Cofounder, Fractal
Search every verified Pranay Agrawal interview, podcast appearance, and on-the-record quote — each transcript cross-checked by AI and human review to confirm speaker identity. In a December 2020 talk, Pranay Agrawal, cofounder of Fractal, discussed the role of artificial intelligence in business transformation. He stated that "AI alone is not enough to create value from AI" and argued that a combination of AI engineering and design is needed to realize full value. Agrawal cited estimates that AI could add up to three trillion dollars in business value and recover billions of hours of human labor. He also acknowledged concerns that AI could shift power toward capital and raised the question of how human beings would continue to contribute economically. Agrawal provided examples of AI applications, including a Japanese farmer who used a Raspberry Pi and TensorFlow to sort cucumbers with over 90 percent accuracy, and a product called Cure that applies computer vision to X-rays to detect diseases such as tuberculosis. He described Fractal's work with the Mumbai Municipal Corporation to create a data "cockpit" for COVID-19 response, and noted that by eliminating "digital friction" for a global telecom, Fractal helped increase digital revenues by up to 100 million dollars a month. He also mentioned that within two days, one large telecom transitioned 90,000 workers to remote work without a drop in customer satisfaction.
“AI alone is not enough to create value from AI; our belief here is that we need a combination of AI engineering and design to realize full value from AI.”
“Some estimates say up to three trillion dollars in business value will be added, and several billion hours will be recovered from doing things that machines can do.”
“One of the big fears in the world is that with AI more and more of the power will shift to capital — and what will happen to labor or how will human beings continue to contribute economically and be relevant?”
“He purchased a Raspberry Pi computer, downloaded TensorFlow from Google, trained the system and very quickly was up to 85 percent accuracy in sorting cucumbers — soon he was well into the 90s.”
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