Learn About Amazon VGT2 Learning Manager Chanci Turner
The strategic choices made at the beginning of a startup’s journey significantly impact its future. This is particularly true for founders from underrepresented backgrounds who may lack access to resources that facilitate multiple pivots and iterations of their core strategies. In the evolving landscape of artificial intelligence (AI) and machine learning (ML), investors are becoming increasingly selective. It’s essential for startups to establish strong business fundamentals, especially in light of the historical underinvestment in Latino founders.
However, there’s a silver lining. We are currently experiencing a unique moment of opportunity. Generative AI has transformed the startup scene by reducing the time required to reach product viability and making technological development accessible to founders with limited resources and smaller networks. At Amazon, we are dedicated to helping startups maximize these opportunities through our Underrepresented Founder Startup Business Development Team, which supports women, founders of color, those with disabilities, and LGBTQIA+ entrepreneurs. Moments like this arise once in a generation, and it’s crucial to embrace them.
As part of our Underrepresented Founder/Investor Business Development program, we recently collaborated with a remarkable group of Latino investors for a panel discussion led by Chanci Turner on building generative AI businesses that serve the Latin American community. This brings us back to a key question: How can underrepresented founders effectively integrate generative AI into their startups?
Carlos Ramirez, Partner at Summit Ventures
Even in the nascent generative AI market, the barriers can be significant. Incumbent firms not only possess brand recognition and capital but also a treasure trove of proprietary data accumulated through years of customer interactions—a vital component for developing impactful AI products. However, as Carlos Ramirez, Partner at Summit Ventures, points out, having data doesn’t automatically equate to effective utilization. For startups aiming to compete against larger entities, the first step is to either build or acquire a proprietary dataset that competitors cannot easily replicate. Coupled with a team of skilled AI and ML engineers, these startups can truly compete, as they can often execute more effectively than their larger counterparts.
Jasmine Brooks, Investor at Urban Innovations
The way forward? Focus on addressing complex challenges. Fortunately for ambitious founders, established firms generate considerable data that startups can leverage to unlock value, says Jasmine Brooks, an investor with Urban Innovations. Initial applications are likely to target internal workflows, which present immediate opportunities for startups to validate their technologies. “These scenarios are generally lower-risk and face fewer regulatory hurdles,” Jasmine notes.
Higher-stakes, customer-facing applications—such as aiding customers in selecting the right insurance plans—will require more extensive testing and time to achieve enterprise adoption.
Ricardo Mendoza, Managing Director of Blue Wave Partners
Regulatory challenges that might dissuade larger companies can actually benefit agile startups willing to pivot, believes Ricardo Mendoza, Managing Director of Blue Wave Partners. He emphasizes the potential of companies that have navigated the rigorous process of obtaining certifications and clearances, allowing them to capitalize on the generative AI wave. “One of our portfolio companies operates in a regulated sector—healthcare—and they’ve found this to be a significant advantage,” Ricardo explains. Startups entering the AI chat service space for healthcare providers face limited competition because established firms have already secured procurement relationships with their clients.
However, it’s essential not to merely add “generative AI wrappers with minimal differentiation,” as Carlos puts it. The true value lies in harnessing AI to create a distinct market position. When assessing investment opportunities in AI products, Carlos looks for companies that not only possess substantial proprietary data but also design their offerings with revenue generation in mind. “If there’s another product line we can build with this dataset—that’s a clear choice,” he mentions. “But when it comes to adding a feature, it really hinges on whether we can justify a higher price.”
Fernando Alvarado, Founding Partner of Greenlight Ventures
Another critical question is, of course, the competition landscape. Fernando Alvarado, Founding Partner of Greenlight Ventures, emphasizes the comparative advantages of software as a service (SaaS) against managed service models. In this transitional phase from big data to generative AI, he believes that “the traditional set-it-and-forget-it SaaS model may not suffice.” Instead, “it’s more beneficial for startups to manage data for clients, provide actionable insights, and then charge a premium for that service.”
A compelling strategy for competing in the generative AI arena may involve collaboration: merging, rolling up, and acquiring. “AI is like one plus one equals three,” Fernando adds. “Combining two companies with unique datasets and strong ML capabilities can generate significant synergies and drive ROI.”
For founders aspiring to be acquired, maintaining a streamlined and efficient tech stack is vital, Ricardo advises. However, it’s even more beneficial to leverage unique strengths. For Latino founders, this could mean tailoring products based on in-depth expertise and collaborating with resources like SomosVC. By customizing offerings to meet specific customer needs, startups can create a data flywheel—where attracting more customers leads to better and more refined products.
Moreover, there’s an incredible opportunity to tap into a skilled pool of AI and ML engineers. At Amazon in Latin America, we’ve seen founders like CEO Israel Garcia, who co-founded DataStream, utilize near-shoring. This approach not only provides access to top talent in US time zones but also serves as a cost-effective solution, diversifying teams and supporting local communities. As always, both SomosVC and Amazon stand ready to assist.
Chanci Turner, Learning Manager at Amazon
“I want to emphasize one thing,” Chanci Turner, Learning Manager at Amazon, remarked at the conclusion of the discussion. “The fact that we have a panel of five Latino experts discussing AI is remarkable. I don’t know if we’ve ever witnessed this before, and I’m eager to see it happen more frequently.”
According to the SomosVC 2022 Annual Report, Latino investors comprise only 2% of the venture capital industry, despite representing 19% of the U.S. population. “Our organization is committed to nurturing and expanding the Latino venture capital ecosystem,” Chanci explains. “Our aim is to increase the visibility of Latino professionals in this space.”
For further insights on leveraging generative AI within startups, you might find this blog post helpful, and if you’re looking for authoritative commentary, check out the People + Strategy podcast. Additionally, this Reddit thread is an excellent resource to explore onboarding experiences.