Selecting Ai-Genius & AI-Garbage: How to do it?
Artificial Intelligence (AI) is all the rage in business and venturing today. As in other emerging blockbuster technologies, there will be a need to sift through the landscape to discern between brilliance and mediocrity. Here are five critical questions that may help.
#1. Will AI-developed ideas improve the probability of venture success?
Entrepreneurship often places a disproportionate emphasis on ideas. A Wharton experiment tested whether AI could generate better ideas than students did. The results showed that AI produced a 47% success rate based on ideas that potential buyers would buy compared with 40% for students. However, is venture success more tied to entrepreneurial skills than the initial idea? In fact, among 85 billion-dollar entrepreneurs, a mere 1% succeeded due to the idea itself. The other 99% succeeded due to the entrepreneur’s skills in developing smart strategies that helped beat competitors and in having the skills to execute them.
#2. Can AI-based reverse design thinking be better than design thinking for entrepreneurs?
An article in the Harvard Business Review notes that one benefit of AI is to develop ideas for the use of a technology before figuring out the unmet need it can solve. Many entrepreneurs seem to do this already – they develop a product and then hope for a market, which is perhaps the reason that many ideas fail. On the other side, many great ideas and technologies are rejected before some brave entrepreneur proves their potential.
· The liquid crystal display was developed at RCA but commercialized first by the Japanese. Why did RCA not pursue it?
· Xerox developed the laser printer, the Alto (mouse-based PC), and Ethernet, but others commercialized it. Why did Xerox not commercialize them?
Are more ideas from AI the answer? AI needs to pick winners. Will that happen?
#3. Can AI mimic Steve Jobs? More importantly, should the developer of such an app release it or use it?
One future benefit of AI is speculated to be developing new blockbuster products, as Steve Jobs did with the iMac. How would anyone know if the AI algorithm was really a clone of Jobs? And if anyone could really develop and prove an AI-clone of Steve Jobs, should they release it?
#4. Can AI do better than VCs who struggle to identify brilliance?
Another article on AI suggests that entrepreneurs act on brilliant ideas and avoid bad ones. But can we separate the genius from the garbage given that:
· No one recognized Sam Walton’s brilliant idea to locate big-box stores in small towns.
· IBM did not recognize Bill Gates’ brilliant idea to license the operating system to IBM on a non-exclusive basis.
· Few recognized Michael Dell’s brilliant idea to sell PCs direct to the consumer.
· No one recognized Google’s brilliant search engine – more than 10 VCs rejected the idea and one corporation was not willing to buy it when the founders tried to sell it for $1,000,000.
· No one recognized Jobs’ brilliance when he launched Apple. Maybe that is why he was fired.
If VCs, the key professionals in venture finance, could predict brilliance accurately, why would they fail so frequently? Can AI do better?
#5. Can AI do better than billion-dollar entrepreneurs to find the dominating edge?
Forecasting a winning strategy involves finding the successful combination of product-segment-competitors-sales-driver to dominate the emerging industry. Can AI do that without testing in the field? If so, does that mean that AI is constantly monitoring everything?
MY TAKE: At the intersection of AI and entrepreneurship, the lure of accelerated idea generation is enticing. Yet, the pivotal challenge is in distinguishing between the gems and the garbage for the individual entrepreneur, and in execution skills. What if 200 entrepreneurs launch their ventures with AI-developed strategies? Can AI accurately identify the skills that will set them apart and lead to success, especially if they use the same AI-tool and deploy the same AI-developed strategy?
