Public has built the technology that makes constructing a multi-asset portfolio, fast, secure, and frictionless. As CFO, Sruthi oversees finance, data, and people operations. Previously, she was the VP of Strategic Finance at MoneyLion, the fintech startup and challenger bank. She was MoneyLion’s first finance hire in 2017 following its Series A, and built the team that forecasts and monitors the firm’s financial performance, overseeing financial planning, capital optimization, fundraising, and Board engagement. She also worked on mergers and acquisitions for RBC and Goldman Sachs. Sruthi also serves on the Board of the nonprofit Women Creating Change.
As the Chief Financial Officer of Public, the investing platform built for serious investors, Sruthi Lanka operates at the intersection of finance, technology, and leadership. In conversation with The WIE Suite, she explored how AI is reshaping decision-making – from building data-driven portfolios to creating more efficient, experimental, and inclusive teams.
“We’re entering a world where building a company can take as little as three to five people,” she noted. “AI allows us to do more with less: faster, smarter, and with fewer resources than ever before.”
Below are five ideas that define her framework for thinking about AI not as a threat to human expertise, but as a co-investor in the future of work.
Sruthi is unequivocal that AI’s power lies in collaboration, not substitution. “AI isn’t here to take over your expertise, it’s here to extend it,” she said. Within her own finance organization, she positions AI as a “junior assistant” – a fast learner that needs oversight and feedback.
Her advice to leaders: use AI in domains where you possess enough expertise to verify its work. “You wouldn’t send your intern to handle your biggest client alone,” she added. “The same principle applies here.” This disciplined partnership, where humans set the direction and AI accelerates the process, anchors Public’s approach to innovation.
At Public, experimentation is a leadership expectation. Sruthi described a company culture where trying, failing, and refining are celebrated rather than hidden.
One example she shared: a controller who used AI to automate a time-intensive spreadsheet. “It used to take three hours. Now it takes three minutes and she’d never written a line of code before,” Sruthi said.
That story became emblematic across teams. By publicly spotlighting “failure before success,” Sruthi’s organization normalized curiosity. “Talking about AI is one thing,” she reflected. “Actually using it every day – across every function – is what sets companies apart.”
Behind every AI success story lies something far less glamorous: data hygiene. Sruthi described how Public’s advantage in building its AI tools began years ago with the disciplined aggregation of unstructured consumer data.
“Garbage in, garbage out,” she said plainly. “AI can only enhance what’s already accurate.”
At Public, daily reconciliation and centralized data warehousing ensure integrity before automation begins. Yet, as she emphasized, even smaller companies can emulate this principle without massive infrastructure. “Whether it’s a spreadsheet or a data lake,” she said, “the key is consistency and checks. AI can even write the rules that keep your data clean.”
Public’s “natively fractional” model, allowing users to invest in even the smallest slices of major assets, embodies how Sruthi thinks about product design in the age of AI. “Fractional access isn’t just about affordability,” she explained. “It’s about flexibility.”
That underlying architecture enables Public’s AI to build customized portfolios on command. A user might type, ‘Give me a basket of all companies that IPO’d in 2025’, and instantly see performance benchmarks and back-tested results.
For Sruthi, this principle applies beyond investing: “When you break something into its smallest possible unit, you open up new ways to repackage, personalize, and scale it through AI.”
Sruthi’s own routines are an illustration of immersion, not abstraction. “My entire workflow has become AI-native,” she admitted. From preparing board presentations with ChatGPT to building internal automations in Claude, she relies on AI as both strategist and executor.
That integration extends to her personal life, where she uses an AI assistant to coordinate her children’s schedules. “I have an EA for work, but I needed one for life,” she laughed. “In its ideal form, you won’t even know you’re using AI, it just quietly makes everything run better.”
Her approach reflects a conviction that AI is no longer a discrete skill but a professional mindset – one that blends technological literacy with human discernment.
Taken together, Sruthi’s framework redefines how leaders should engage with technology.
AI, she argues, is both a multiplier of expertise and a mirror of organizational discipline: it rewards curiosity, structure, and clear thinking.
“AI isn’t a nice-to-have anymore,” she concluded. “It’s a leadership responsibility. The teams who learn to use it safely and creatively will be the ones who build the next generation of companies.”
At its core, her vision of AI as a “co-investor” is less about automation and more about amplification; the idea that human insight, when paired with intelligent tools, can compound in value just like any good investment.
