing us back to what makes us distinctly human.

There is a common misconception that digital skills are about coding, configuring tools, or speaking machine language, but digital fluency is far broader than that. It includes the ability to interpret data critically, navigate ambiguity, and connect the dots between technology and human needs.

Business analysts excel in this space: we are translators, integrators and bridge-builders. We don't just adopt tools; we shape the conditions in which tools make sense. We create clarity where others see only dashboards. We turn information into meaning and meaning into action.

A call to human-centred analysis

To my fellow analysts, strategists, and digital leaders: your role matters.

We don’t need more automation without reflection; we need thoughtful people who are willing to ask uncomfortable questions, even when the answers don’t come from a dashboard.

Because in the end, the most important skill I learned wasn't how to speak to AI. It was how to stay human in the face of accelerating systems — and that, to me, is the real value of digital literacy.