Trends

Jack Kokko: Creating a copilot for market intelligence teams

Marcelo Bigal: Always putting patients first

Strategy

Lenskart: A vision for e-commerce success

A vision for e-commerce success

Feature

Building high-performing teams in the age of AI

Video

Data

CHRO Survey: Despite layoffs, talent is still king

Despite layoffs, talent is still king

Data Analysis

2022 Milken MEA Summit: Tech Investing Panel

Scaling across borders

Wes Schroll: From startup to category leader in a crowded market

Mapbox: The fastest route to success

AI Stack

SambaNova: Dancing with AI

Venkat Sathyamurthy: A mantra for AI success

Investing in biotechnology in 2025

Podcast

CHRO Survey: Grappling with changing employee expectations

Inside the SoftBank Vision Fund portfolio ecosystem

CFO Survey: Capitalizing on a brighter economic outlook

Nancy Stagliano: Bringing AI to life

CEO Insights: Thriving in the world of hybrid work

Roundup

CEO Survey: Prepping for a rebound

Prepping for a rebound

Efficient marketing that moves the needle

Deidre Paknad: Redefining success metrics

CEO Survey highlights: Entering 2025 with optimism and caution

Making responsible and ethical AI a priority

Data and ML are creating a golden age of drug discovery

Seizing the generative AI moment

CFO Survey: AI takes center stage as economic woes recede

Generative AI takes center stage as economic woes begin to recede

Brand new: How a new identity became a unifying force for LTK

A new C-suite mandate: Maximizing the AI opportunity

How the C-suite is tackling a new mandate: Making the most of AI opportunities

Avi Meir: Why a bet on the power of human connection was key to success

The strategy behind the SoftBank Vision Fund

Starting at discovery

Be humble and keep learning

IPO Readiness: Lessons from the field

IPO readiness: Lessons from the field

CTO Survey: Generative AI is unlocking ROI in software development

Peter Chapman: Quantum computing’s coming of age

Ensuring human values are central to AI-driven progress

CEOs brace for a new wave of challenges in 2023

Apollo: Seeding a revolution in Kenyan farming

Seeding a revolution in Kenyan farming

Leading a high-growth company through an economic downturn

Doubling down on marketing in an uncertain environment

CTO Survey: Targeting AI, CTOs pursue different approaches

Job&Talent: Hacking global expansion through M&A

Aaron Tan: How AI is driving used car sales in Asia Pacific

Clearing the path for AI adoption

Thirteen countries, one culture

CHRO Survey: Hybrid work statistics say it’s here to stay, and employees are in the driver’s seat

Cloudbeds: The art of calculated risk

The art of calculated risk

Leveling the financial playing field

COVID-19’s impact on technology

CTO Survey: AI budgets surge

CFO Survey: Navigating toward growth

Remaking the last mile of e-commerce

CFO Survey: How CFOs are navigating a changing market

Paper’s fast learning curve

Glean: Competing at the speed of AI

CHRO Survey: Hiring is back on the front burner — selectively

Turning IoT’s promise into reality

Gary Beasley: Finding opportunity in a cooling market

Job van der Voort: The future of work is remote

CEO Survey: As economic outlook brightens, global uncertainty casts a shadow

The rapid rise in opportunities — and risks — sparked by artificial intelligence has pushed oversight of AI into the C-suite. In many cases, companies are creating new positions with titles like “Chief AI Officer” or “Head of AI.” Around one-third of medium to large enterprises have already appointed someone for this role or are actively recruiting for it, according to recent research by Foundry. And the White House recently announced that federal agencies are required to appoint a Chief AI Officer. In other cases, responsibility and oversight of AI ladders up to an existing C-suite position — most often the Chief Technology Officer.  To gain deeper insights into the role and into how companies are organizing themselves to make the most of AI, we recently spoke with two executives who are leading AI initiatives at high-growth tech companies. Craig Martell joined <a target="_blank" href="/portfolio/cohesity">Cohesity</a>, a Silicon Valley–based, AI-powered data security and management platform, as CTO in May 2024. Previously, Martell served as the Chief Digital and Artificial Intelligence Officer (CDAO) for the U.S. Department of Defense, and held senior roles at Lyft, Dropbox, and LinkedIn. Debdoot Mukherjee joined <a target="_blank" href="/portfolio/meesho">Meesho</a>, a social commerce platform based in India, as Head of AI and Demand Engineering in March 2022. Mukherjee oversees the company&#039;s efforts to make its e-commerce marketplace smarter and more efficient through the use of AI. Mukherjee previously held leadership roles at ShareChat, Hike, and Myntra.

<h2>What are your organizations doing with AI? </h2>Martell: At Cohesity, we think about AI in two pillars. The first is our platform AI: good old-fashioned work-a-day AI that, since the founding of the company, has managed, protected, and secured data. It includes ransomware anomaly detection, which looks out for behavior patterns that could indicate an attack. We also use AI in our core product for insights into data. Our generative AI agent, Cohesity GAIA, which we launched in February, lets you have a conversation with your data. You can quickly perform a financial check, for example, or assess your cyber resilience. You can also get summaries of documents to help you train new employees. Mukherjee: Meesho is a marketplace that connects users and sellers. The more effective that is, the better value we deliver to both groups. And AI supports every leg of Meesho’s e-commerce journey — whether for the user/shopper, supplier, or delivery partners. With AI, we tailor individual shopper’s journeys by effectively gauging their needs. We cater their homepages and widgets to their taste and interests. Many of our users in India use vernacular languages and nuanced expressions. They aren’t always keyword-search savvy, and use long sentences in their searches. They browse a lot: they’ll keep scrolling to discover products. We apply AI and machine learning to understand their intent and serve relevant products. AI also helps catch potential fraud on the platform.For the sellers, AI helps list and price their products correctly. We also use AI to optimize the entire delivery process, from personnel and partners to routes.

<h2>What does your role entail? </h2>Martell: I took this role, in large part, because very early on, Cohesity’s founder, Mohit Aron, had a vision about AI being able to do analytics on top of secondary data. Think about the difference between primary and secondary data: primary data is the small, visible part of the iceberg and secondary data is the massive part that’s under the water. That secondary data contains your company’s history, evolutions, and data you’ve archived. It’s a treasure trove for building predictive AI models. My job is to think about all the ways we can provide that value to our customers. Mukherjee: I lead Meesho’s AI organization, which is just over 50 people, and also an engineering team, which is responsible for user growth, shopping experience, and client platforms. When I joined two years ago, I focused on hiring and scaling the team, which has grown to more than twice its size. I also assess the needs of the business. From the beginning, I picked projects where AI could make a large impact — that helped earn the confidence of the business. These projects were tightly connected to the core flywheel of the company and impacted core workflows. They were also great opportunities to gather data. More data means better training models, and better models make the experience even better.

<h2>AI’s potential is so vast and touches everything from operations to product. To fully seize the opportunity, should companies centralize AI oversight or distribute it across the organization? </h2>Martell: It depends. I think for a smaller company, you should have some centralized leadership to ensure alignment. At larger companies, like ours, centralizing could become a blocker. You want some centralized leadership to make sure that you can give a cohesive story externally. But internally, you should let 1,000 flowers bloom. At Cohesity, some ideas come from the office of the CTO, but many rise up from across the company. And their implementation is distributed across teams. So we have centralized leadership, but most of the work is distributed. We also lead internal education efforts to make sure that those teams have the right guardrails and are thinking about AI responsibly.Mukherjee: I recommend a centralized development and maintenance of a core safety layer. It’s the best way to address threats and provide a consistent baseline of protection across all AI solutions in the company. When new threats or ethical concerns emerge, the centralized team can quickly mobilize resources and expertise to address them. However, the central team must work closely with individual AI teams to understand their specific needs and constraints and adapt as necessary. Safety measures shouldn’t unnecessarily impede innovation or deployment.A decentralized implementation with centralized oversight also makes sense for aspects of responsible AI development beyond core safety. In this set up, teams can work more independently with the centralized leadership setting overarching responsibility objectives, metrics, and guardrails. It allows teams to innovate while still adhering to ethical and safety standards.

<h2>What’s the role of experimentation? </h2>Martell: My view is that we should be experimenting broadly and all the time. It varies by role and team, but it’s important to have folks exploring, with our customers, the problems that need solving. We should try things, and have our customers tell us if we’re on the right track. We always want to make sure our experimentation is tackling actual customer problems. Mukherjee: At Meesho, it all starts from the leadership — the CEO, CTO, founders — in betting heavily on AI. But picking the right AI projects is crucial because they require a fair degree of iterations to create impact. I’ve seen companies pick a problem that’s not a core issue. When you do that, you risk losing momentum, and you risk losing interest once the first set of experiments doesn’t work.

<h2>How has ROI played into the development and deployment of AI? </h2>Martell: The largest ROI we’ve seen so far is with the AI we use when we manage data — the bread and butter of Cohesity. We’ve also had great traction with GAIA in the months since launch. We’re now getting feedback from companies who have been using it, so we will be tweaking and augmenting it to make GAIA even more widely impactful. Mukherjee: We proved impact fairly early on, and that built trust and credibility. It helps that everyone at Meesho, from leadership on down, believes in betting on AI — because to take that initial investment needs a leap of faith. If you can stay the course till you see impact, you can then start to scale up investment in AI.

<h2>Is finding AI talent a challenge? And if so, is it a bottleneck for moving forward?</h2>Martell: We feel really lucky because as we hire new computer scientists we see how much the marketplace has changed. Talent comes out of school with multiple great AI classes under their belts. AI is no longer a foreign concept to anyone who’s not an engineer. Mukherjee: It’s getting easier to find good AI talent. Back in 2007, I began my AI career when ML was largely confined to research labs. Since then, the interest in this discipline has grown exponentially. It used to be a very mathematical field. You needed a rigorous mathematical and research background; an advanced engineering degree, even a Ph.D. Now the talent pool has expanded. AI courses have also matured — and that, combined with the availability of open source, means that knowledge is more easily and openly accessible.

<h2>Is the promise of AI overhyped?</h2>Martell: I’ve been working in technology for 30 years, and this is the most exciting it’s been. Generative AI is a fantastic breakthrough, and it’s one whose capabilities have been developing for a while. I also believe that people may want too much from AI systems, which, after all, are gathering data from the past to predict the future. Reasoning isn’t happening. There’s no intelligence there. When you ask a question outside the AI’s training data, you get randomly generated text. It’s important for us as users to be aware of that. Mukherjee: It’s an incredibly exciting time to embrace AI — whether you’re a user, practitioner, or researcher. The rapid rate of change is extra exciting. We at Meesho certainly feel it. We’re constantly revisiting where we are and where we want to be. Not just in our big launches and epochal moments, but in smaller daily decisions, too. It’s one of those things in our lifetime that is very significant. Embrace it and take full advantage of it.

Amid growing optimism, CFOs are stepping up investment and eyeing growth

CFOs - Q2 2024

Terms

Privacy

Regulatory

Portfolio

Team

Insights

Work With Us

Portfolio Careers

Sustainability

Presentations

Company

Contact

We use necessary cookies to make our site work. We would also like to set optional analytics cookies to help us improve our site by anonymously collecting and reporting information on how you use it. For more information on how these cookies work, please see our <a target="_blank" href="https://visionfund.com/terms#1&amp;cookie-policy">Cookie policy</a>.

How the C-suite is tackling a new mandate: Making the most of AI opportunities

AI leaders at Cohesity and Meesho discuss how they’ve organized themselves for maximum impact

Job&Talent: Hacking global expansion through M&A

Amid growing optimism, CFOs are stepping up investment and eyeing growth

The strength of 450+ leading tech companies—direct to your inbox