@blissweb 16 December 2022 more from that month

Bringing on the Right Investors: What Every AI Startup Needs to Know Move these five things to the top of your pitch deck when seeking investors. It's a good time to be an early-stage investor, and it's an even better time to be an AI-first startup looking for funding. Investments in AI companies topped $77 billion last year globally, more than doubling from $36 billion in 2020. However, with more and more AI-first businesses launching and challenging market and economic conditions, it can be tough to stand out and find a partner ready to take your business to the next level. As someone who has both founded an AI company and now invests in early stage AI-first startups, I know how critical it is to connect with the right investors. Five things I consider before investing: When evaluating potential investment opportunities, I start with the basics: How big is the company's total addressable market, how strong is the founding team and how transformative is their vision (and how excited am I about that vision). Once I've answered these questions, I dig into all things AI. Here are five key areas I look at closely – and elements any AI-first company should pitch to potential investors: 1. Spotlight core AI intellectual property These days, almost all startups claim to be AI companies. It's my job to find out if they really are and so I evaluate: If AI / Machine learning techniques is/are core to the business, its products and/or its go-to-market strategy. If there is a company that creates unique intellectual property (IP) – products, technology and or services – built using machine learning, deep learning or computer vision, speech analytics etc. I also believe it's not enough to use off-the-shelf technologies. The team must have core domain expertise and should be able to build these complex models internally. Ultimately, I assess if the company authentically leverages AI and whether AI is even really needed to solve the problem the business addresses. If that's not the case, then the company isn't the right fit for my investment. 2. Highlight AI expertise on your team If a startup has AI IP, my next step is to determine if the company has the right technical team to back it. I evaluate if the company's team has the right domain expertise (e.g., the machine learning background to build and maintain the technology) and I will usually make a point of meeting with the company's Chief Technology Officer or Head of Engineering. Roles like data scientist and machine learning engineer should be central to the team structure – if these skills aren't available in-house, it's challenging to run a successful AI-first company. I also look at the org chart. Is there AI representation on the core founding or executive team? This is often telling and indicates how serious the company is about being AI-first. Team considerations go both ways. If you're an AI-focused company, you may want to bring on investors who have AI domain expertise and can be helpful with your AI and product strategy. 3. Position data as a competitive advantage Access to unique data is a must for any AI company I consider investing in. I want to know if the startup has proprietary data that doesn't already exist in the world and if that data is used to generate unique insights no other company provides. When speaking with investors, it's tempting to shy away from the detailed inner workings of your data. But we want to know It's important to highlight data in your pitch decks, such as how you acquire data (and at what cost), how you annotate/index data and how your data warehousing and infrastructure are designed – and how you're thinking about scale. For AI-first companies, data is often your most competitive advantage. Clean, reliable and scalable data ensures faster time to market for products, smarter analytics and more accurate reporting. 4. Value and promote diversity Diversity fosters innovation. Beyond AI, I explore company diversity and assess whether DEI principles are core to business operations. And diversity isn't just looking at age, gender and ethnicity, but also diversity of experiences and backgrounds. When I'm evaluating a startup, it's a red flag if the team lacks diversity and I call it out. If I do end up investing in a team that I believe could be more diverse, I will use my investor influence to ensure the company corrects this dynamic as it grows. Especially at AI-first companies, a diverse team decreases the likelihood that the technology developed will perpetuate racial and other inequities. We've all seen articles about how AI is racist or sexist and maybe you've unfortunately experienced this reality yourself. If an AI company values and promotes diversity in its ranks, my hope is there's less risk for these problems thanks to more diverse perspectives powering decision-making. 5. Meet economies of scale and scope Finally, I evaluate how the company could potentially evolve both in terms of scale and scope. When we think of scale, we examine how costs diminish over time as a business improves its ability to complete more tasks in better ways. But when we think of scope, we're exploring how a company can take what it's learning and apply it elsewhere – this is a particularly unique property of AI-driven businesses. With machine learning, companies gather super interesting data about specific use cases and customers. Over time, this data helps expand the scope of the business and potentially surfaces new products or services beyond initial focus areas. For example, if a company incorporates AI to help users find rental properties, data collected could offer additional insights into customers' larger financial situations. Perhaps information gathered through the rental process about credit scores can be leveraged to offer customers loan refinancing options or additional financial consulting services. AI is transforming every industry. As someone who has spent the last 20 years in this space, I'm excited to see how early stage companies continue to bring this technology to life. Maybe I'm even your next investor.