Anu Chandrasekar

Anu ChandrasekarJul 14, 2026

Years from now, I probably won't remember every meeting from my first month in a new job. But I'll always remember what happened by the printer. Starting after a year's career break, I expected the obvious challenges.  Learning new ways of working,  remembering what felt like 10,008 names, and trying not to look completely lost looking for Meeting room 4. Well throw perimenopausal brain fog into the mix and, honestly, it felt like I'd accidentally signed up for an endurance event. 😅 One afternoon, a few weeks in, my brother called from India. He was worried about Dad's health. I carried on with my day.  Or at least I tried to. I found myself standing by the printer. Trying so hard to keep it together. And then... I couldn't. The tears just started rolling down my face. I remember frantically looking around for tissues... ...or even my sunglasses. Anything that would help me hide for just a minute. Before I knew it, a colleague had noticed. She quietly excused herself from the meeting she was in, walked to the kitchen, came back with a handful of tissues, handed them to me and simply asked, "Are you okay?" That was it. No awkwardness. No trying to fix me. I've worked on programmes worth millions. I've designed operating models. I've delivered transformation. Yet years from now, I probably won't remember every workshop or presentation. I'll remember the colleague who quietly walked out of her meeting to bring me a handful of tissues. Every person we work with is carrying a life outside the office. Parents. Partners. Health worries. Dreams. Heartbreak. Joy. Things we know nothing about. Sometimes the most memorable thing you do at work isn't leading the meeting. It's noticing the person standing quietly by the printer. To the colleagues who ask, "Fancy a coffee?" Who suggest a quick walk. Who notice. Thank you. 😊 Work will always be about delivering results. But the best workplaces are built by people who never forget they're working with humans first.

Anu ChandrasekarJul 31, 2026

Some of the biggest problems in banking.. ..aren't technology problems at all. They're people, process and fragmentation problems. And no amount of AI sprinkled on top will fix that. That's exactly why I said yes when our lovely Katie invited me to speak at the October Banking Leaders Forum. After two decades in banking transformation, I've learnt something that surprised me. (I should say still learning) The banks that move fastest aren't always the ones with the biggest budgets or the newest technology. They're the ones that connect the dots. Between teams - systems - strategy & delivery. Because when every department solves only its own problem, everyone works harder... ...yet customers still feel the gaps. I'm looking forward to sharing practical stories from my own experience - where simplifying the foundations made AI genuinely useful instead of just another shiny initiative. And, if we're lucky, having a few honest conversations about the things we don't usually say out loud. Thank you, Katie and the Soul Technology team for the invitation. I can't wait to see everyone there. I'll leave the link in comments to register :)

Anu ChandrasekarMay 30, 2026

In banking, we rarely start with technology. We start with the problem we're trying to solve. We don't select a payments platform before understanding the payment problem. We don't choose a cloud provider before understanding the workload. So why do so many AI conversations begin with: "𝘞𝘩𝘪𝘤𝘩 𝘮𝘰𝘥𝘦𝘭 𝘢𝘳𝘦 𝘸𝘦 𝘴𝘵𝘢𝘯𝘥𝘢𝘳𝘥𝘪𝘴𝘪𝘯𝘨 𝘰𝘯?" I wonder if we're sometimes asking that question too early. Because a relationship manager drafting client communications has very different needs from a risk analyst reviewing controls. A finance team looking for accuracy and traceability has different requirements from a developer writing code. Different users. Different outcomes. Different measures of success. The reality is that AI models have different strengths. Some are stronger at natural language generation. Some excel at coding. Others perform better on research, document analysis, or structured reasoning. Which is why the challenge may not be model selection alone. It may be understanding the use case first and then determining which capability is most appropriate. That is where the conversation becomes more interesting. Governance. Operating models. Controls. Accountability. And how AI is embedded into the flow of work in a way that delivers value while remaining safe, explainable and manageable at scale. One of the things I found particularly interesting at Seismic was seeing how the industry is moving beyond standalone AI tools and towards AI embedded directly within business workflows. For me, the strategic question is becoming less about: "Which model should we choose?" And more about: "How do we ensure the right capability is being used for the right task, under the right controls?" Thank you Gemma for the invitation to Seismic CityTours and a thought-provoking event.