Anis Uzzaman (アニス・ウッザマン) is the general partner and CEO of Pegasus Tech Ventures | President of the Startup World Cup.
There is no doubt that artificial intelligence is changing the way people run their businesses, develop technology and invest. Although some jobs could be negatively affected, I believe AI will create opportunities and have a net positive impact on the economy. AI can help invent new technologies, make the world more productive, and ultimately make a positive impact on the world.
According to a PwC report, AI could potentially help 15.7 trillion dollars for the global economy by 2030. By then, the report says, local economies around the world are expected to grow by up to 26% thanks to AI. This growth is expected to be primarily driven by product enhancements leading to increased customer demand, accounting for 45% of the economic gains.
This explosion in AI presents a major opportunity for venture capital firms. Based on my experience investing in this area, here are some of the trends that venture capital firms should watch for, as well as key considerations that are important when considering an investment in a startup in AI.
AI Trends
As the AI industry rapidly evolves, there are several trends that I consider critical for venture professionals to understand. Knowing these trends can help investors anticipate consumer demand and where the market might go.
• AI for edge computing: The combination of AI and edge computing devices is steadily gaining popularity. Edge AI involves implementing AI algorithms directly on edge devices, such as Internet of Things devices or edge servers, instead of relying solely on centralized cloud computing. This trend helps reduce latency, improve real-time processing capabilities, and address privacy concerns by keeping data processing closer to the source.
• Explainable AI: As AI systems become more advanced, it becomes increasingly necessary to make their algorithms explainable and interpretable. The goal of explainable AI is to provide insights into how these models make decisions, particularly in critical areas such as healthcare, finance, and autonomous systems.
• Ethics and responsible AI: There are growing concerns about the ethical implications of AI technologies, such as AI algorithms, that reinforce bias. Ethical guidelines, standards and frameworks are needed to ensure the responsible development and deployment of AI. Companies must incorporate ethical considerations into their AI strategies to address these concerns and comply with regulatory requirements.
Industry Spotlight: AI for Robotics
Despite the abundance of talent and capital in this sector, AI for the robotics industry has not yet reached the inflection point necessary for adoption. However, this could change as software capabilities begin to mature. The e-commerce industry is beginning to adopt these solutions at scale for use cases such as pick-and-place, truck unloading, automatic bagging, and depalletizing.
Another emerging trend in this sector is the emergence of humanoid robotics. Companies like Tesla, Figure AI, 1X Technologies, and Agility Robotics are attracting a lot of attention in the venture capital community. One of the main enablers is the integration of vocal and visual capabilities of large language models.
Important Considerations for Venture Capital Firms
VCs interested in investing in AI should understand several key factors relevant to this sector:
• Understand AI technology: It is important to have a solid understanding of different types of AI technologies, such as machine learning, natural language processing, and robotics. Understanding how these technologies work and their potential applications is crucial to evaluating investment opportunities.
• Scalability and integration: I generally advise thinking about how easily AI technology can scale to meet growing demand. One sign that AI technology will scale well is its ability to efficiently handle larger data sets and increased computational demands without sacrificing performance or accuracy. If an AI model or system can maintain consistent performance levels as data volume or task complexity increases, this suggests that the technology is scalable.
Today, one of the most important ways to measure scalability is whether a business can access the necessary computing and whether it can provide real-time inference. Another important consideration AI now faces when it comes to scalability is energy, and ideally clean energy. It is now increasingly important for AI companies to develop their energy plan to ensure they can scale with demand.
• Business model and monetization strategy: Venture capitalists need to understand the startup’s business model and how it plans to monetize its AI technology. Whether through licensing, subscription models or other means, a clear and viable monetization strategy is crucial for long-term success.
• Industrial applications: AI has applications in various industries, including healthcare, finance, logistics and marketing. Investors should be aware of the specific focus of AI-driven companies, as different sectors can present unique challenges and opportunities.
For example, in my experience, a financial company may face challenges related to managing complex regulatory requirements and compliance standards while leveraging advanced AI technologies. Logistics companies face the challenge of optimizing complex and dynamic supply chain networks in real time. Unlike other sectors, logistics involves managing the movement of goods, vehicles and resources across large geographic areas, often with many interconnected nodes and stakeholders.
Venture capitalists can’t afford to ignore AI
AI is shaping up to be a revolutionary force that increases productivity, fosters creativity, and gives a competitive edge to startups and technology companies. It is not just a technological instrument but a strategic area for venture capital firms that want to thrive in the digital age.
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