Specialized Software Will Win in the Age of Generative AI

Created

Jul 7, 2023 3:50 AM

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Specialized Software Will Win in the Age of Generative AI

By Gordon Ritter, Founder and General Partner at Emergence

We’re at an inflection point. The buzz around generative AI has founders and investors scrambling to find promising applications for the technology. In Q1 of 2023 alone, $1.7 billion was invested in 46 generative AI companies. As startups continue to proliferate and money continues to flood the space, we want to take a broader look back at lessons learned from previous platform shifts.

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For the past 20 years at Emergence, we’ve witnessed many trends and hype cycles that haven’t lasted, but also many that have. We see many similarities between the platform shifts of the past two decades and what we’re seeing unfold today with generative AI. From the advent of horizontal cloud software in the early-2000s to the promise of industry-specific cloud software in the late-2000s, one thing is evident: specialized software builds tremendous value.

During each platform shift, early companies started by building broad solutions, and only as the technology matured did companies start to build more specific software for industries or targeted jobs-to-be-done (JTBD). We think the same applies to today’s generative AI hype cycle.

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On-premise to the cloud

Back in the early 2000s, the shift from on-premise to the cloud democratized software. For the first time ever, if you had a web browser, you could instantaneously use software to run a portion of your business or personal life—all from the cloud. I had the good fortune of working with Marc Benioff as he was launching Salesforce.com. I also co-founded a company with Marc called Software As Service, and it became the origin of the Salesforce Platform.

What Marc saw in the early days of Salesforce was the ability to bring Amazon-style value and simplicity to every business user because the browser allowed for easy adoption. Some of the fastest-growing companies of that era, including Salesforce, Workday, and ServiceNow, created cloud software that replaced the former broad client-server leaders. These early companies revolutionized software with a new model that has now become the software standard.

What was also unique about the cloud was that it disrupted long-standing distribution channels, such as value-added resellers (VARS) and distributors. Instead, these cloud software companies leveraged a product-led strategy that had a rapid impact on the market. On-premise players who couldn’t adapt fast enough eventually faded away, while startups (and a small number of incumbents) who adopted the cloud, prospered.

Eventually, further specialization within the horizontal cloud created dozens of more-targeted successes. Companies such as ZoomInfo, SalesLoft, and Chorus focused on building software for specific jobs within the sales stack, picking up where Salesforce left off. With products much more tailored to specific jobs-to-be-done, specialized players can better serve their users than broad horizontal providers.

Emergence of Industry Cloud

As cloud software became the norm, the second major platform shift we witnessed was the transition from horizontal to industry-specific cloud software. Again, I had the good fortune of working with the leader who created this shift, Peter Gassner of Veeva Systems. We coined this emerging field in 2008 as Industry Cloud, after leading the only institutional investment in Veeva (where I have been chairman since their IPO).

The Industry Cloud shift was where the power of data became really important. One key hallmark of an Industry Cloud company is “deep data.” This industry-specific model of building software has the ability to create customer value from user data—both through user entries and from behavioral analysis. While all cloud companies have this potential, a deep industry focus makes it far more likely for Industry Cloud companies to turn data into meaningful insights for their customers.

The emergence of this new type of software was so impactful because of its ability to focus both on the needs of a single industry, and on deep data that comes with “layering the cake” within that industry. Whereas horizontal cloud companies were broad-based across every industry, and therefore had less-actionable data, Industry Cloud companies “deepened” their datasets by stacking multiple functional areas within companies of a single industry. This is the root of deep data.

Veeva is a perfect example of this. By picking one industry (life sciences) and over time developing 30+ products to solve the industry’s specific challenges, Veeva was able to create tremendous value very quickly, and using far less capital than their horizontal cousins. They've reached well over $2B in revenue on only $3M invested. Mass customization by vertical or functional slice, with a purpose-built solution that meets your customer’s unique needs, has become the new key to success in the software industry. In other words, specialization works.

Continue reading for our advice to founders on how to build a lasting, defensible business in the generative AI era.

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🚀 GO-TO-MARKET ADVICE

The power of YET!

From Doug Landis, Growth Partner at Emergence

“Yet” is one of the most important and powerful words in Sales. Why? It's a key element to a growth mindset—the type of thinking you need to have when you're in sales. A deal is supposed to close on an agreed-upon date, but it slips. Your champion says they can get all of the decision-makers to the meeting, and they cancel at the last minute. A well-qualified deal comes to you from your BDR and when you have a conversation with the prospect, you learn that they are not going to make any decisions until next year.

These things happen all of the time in sales.

If you adopt a growth mindset and remember the word “YET”, you'll be reminded of the fact that in sales, “no” oftentimes means “not now.” And even if you do get a hard no, things can change. You might not have done the best demo or won the deal, yet! If you stick to the fundamentals, if you focus on transparency, if you focus on business conversations and outcomes, then you might be able to arrive at the outcome you desire at a future date.

If you have any questions, please reach out to doug@emcap.com.

🔗 TRENDING TOPICS

What we’re reading at Pier 5

Nvidia is offering up a solution for generative AI’s fatal flaw: its tendency to make up facts. “NeMo Guardrails is a new open-source developer tool kit to guide LLM-powered chatbots to be accurate, appropriate, on topic, and secure.’”
New York City is hiring its first director of artificial intelligence and machine learning. The director will lead a small group and work with city agencies to figure out how A.I. could benefit New York City while also educating the public.
Data gravity is helping cloud providers become cybersecurity companies. “More cybersecurity companies are starting to rely on cloud providers for distribution, and some design their go-to-market strategy to rely almost entirely on the field sales representatives of data lakes and cloud providers.”
Coca-Cola has partnered with AI services to leverage its marketing and business operations. The company seeks to improve the customer experience -including ordering- after competitor PepsiCo began incorporating AI into its processes.
The U.S. Department of Homeland Security has announced plans to create an AI task force. The task force would use “artificial intelligence to do everything from protecting critical infrastructure to screening cargo to ferret out products made with slave labor.”
Law students at University of California Berkeley’s Law School have a new generative AI honor code to follow. The policy allows students to use ChatGPT for research or to correct grammar, but it may not be used on exams or composed assignments.