Can a “Business Model Canvas” help in assessing AI-powered startups?
During the COVID-19 lockdown, I started learning ‘Machine Learning’ out of curiosity. It eventually became a habit, and now I cannot spend a day without learning something new in this direction. I also started looking up startups in the field of AI and found that Crunchbase and CBinsights provide thoughtful insights into how AI is transforming almost every industry. CBinsights released a list of startups in March 2020 called AI-100. I used the internet and some data analytics techniques to generate insights from this list. Additionally, I found it intriguing how these startups employ state of the art technology to provide solutions to the world’s most complex problems with their unique value proposition and revenue generation models.
AI 100 is a list of 100 top-performing AI companies of 2019–2020 that started small and have secured huge amounts of funding from key investors and venture capitalists like Google ventures, Founders Fund, Sequoia Capital, Khosla ventures, and Plug&Play tech. The performance of these companies has been evaluated by parameters like R&D strength, business relationships, earnings, innovation, and news sentiment analysis. The number of startups in the healthcare sector is the highest among all others. Other major investment choices are transportation, Financial instruments, retail & warehousing, NLP, and computer vision. As can be seen in the doughnut chart, among a total of 314 venture capitalists or early-stage investors, Google Ventures and Founders Fund top the list with investment in 8 and 7 startups, respectively.
Most early-stage investors have invested significantly in transportation, healthcare, and cross-industry tech (see the chart below). The cross-industry tech sector has been funded heavily because its scope has virtually no limitations. For example, a cross-industry tech startup, Graphcore, provides services in both finance and healthcare. It offers intelligent processing units for algorithmic trading and also for early disease detection. And, it is just one example of one startup. Their scope is virtually limitless. The transportation sector includes startups working on autonomous vehicles and advanced logistics solutions. One reason it is enormously funded is its inherent capital intensive nature. As compared to transportation, healthcare is not that capital-intensive, but their funding is almost equivalent. That signifies the significant share of an investment gone into human resources and research in healthcare. This trend doesn’t seem to change soon as nearly all the startups have started working on solutions for the current pandemic situation. For example, Atomwise, an AI-powered drug discovery startup, has partnered with the world’s leading research teams working on COVID-19 vaccine.
If you know Simon Sinek, you will say “Why” comes first. Definitely, “Why” is imperative while building a startup. But, for me, the founders’ rationale behind building these top-performing AI ventures should be almost indisputable at this stage (Let’s forget about Theranos for now). Therefore, “Why” is an essential but not-that-interesting kind of question. But, more interesting is “How.” Wouldn’t it be interesting to know how their business models work? Analyzing business models will give answers to many questions, such as:
How their value proposition strategies are different from traditional tech companies?
Why 65 of these 100 startups are from the USA alone?
Is there any similarity between the type of business model and investors’ choice for startups?
Can one predict by its business model whether a startup is going to be a successful one?
Why “where to invest” is a question as crucial as “What to build” for giant tech companies?
Which companies are more agile and can adapt to disruptive changes?
This stream of questions does not seem to end. One way to find out the answers is to fit the business models of these startups to the famous “Business model canvas” developed by Alexander Osterwalder, a swiss business strategist. “Business model canvas” is a tool to visualize how resources are used to make money with a unique value proposition strategy. The picture below shows Alexander explaining the basic building blocks of a “business model canvas.”
The most exciting block here is the Value proposition of these startups. Augmentation in the computational power of machines and the development of novel learning algorithms have changed the way these businesses provide value. Take, for example, the idea of effectively using a smartphone as your personal clinical laboratory. One of these AI100 startups, healthy.io, has developed applications that can perform a urinalysis using a smartphone. This service could not have been possible without large-scale image processing and pattern finding algorithms. Advancement in AI is more or less advancement in how we use technology. Moreover, what exactly goes into building these startups is a topic of research itself.
In later articles, I look forward to writing on the value proposition of startups in different sectors and dive deeper into their business models to answer the questions asked in this article. I believe it is vital to keep abreast of business models of these companies for anyone looking forward to building or funding similar startups in the future. But anyway, for anyone interested in AI, it is fascinating to see how they work.
Thanks for reading!
PS: This is my first article on Medium. I’d love to hear your comments :)
References: 1) https://www.cbinsights.com/research/artificial-intelligence-top-startups/ 2) www.strategyzer.com
Tools I used: 1) Py Pandas 2) MS Excel
