This interview was originally published at WARC.
As digital transformation becomes standard across banking in India, competitive advantages will increasingly come from something harder to commoditise: intelligence. dentsu's Hemant Kshirsagar explores why the next generation of winning banks will be AI-native, anticipatory, and built around relationship intelligence at scale.
The day has finally arrived! You have successfully become a digital-first bank, and that is not a small achievement. Years of focused investment across platforms, infrastructure, and customer journeys are now visible. Mobile and web experiences have evolved meaningfully. Core workloads have moved to the cloud.
Data platforms and lakes have been established. Processes have been digitised. Chatbots and digital-first journeys are embedded into the system. This is real progress. It has taken intent, capital, and persistence. But behind that sense of achievement and happiness lies a deep undercurrent of worry.
Does being digital-first still create a meaningful advantage, or has it simply made you competitive rather than distinctive? Because today, being digital-first is no longer an advantage. It is table stakes, the baseline expectation, or as Gen Z would put it, the bare minimum.
The next shift will not be incremental
Over the next 36 months, the institutions that will define the future of banking and emerge as winners will be those that move beyond digital and reimagine themselves as “AI-Native Banks”.
This is not about adding AI to what already exists. It is about rethinking banking from the AI-native lens, with intelligence at the core of everything. The shift is structural.
Banking comes full circle
It is not a distant memory for those born before the mid-90s in India, when the neighbourhood branch manager was a trusted part of the family. They understood your financial life in detail, not as data points but as context.
They knew that Mr. Sharma’s son was getting married and might require a personal loan. They knew that Mr. Soni’s garment store would face a cash squeeze every September and would need working capital. They knew when you had just started your first job and would need to open your first salary account. That depth of relationship intelligence was the real competitive advantage.
As banking expanded, scale became the priority. Banks grew from a few hundred branches to thousands, from lakhs of customers to crores. In that transition, something fundamental shifted. Relationship intelligence was traded for operational efficiency.
The system moved from the individual to the cohort. Personalisation did not disappear; it standardised. Communication, messaging, and offers were designed for segments. Over time, banks moved further away from each customer’s financial reality.
AI-native banking restores this advantage at scale
AI-native banking brings us back to understanding the customer deeply, anticipating needs, and initiating the right conversation at the right moment.
The difference now is scale. It combines that depth of understanding with the ability to serve millions simultaneously, consistently, and in real time, at an industrial scale. The trusted bank manager returns, always on, continuously learning, never forgetting, and capable of managing millions of relationships at once.
Why now?
Two forces are converging, accelerating this shift.
Large Language Models, data platforms, and AI infrastructure have crossed a threshold – they are no longer experimental or prohibitively expensive. Over the years, Indian banks have built mature data infrastructure but have been limited by traditional AI's ability to extract real-time intelligence and convert it into personalised, contextual human interactions at scale, accurately and affordably.
Expectations are no longer shaped by banking. They are shaped by ecosystems that anticipate needs.
Quick commerce platforms predict needs before intent. Streaming platforms curate choices instantly. These are now the benchmarks customers bring into every interaction.
As players outside banking embed LLMs and Agentic AI into every customer touchpoint, expectations are being recalibrated completely. Discovery has also shifted. Customers are no longer coming to your website. That journey has moved to social feeds, voice interfaces, and AI agents. This shift is structural.
How will AI-native banks be different
Most leading banks today appear structurally similar. Each bank has a sleek mobile app, an API layer, digital-first journeys, a conversational chatbot, and a digital transformation story. The advantage that digital once created has plateaued. Then, how will banks differentiate?
On the surface, not much will change. The app will still be there, the branch network will exist, the API layer will continue, and the digital-first journeys will keep chugging. What will change is the intelligence that underpins every interaction.
The quality, speed, and relevance of attention delivered to each customer will improve meaningfully.
Anticipatory attention, grounded in the customer’s context and well-being, will become the defining capability. It may well become the only moat that does not get commoditised.
What this transition requires
The shift to AI-native banking is already entering boardroom conversations. The window for first-mover advantage will not remain open for long. The transition to AI-Native won’t be just adding another layer. This requires a fundamental rethink of how intelligence is embedded across every interaction.
It begins with a unified customer data profile, a single source of truth.
To add to it, a real-time AI decisioning layer must interpret signals such as life events, cash flow patterns, and income changes, and initiate the right interaction before the customer expresses the need.
The experience layer must become dynamic and adaptive, changing with every interaction based on context. Even here, the digital assets will need to be dynamic, with post-login content changing each time the customer logs in based on insights.
And then there is a layer most banks have not started thinking about – the agentic interface.
Customers may no longer find you in search results and then land on your app or website. They will arrive through social environments or AI agents that have already evaluated options. If your products are not structured, discoverable, and machine-readable, you may not enter the consideration set.
In this environment, visibility alone is not enough. You have to be chosen.
AI is everywhere in conversation today. The more important question is whether you have clearly visualised what it means for your bank's future.
“Congratulations, you are a digital-first bank. But it is not enough.”
When a customer’s AI agent evaluates a credit card, will it find you and choose you? You have millions of customers and vast amounts of data, but how many truly feel understood?
Your platforms have scale, but do they create ongoing relevance? Are you building a differentiated institution, or becoming invisible infrastructure in a more intelligent ecosystem?
These are the questions that will shape strategic priorities. And the institutions that address them early will build an advantage that is difficult to replicate.
This is the transition the industry must now actively navigate. Moving from digital capability to intelligence-led differentiation, building unified data foundations, embedding intelligence across the experience, and ensuring discoverability and preference.
If any of these questions are keeping you up at night, they should be.
The shift from digital-first to AI-Native has already begun. The question is whether you are leading it or responding to it.
