Marcellino Carlo leads Data and Analytics for Secured Lending at Standard Bank Group, where he spends his days convincing machines to behave and humans to think. With over 15 years as a data practitioner, he has built analytics capabilities across banking and shipping & logistics, survived more legacy system migrations than he cares to count, and somehow still finds joy in the craft. When he is not orchestrating AI, he is orchestrating music as an avid orchestral music leader. He believes both require the same thing: knowing when to trust the instrument and when to trust your ear.
Session Overview
Leading Analytics in the Age of the Machine
Something uncomfortable is happening in data and analytics, and most practitioners are discussing it at the edges rather than confronting it directly. Agentic AI is quietly automating the foundational layer of our craft: the queries, the data cleaning, the dashboard builds, the ad-hoc analysis requests that once required a trained professional. The work we used to hand to junior analysts. The work that, for decades, was how this profession built its next generation.
We are democratising analytics at exactly the moment we risk hollowing out the pipeline that makes great analysts possible.
This session takes a practitioner’s honest look at the convergence of forces reshaping the analytics profession over the next three to five years. Drawing on current research, industry data, and real leadership experience in financial services, it examines the following:
• Agentic AI and its structural impact on analytics team composition, with specific attention to what happens to the apprenticeship layer of our profession when AI absorbs foundational work.
• The psychology of professional identity disruption, and what genuine resilience looks like in a field where the definition of expertise is shifting faster than most organisations can manage.
• The false security of organisational bureaucracy as a brake on AI adoption, and the real risk that sits behind institutional slowness: not that change is coming too fast, but that it will arrive all at once when the cultural and structural barriers finally give way.
• The trap at both ends of the adoption curve, from early adopters who deploy AI before their teams have the baseline judgement to catch its errors, to late adopters who mistake institutional inertia for strategic caution.
• The longer horizon question of where AI capability is actually heading, including the relationship between quantum computing advances, room-temperature superconductors, and the acceleration toward artificial general intelligence, and why this matters for career and workforce planning decisions being made today.
The session argues that the analytics profession is not being gradually upgraded by AI. It is being structurally restructured, and most organisations are not managing that restructuring with intention. The transition from builder to orchestrator is real. But it demands that people have first been builders. The most dangerous outcome is not AI replacing analysts. It is AI replacing the foundational work of analysts before organisations have built the human judgement required to govern what AI produces.
WHAT ATTENDEES WILL LEAVE WITH
• A framework for auditing which parts of their analytics function are genuinely defensible as AI capability advances, and which are not.
• Practical approaches to restructuring teams to preserve foundational learning while embracing AI capability.
• A leadership model for guiding people through professional identity transition, not just technical change.
• Clarity on where the real risk sits in the AI adoption timeline, and how to use the current window of institutional lag to prepare rather than to take comfort.
WHY THIS TALK NOW
This is not a talk about whether AI will change our field. Most conferences are already having that conversation. This is about whether analytics leaders are leading that change or simply being led by it. The distinction matters more than any technology decision any of us will make this year.
At TED2025, former Google CEO Eric Schmidt argued that the AI revolution is not overhyped but wildly underhyped, that human minds evolved for linear thinking are structurally unable to forecast the impact of exponential change. This session takes that premise seriously and asks what it means for the people leading analytics functions inside large organisations right now, while the lag still gives them room to act.
This talk is not an alarm. It is an honest reckoning and a practical roadmap.
The window to act is now, and the question is whether we are leading the change or being led by it.
Alternatively, please email sales@eventfulpeople.com for quote, invoice or any queries and we’ll be glad to assist.
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Marcellino Carlo leads Data and Analytics for Secured Lending at Standard Bank Group, where he spends his days convincing machines to behave and humans to think. With over 15 years as a data practitioner, he has built analytics capabilities across banking and shipping & logistics, survived more legacy system migrations than he cares to count, and somehow still finds joy in the craft. When he is not orchestrating AI, he is orchestrating music as an avid orchestral music leader. He believes both require the same thing: knowing when to trust the instrument and when to trust your ear.
