A few months ago, Shekhar Kirani, a partner at the Venture Capital firm Accel, addressed startups, at a session hosted by SaasBoomi.
Given his profile, there was huge excitement and a buzz in the room.
Shekhar leveraged his many decades of nurturing startups experience and generously shared insights on a broad set of ideas. For instance, the importance of spending a few months at the Valley, business priorities in an AI-led world, “building” the magic in products, the significance of pivoting to newer ideas, dreaming big and getting VCs interested, and at every stage owning the outcome while climbing the archetypal mountain (read a startup’s journey to the top).
This blog tries to capture the key messages that resonate with startups.
To begin with, he emphasized the importance of spending a few months in the Valley. Approximately it works out to be 5k dollars: it’s a great investment. He pointedly asked around the room how many people had spent 3 months there in the last 3 years – a few hands went up and the excitement was palpable. Interestingly, it underpinned the great significance of physical presence in a digital-first world where everything is supposedly just a click away.
Rapidly shifting AI priority at large enterprise buyers
The big question that CIOs world over are facing – what’s their company’s AI strategy? Market advancements are rapid, and companies often struggle to keep pace with AI advancement. Even Boardroom discussions are dominated by AI and the constant ask is – what can we do to stay ahead of the curve? The need for every company to be an AI company is growing stronger by the day and founders are desperate NOT to be seen as laggards.
While this constant pressure can be overwhelming, and one can get lost in the hype and noise, the timing to be an AI company couldn’t have been better. Broadly, in the evolutionary stages of AI, a company can be:
- AI-first (Auto-pilot)
- AI-assist (Co-pilot)
- SaaS + AI (sprinkle AI on top of your SaaS – this is basic)
Think BIG!
“Most of the time, we don’t fund companies because they do not think big enough.” A hard-hitting statement that he made to drive home the point. He reinforced: “Remember, it doesn’t cost to dream big, it only costs to build big, and if you bring in the right business plan and ingredients, we are here to support you.”
Today human expertise can be replicated by AI. There’s a margin in this model but time’s running out and tomorrow, when the pricing falls dramatically (of AI tools) it may not seem so attractive, and it may become a red ocean.
Now’s the time to replace human-intensive work with AI tools and save dollars for the user company. A new trend: many companies are approaching marketing agencies to buy them out and acquire their solid customer base. With time, the processes of these companies have been well-defined, structured, and documented so human effort can be replaced with AI. A similar trend is seen in customer service agencies as well.
- Shekhar shared a few industry examples to drive home what it means to think BIG:
- Front desk management – this is huge. Every front desk worker in the US costs the company 50K USD per annum, at the bare minimum. Imagine if they can be replaced by AI. Zenoti tried to release some fancy AI features, and all the customers asked was how they could replace the front desk talent with AI. So, knowing what exact AI component the customer wants is a critical ask.
- Health care – this is yet another huge opportunity. The US spends 4 to 5 trillion dollars on healthcare. A substantial part of that is medical coding. And most of that work is done in India. There are thousands of companies in this space, working out of India and they have a strong grip on the end-to-end process. Can this work be done by AI-driven code generators?
- Insurance – this is another massive market ripe for disruption. Many processes, such as underwriting and claims management, and customers calling (to check how much insurance is approved, etc.) can be automated using AI. This could lead to significant cost savings – value creation that the startups building in this space can capture. RCM or Revenue Cycle Management is another space.
- Tax/ Accounting Consulting – Minimum Accountant charges are upwards of 200$ per hour. AI can replace a significant portion of that work.
- Legal space is yet another use case – ripe for AI adoption.
2. VCs don’t fund companies that target TAMs (Total Addressable Market) that aren’t significant. Sometimes, it’s a great idea backed by a very good product but the TAM is too small. This doesn’t attract VC funding.
3. What also happens is that founders want to climb a mountain but they realize midway that they are climbing a small mountain such as Nandi Hills. What to do? 3-4 scenarios can play out:
- The hill keeps growing (that is, they get lucky).
- They become profitable because it’s a small space, and someone buys them out later.
- They stay bootstrapped and profitable and use it to fund a different product.
- They give it to their team to run and step out to do something else.
4. Own the Outcome. It’s critical to take extreme ownership of the outcome.
These were some of the learnings shared from his experience and later it was most inspiring to see startups interacting with Shekhar Kirani, trying to get a deep dive.
This blog is based on a session conducted by Shekhar Kirani of Accel (about 2 months ago) for SaaSBoomi. It was an interactive session that brought in a lot of buzz from the participants (startups) as Shekhar shared his deep learning on setting priorities when everyone’s asking how can they be an AI company. He also emphasized the great significance of thinking big!