2020’s: the decade of AAA digitization
(‘AAA’ : Automation powered by AI and API)
Today’s is a fascinating era, when technology innovation as well as technology adoption is accelerating at a tremendous pace. This goes much beyond cool technology inventions happening in academic labs or in big tech companies. This is about main street industries adopting technology to transform themselves digitally. This movement has been largely boosted by the advancement of AI and data science techniques along with software innovations making it easy to develop and deploy AI at scale (e.g., by innovators like H20.ai), that enable automation of tasks and processes at various degrees of sophistication. Equally effective have been the advances in secular “compute everywhere” technologies (like that of Rancher) and API technologies enabling ‘low-code / no-code’ software development, vastly extending the reach and scale of digitization (e.g., by platforms like Postman).
This combination of AI and API — the power of AI to understand unstructured data and processes, and embed that intelligence via APIs seamlessly in existing or new applications — is truly enabling digital automation across industries. Intelligent automation is not about replacing humans by machines, it’s about using machines to complement human judgment, and enable use cases that were not possible before, while significantly increasing efficiencies and reducing proneness to human errors.
While we have been seeing glimpses of such digitization and automation over the last few years, we expect that to grow into a tsunami over this decade, transforming several trillion dollar industries, powered by innovations from startups challenging the status quo: transportation and logistics (e,g., Delhivery, Pando, Hypertrack), real estate and construction (e.g., Infra Market), education (e.g., Unacademy), travel and hospitality ( e.g., Headout ), financial services, insurance ( eg., Turtlemint), and healthcare ( eg., Clover Health, Imagen). We will see many contextual and vertical oriented AI innovations to cater to specific industries and use cases. Likewise, we will also see innovations automating horizontal cross-industry functions like customer service (e,g. Observe.ai).
What will it take for entrepreneurs to be able to contribute to and capitalize on the digitization wave? Back to basics: user-centric approach and product-driven mindset. Start with answering these questions: what is the problem I am addressing; whom am I addressing it for; why is this problem worth solving; what should be my solution that will be easiest to use yet fastest to get value from (however sophisticated the underlying technologies being used might be). For AI driven automation, it is also paramount to have access to the right kind of data for training the AI models correctly. In absence of right data, even the most advanced AI algorithm will fail to yield the right result. While understanding of the domain is needed, domain experience is not a must. What is most valuable is an intelligent and agile mind, obsessively committed to solving the problem.
Jishnu Bhattacharjee, Nexus Venture Partners
Disclaimer: the companies mentioned here are portfolio companies of Nexus Venture Partners, where the author is MD.
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