By Dan Pontefract.
In 1914, Henry Ford was in the midst of a dilemma.
The year prior he had successfully engineered how to mass produce automobiles thanks to the invention of the first-ever moving assembly line. Instead of several people working collaboratively to put together the car, each employee now possessed a specialty, performing a specific task as the vehicle made its way down the line through motorized conveyor belts.
That car, of course, was the Ford Model T, and in 1913 over 200,000 of them were manufactured.
However, there remained a problem in 1914. The workers.
More cars could be put on the road if it were not for the dismal state of the workers.
They were often late or absent. Some would quit without notice to seek out riches in the Gold Rush. The cost to hire and retrain—not to mention the lost productivity of chronically absent employees—impacted Ford’s bottom line tremendously.
Ford’s idea? Cut the workday down to 8 hours and double the employee’s pay to $5 a day. It was a seminal moment in the history of the worker and of Corporate America in general.
It brings us to today and the inevitable penetration of artificial intelligence. AI not only might positively affect our organizations the way in which it helped Ford, but it might also even help employees.
Financial advisors provide us with an example to consider.
Who wants to outsource their entire life savings and investment options to a machine? No one. Well, not me at least. However, when AI algorithms are used to ascertain potential exposure to various equity indexes quickly, what’s not to like? When machines analyze reams of information and statistics—while evaluating variables and near infinite bits of data in an expedited and thorough manner—the partnership between AI and financial advisor changes dramatically. Ultimately it can become a win-win example of AI for the organization, employees, and customers.
In this case, the financial advisor (the employee) does not have to spend (or waste) precious time trying to identify whether the customer is at risk or whether the data and statistics line up for profitable and positive returns.
Instead, AI takes care of that at lightning quick speed, and often in the background. The advisor is then allowed to spend more time with the customer explaining things human to human. In today’s world, advisors do both the financial sleuthing/planning and the human relationship building, but it is the latter that often suffers. That is, there is less time to spend with the customer as more time has to be paid identifying exposure, studying the trends, and so on.
The customer is indeed quite pleased. Rather than feeling like a metric, they feel human, again. The relationship between the customer and the financial advisor becomes a much-improved one, where the advisor becomes the translator of what the AI has sleuthed and even recommended.
The improved connection with the financial advisor also delights the organization’s C-Suite. Those senior leaders are impressed by increasing customer satisfaction scores, as well as the employee engagement scores of its financial advisors. When employees have more time to be human with their customers, what’s not to like?
I envision a scenario in the not-too-distant future where AI and financial advisors become an inseparable pair. Not only will the financial advisor have more time to be human with the customer, but they can also become more than just a “numbers guy/gal.” They may even free up the time to advise not only about finances, but other facets of life and our estates including family, tax implications, bequeathing issues, and so on.
Henry Ford’s assembly line invention demonstrated how the organization, employee, and customer benefited when technology got paired with humans.
Could AI and financial advisors be one example where—over a hundred years later—it could happen again?