By Farhaan Tipu

In the still-humming early hours of a bright morning, Maya Singh, founder of a fast-scaling e-commerce startup, sat at her desk, coffee in hand, staring at her real-time dashboard. Her startup, just a few months old, had begun to show impressive traction. Sales were up, customer churn was down, and her burn rate was healthier than expected — but she wasn’t interested in comfort. Maya had no time for static spreadsheets or five-day forecasting cycles. She wanted clarity, now. Decisions, now. Outcomes, now. And that’s why AI was no longer a tool for her — it was her competitive operating system.

Now, that’s a fictional story we just narrated, but nonetheless a reality that AI and finance have now joined hands and together, are ready to spearhead the future.

In the story above, what Maya had realized early — which many founders are now waking up to — is that artificial intelligence in finance isn’t just another buzzword, it’s the velocity engine that powers modern leadership.

It’s true. In a world where decisions compound by the minute, AI compresses time, expands insight, and removes friction from the things that once took teams of people weeks to untangle.

When Goldman Sachs CEO David Solomon recently revealed (at a Cisco AI Summit in California) that AI can now generate 95% of an IPO prospectus in minutes, a process that used to take two weeks and a full team of bankers, the world noticed — but alert and innovative leaders already knew. They’ve been living at the edge, watching AI go from assistant to architect, enabling five-person finance teams to operate like 50.

For the first time, they felt that they’re working in one place instead of logging into separate systems and stitching data together. What has also impressed is how naturally MeeruAI fit into their existing tools. It didn’t replace anything — it connected the dots that were missing.”

The collaboration tools — notes, watchlists, and task links — sound simple, but they cut out duplicate work and keep everyone aligned. Having a consistent financial model across entities gives the customers confidence that leadership and teams are always working off the same numbers.

In a recent report, JPMorgan Chase revealed that AI tools like Smart Monitor and Connect Coach have already delivered nearly $1.5 billion in cost savings, slashed servicing costs by 30%, and tripled the productivity of their advisors. While Wall Street transforms with enterprise AI systems, startup founders are deploying leaner, scrappier versions of the same tech — often open-source or embedded in fintech SaaS — to play at the same level.

What’s fueling this revolution is more than efficiency — it’s strategic clarity. AI doesn’t just make things faster; it makes them smarter. Risk, for instance, is no longer something you discover in hindsight.

AI engines now monitor patterns across transactions, accounts, geographies, even IP addresses to flag suspicious behaviour before the damage is done. “We have also done our homework in terms of finding out what leaders foresee benefiting from MeeruAI in daily operations. And we have had some very insightful responses. One leader told us that the biggest change will be predictability. They’ll know each day if the close is on track, instead of waiting until the end to see what went wrong. Another said their daily meetings are no longer about status updates. The dashboard already shows who’s accountable and what’s overdue — so they focus on decisions instead. The important point is, seeing when data was last refreshed takes away second-guessing. People trust the numbers they’re analyzing.”

Insurance companies are doing the same thing at scale. As per reports, AIG CEO Peter Zaffino is transforming underwriting and risk modeling with AI, partnering with Palantir and Anthropic to create predictive, low-volatility insurance models that process what used to take days, in seconds. The goal? Fewer surprises, better margins, more confidence. Sound familiar? That’s the same mindset any founder brings to a board meeting.

It’s true that data will decide winners in the generative AI era. In this world, whoever has the clearest picture, the fastest model, and the cleanest data pipeline will outmaneuver everyone else. “The finance leader of tomorrow won’t just be a custodian of spreadsheets — they will be the chief enabler of intelligence and value creation, marrying AI’s speed with human values, context, and people-connect,” says Sai Gunaranjan Puranam, Group CTO, Lytus Technologies & COO, Lytus HealthTech. He adds, “When I speak about finance as an embedded function, I don’t mean it as a concept. I mean it as something we actually implemented, ran, and stabilized in practice. To give an example, in one of my previous organizations, we treated HR not as a support function but as a profit centre in its own right. When HR recruited for Sales, there was a clear economic impact — even if no physical money changed hands between the two teams. We built an internal accounting treatment to capture that impact in the P&L of each vertical. That shift made every function conscious of how it created value, not just how it consumed costs. We extended this mindset even into meetings. Over time, it created a culture where performance appraisal was continuous, not annual. You couldn’t just attend a meeting; you had to add visible value. To tie all of this together, we created the Mission Control Centre (MCC) — our enterprise control tower. It wasn’t a metaphor. It was a working system, a true value exchange.”

He further shares, “From those years, one principle that has stayed with me came from a previous mentor: ‘ATQ–GRA – Ask Thousand Questions, Get Right Answers’. That single idea shaped how I looked at finance and leadership. Business will always give you only 60–70% clarity; the rest is ambiguity. AI doesn’t remove that ambiguity; it only helps you navigate it faster, if you’re asking the right questions. And what is “right” depends entirely on the context you create.”

That’s why MeeruAI has spent a considerable amount of time and energy on addressing challenges or pain points. “We have learned that the close has always been a grind. Automating workflows means companies/leaders can shorten it without burning people out. Some of our clients shared how visibility has been the biggest frustration, but since with MeeruAI, issues show up in real time, they are able to resolve them before they derail them.

Finance processes can often feel disjointed. MeeruAI brings them together so that operations run as one coordinated flow. We have also had some clients tell us that they have spent too much time on process and not enough on insight, but z shifts that balance back toward analysis and decision support.”

But it’s not just founders who feel the pull of AI’s potential—it’s the institutions, the boards, the analysts who see the writing on the wall. The Commonwealth Bank of Australia made headlines when it reversed its decision to replace call center staff with AI bots after public backlash. Their executives admitted that full replacement wasn’t the future—augmentation was. The goal wasn’t fewer people; it was smarter people, armed with better tools. AI should elevate human potential, not erase it.