RoboSellers And RoboBuyers: A Thought Experiment

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In 2013, Oxford Professors Carl Benedikt Frey and Michael A. Osborne claimed that 47% of US jobs are susceptible to “computerization.” In their model, sales jobs were among the most likely positions to be automated. Salespeople in technical fields had a 25% probability of being computerized while those in non-technical fields faced 85% odds of automation. Both insurance agents and retail salespeople were given a 92% probability of being replaced by machines—eventually.

However, I believe artificial intelligence (AI) commentators have overlooked one of the most interesting consequences of this future: If you could build a “RoboSeller,” you could also build a “RoboBuyer.”

Machines wouldn’t need rest, pay or double shots of espresso to sell – they would only need power and connectivity. Thus, buyers would be bombarded by even more cold calls, email pitches and LinkedIn LNKD -6.37% messages than they face already. To preserve their time and sanity, business leaders would need RoboBuyers to filter incoming offers and eliminate all but the best.

Personally, I am not in favor of automating salespeople at all. But this scenario provides an interesting thought experiment: Hypothetically, how would we ‘train’ RoboBuyers to filter out bad sales pitches? What would automatically eliminate a pitch? Tackling these questions can help us improve our sales technique today.

Read the rest on Forbes.

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