AI: Gap between Expectation & Execution

According to a recent survey done by BCG across industries - Three-quarters of executives believe AI will enable their companies to move into new businesses. Almost 85% believe AI will allow their companies to obtain or sustain a competitive advantage. But only about one in five companies has incorporated AI in some offerings or processes. Only one in 20 companies has extensively incorporated AI in offerings or processes. Less than 39% of all companies have an AI strategy in place. The largest companies — those with at least 100,000 employees — are the most likely to have an AI strategy, but only half have one.

So what’s the reason for this gap? Primarily there are three reasons –

#1 Relevant Data – machine-learning algorithms are not inherently intelligent. They require past evidences or simulations to predict the future outcome. Even though most companies seem to be collecting some data but that turns out to be insufficient or irrelevant post their discovery of business opportunity. Take for example the Battery manufacturer that we worked with to predict on the industrial battery failure. As described in this case study. Or the predictive maintenance solution that the Pharma company was looking for in this case-study.

#2. AI is strategic not business critical. Enterprises don’t invest in image or natural-language processing. They don’t invest in predictive analytics or big-data. They invest in solving business problems. A large manufacturer had over 1000 suppliers world-wide. They engaged us not for implementation of forecasting techniques for time-series data but to automate their plant-level material forecasting and to improve their per component cost reporting. Similarly a large IT services company invested in employee retention solution rather than reporting on people analytics.

#3. Executives lack AI understanding. An unsophisticated manager might see one prediction work once and think that it’s always good, or see one prediction that was bad and think it’s always bad. A small minority exhibit a deep understanding of AI, which they accumulate not by visiting Silicon Valley for a demo of a self-driving car or a robot playing soccer but by getting to the nuts-and-bolts of several moocs detailing the intricacies and benefits of AI for their domain. Recently we were approached by the CIO of a temp staffing company with a request to identify people who are likely to accept a contract job over a permanent one. His inputs were the 50,000 resumes. And his request, use your deep learning engine to identify resumes for the contract job with 1% accuracy. You know where its going.