“If you’re not curious, you’ll be irrelevant.”
That’s the stark warning Sudhish Mohan, Group CIO & CTO at TransUnion, offers leaders navigating the pace of change in data and AI. In his conversation with Dr. Raoul-Gabriel Urma on Data & AI Mastery, Sudhish reflects on what it really means to lead technology transformation in an industry where decisions affect banks, businesses, and millions of consumers.
His message cuts through the hype: AI isn’t a shortcut to success. It’s a long-term capability that demands curiosity, discipline, and human judgment.
As a CIO, Sudhish is clear-eyed about AI’s potential and its limitations. While many organisations rush to deploy tools, he describes TransUnion’s approach as deliberately measured.
AI has been introduced into developer workflows through tools like coding assistants, with the goal of removing low-value, repetitive tasks and enabling engineers to focus on higher-order problems. But despite industry claims of dramatic productivity gains, Sudhish is refreshingly honest: the benefits aren’t fully visible yet.
And that’s okay.
True transformation, he explains, takes time. New tools require new ways of working, and people need space to experiment, learn, and adapt. The value of AI isn’t just speed; it’s in creating capacity for better thinking and better outcomes.
Rather than treating AI as a monolithic strategy, Sudhish frames it across three clear buckets:
In the credit ecosystem, fraud is constantly evolving. AI, particularly newer modelling techniques, enables teams to identify attack patterns humans wouldn’t naturally anticipate. This doesn’t replace traditional methods; it strengthens them.
From service desk workflows to customer interactions, generative AI offers opportunities to reduce manual effort and streamline processes. The emphasis isn’t on replacing people but on freeing them to focus on higher-value work.
Ultimately, faster development cycles and better analytics translate into improved services for banks, lenders, and consumers, especially those historically excluded from mainstream financial systems.
Across all three, the common theme is experimentation with guardrails, not blind acceleration.
One of the most important insights from the conversation is Sudhish’s view on investment and return.
Many AI initiatives struggle because leaders expect short-term ROI from capabilities that are inherently long-term. Building platforms, consolidating data, and creating global analytics capabilities require upfront investment, often well before revenue catches up.
At TransUnion, the business case is grounded in market evolution and customer need. By staying close to customers, testing ideas early, and watching for “green shoots,” leaders can justify investment even when immediate financial returns aren’t guaranteed.
In fast-moving environments, waiting for certainty often means falling behind.
Another myth Sudhish challenges is the idea that more data automatically leads to better decisions.
In reality, quality matters far more than quantity. In regulated industries, some data is fixed and tightly controlled. The real opportunity lies in responsibly using alternative data, such as rental payments, to create fairer, more inclusive models.
This requires robust data foundations:
AI even plays a role here, helping teams assess data quality and spot anomalies before they affect customers.
When asked what worries him most, Sudhish doesn’t hesitate.
First: cybersecurity. As custodians of sensitive data, organisations must assume constant threat and build resilience accordingly.
Second: operational excellence. Poor data quality or system failures don’t just affect metrics; they affect people’s lives.
Third: transformation while running the business. Changing technology and operating models without disrupting customers is one of leadership’s hardest balancing acts.
And finally: talent.
Perhaps the most striking part of the conversation is Sudhish’s perspective on hiring.
In a world where knowledge becomes obsolete in months, formal qualifications matter less than mindset. What he looks for instead:
Degrees can open doors, but curiosity keeps them open. Leaders and organisations that stop learning quickly fall behind.
As Sudhish puts it, if you’re not curious, the pace of change will make you irrelevant.
One final insight stands out: Sudhish’s challenge to “cloud-first at all costs.”
While the cloud is a powerful tool, it isn’t always the most cost-effective or appropriate solution. Hybrid models, blending on-prem and cloud, can offer better control, performance, and economics, especially at scale.
The real leadership skill is knowing why you’re choosing a technology, not following trends unquestioningly.
This episode is a reminder that AI leadership isn’t about chasing the latest model or platform. It’s about building organisations that can learn, adapt, and make good decisions over time.
Curiosity isn’t a soft skill; it’s a survival skill.
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