Instinct, acumen, and industry foresight. Three crucial components to guiding a brand or corporation through mergers, industry instability, and overall strategy.
When instinct is wrong, you become “the company that made the wrong move” like Kodak. When acumen lacks, you become an afterthought like Dell. When industry foresight is absent, you become obsolete like Blockbuster. Companies who aren’t capitalizing will be crumbled.
…the cost of bad decisions is high… Consider that 50% of the Fortune 500 companies are forecasted to fall off the list within a decade, and that failure rates are high for new product launches, mergers and acquisitions, and even attempts at digital transformation.
Barry Libert & others, MIT Sloan Review
It’s not like folks don’t see failure coming. A 2015 McKinsey study found that only 16% of board directors said they fully understood how the dynamics of their industries were changing and how technological advancement would alter the trajectories of their company and industry. Business is moving faster than ever; boards and executives cannot continue to make great decisions without the help of intelligent systems.
We often perceive algorithms to have a great impact on small tasks, but their greatest impact may come in the form of strategic corporate foresight.
Some of the best human strategic thinkers may be able to think five or six moves ahead. But, they can’t juggle this same process with dozens or hundreds of decisions at once. On the other hand, one of the main tenets of machine learning algorithms is their ability to run millions of simulations and peruse terabytes of data in
Currently, we see this skill being utilized to support capital investment.
BlackRock says it relies on it [AI] for heavy cognitive lifting, often by scouring data to tease out patterns that might remain obscure to human eyes and brains. Examples offered by Jessica Greaney, a company spokeswoman, include identifying and trying to exploit
Conrad De Aenlle, NY Timesrelationships between securities or market indicators, perusing social media “to gain insights on employee attitudes, sentiment non intuitiveand preferences,” and monitoring search engines for words being entered on particular topics, say cars or luxury goods.
These same processes could be tweaked to support corporate executives when building strategy. They might use AI to scan particular industries for emerging competition. Then, running simulations to weigh their likelihood of future success. And possibly even deciding what is the ideal merger & acquisition scenario. This isn’t a foolproof plan, though.
AI is only as good as the data and resources that you give it. If the AI works off of false assumptions or your
Mark van Rijmenamorganisation has poor data quality, then you could be led astray. The underlying infrastructure and data sources need to be sound before the AI can make meaningful contributions to the company.
AI’s reliance on data brings up another question: can AI make accurate predictions where little or no data exists? For instance, if Coca-Cola employed an advanced AI Board Member today, would it have found, assessed, and invested in BodyArmor SuperDrink far earlier and gotten a better deal?
This comes back to the element of instinct. It’s hard to predict a
It’s important to note, though, that far sooner on the timeline for AI’s role in the workplace will be the commercialization of virtual assistants like Fin.
We know that business relies heavily on relationship building and a human assistant can be an executive’s biggest weapon for this task. However, they are often times bogged down by the menial duties such as calendar upkeep, travel coordination, and writing emails. Very soon, virtual assistants will relieve employees of these simpler duties, allowing them to focus full-time on the actions that’ll help their boss build better client relationships (remembering small and meaningful details, reading behaviors, giving the perfect gift, etc.).
Although we’re beginning to see investment firms employ AI to assist in decision-making, the role is very limited. Similarly, AI will be stuck in a supporting role for quite some time before they are guiding boardroom strategy.
The technology necessary to make sense of something as broad as corporate strategy is quite a ways off. And even then, the implementation curve will be stark.
Around 2038, AI-assisted Board of Directors will begin to be a niche worth watching – with mass adoption coming around 2050.
Nonetheless, an AI-assisted Board of Directors would be worthwhile across a plethora of industries because it theoretically can remove human bias, prevent opportunities from going unnoticed, and ensure resources are being used properly.