Sign up for our newsletter and get the latest big data news and analysis.

How AI Can Save Jobs in the COVID-19 Economy

In this special guest feature, Arijit Sengupta Founder & CEO of Aible, believes that the key to saving jobs in the COVID economy requires the right tool for the job, in this case, a new type of AI that blends augmented analytics and human domain knowledge. Arijit is the former Founder and CEO of BeyondCore. He has guest lectured at Stanford and other universities; spoken at conferences in a dozen countries; and was written about in The World Is Flat 3.0, New York Times, San Jose Mercury News, Harvard Business Review, The Economist, and other leading publications. Arijit has been granted eighteen patents in the domains of advanced analytics, machine learning, Business Process as a Service, business process improvement, operational risk, privacy and information security. Arijit holds an MBA with Distinction from the Harvard Business School and Bachelor degrees with Distinction in Computer Science and Economics from Stanford University

Massive job cuts and unprecedented economic uncertainty have triggered a flight-or-fight response in businesses all over the world. Confronted with a lack of new information, company leaders are going with their gut reaction: slashing jobs to save cash and preserve options.

Their reaction is understandable. The key analytical tools they typically rely on—business intelligence systems, AI models and strategic planning forecasts—have stopped working.

Business intelligence tools look at the past, but in the current business climate, the past looks nothing like the present. Traditional AI relies on historical data, but with business conditions changing week-to-week (and sometimes day-to-day), most data is hopelessly out of date. Businesses could wait for a “new normal” to take hold and retrain the AI models, but could take years. No one has that long to wait. And annual plans and quarterly targets seem almost quaint when it’s impossible to predict what will happen in a month.

While the rush to make business decisions based on instinct may seem logical, it can be counterproductive and even dangerous. Making drastic across-the-board cuts in budget and jobs amounts to wielding a meat cleaver rather than a scalpel. You have no idea whether you’re cutting fat or muscle. And rather than preserving options, big cuts often reduce options when companies try to move forward.

What leaders need is an analytical tool to help them consider many possibilities quickly, execute a strategy while preserving options and react to change based on timely feedback. Those things are impossible for a person to accomplish on their own. The right tool for the job, in this case, is a new type of AI that blends augmented analytics and human domain knowledge. 

As recently as last year, 37% of workers between the ages of 18-24 said they were worried about new technology eliminating their jobs. What would they say if they knew those same technologies could be used to save their jobs?

AI is well-suited for trying out hundreds of scenarios quickly to see how different assumptions would affect the business. AI creates optimal models for each scenario (plus thousands of others that managers hadn’t even considered) and deploys them automatically. Rather than a blunt 50% cut in sales costs, what happens if those cuts are reallocated across new sales efforts, upselling and replacements? Similarly, if conditions call for a 15% across-the-board cut in marketing costs, does it make sense to apply that across all channels, or are there ways to adjust the mix? Instead of cutting 40 workers in a department, the company may actually save money in the long run by cutting half that number and redeploying some workers to more promising areas of the business.

Next, once you choose a strategy, it needs to be embedded in everyday operations through end user tools like Salesforce. But the strategy is not static —end users can adjust the aggressiveness of the model as new business realities are revealed, and those recommendations are shared with management, creating a collaborative feedback loop. The AI learns from every prediction it makes, and allows for granular fine-tuning, a critical advantage at a time when business conditions are changing quickly.

Done right, AI may well become the tool that saves jobs rather than eliminates them. But humans need to be an active participant in the way AI models are created and adjusted for it to work. AI and humans working together are far superior to either one acting alone. In the face of major economic uncertainty, humans alone are likely to pull one big lever, make big cuts across the board and hope for the best. Humans don’t have the capacity to consider thousands of competing factors. On the other hand, AI alone can’t make informed predictions and recommendations when rapidly changing business realities mean that most data is out of date. 

But when front-line workers are empowered to add valuable insights to what the AI has learned, it creates a powerful engine for informed decision making. And in the months ahead, making smart data-driven decisions will be more important than ever.

Sign up for the free insideBIGDATA newsletter.

Leave a Comment

*

Resource Links: