Most of AI and IoT projects are going to fail

Andrey Lovygin, Head of International Business of ZYFRA has commented the following opinion on implementation of digital solutions to industry.

While digital solutions implementation promises industries great benefit, it’s important to remember that there will first be more failures than successes, but those failures are for good.

Driven by a fear of missing out, companies in many industries have announced AI and IoT-focused initiatives. Recent research from McKinsey Global Institute found that 45% of work activities could potentially be automated by today’s technologies, and 80% of that is enabled by machine learning. According to the EY report, robotic process automation (RPA) and advanced analytics are expected to have the most significant impact on the industry over the next five years.

 70% industrial company executives say they plan to adopt IIoT in the next 18 months. Unfortunately, most of these efforts will fail. They will fail not because AI or IoT technology is all hype, but because companies are approaching digital-driven innovation incorrectly. We’ve seen this in a time of dotcom.

 Equally important, AI and IoT are not just technology, but include data, security, user experience, and business/business model elements. A company going digital has a lot of decisions to make, of which technology is just one component. Early AI pilots are unlikely to produce the dramatic results that technology enthusiasts predict. Companies from sectors such as manufacturing and health care (IBM Watson’s fail is an example) have captured less than 30% of the potential from their data and analytics investments.

 By now in Oil and Gas sector it’s about 5-10% efficiency increase, for metallurgy 3-5%. Those who started investing in AI and IoT projects accounting for fast returns are rather fail or get just point of percent in production cost decrease. It is long-term projects, one might go beyond point of optimization, to rethinking end-to-end processes, which is the area in which companies are likely to see the greatest impact.

 What is the most rational at the moment is collecting valuable and useful data. No matter how good your models are, they are only as good as your data – and quality of data, where there is no globally recognized standard yet, differs a lot. So, the first step in digitalization process for manufacturers all over the globe should be implementation of real-time machine monitoring and manufacturing data collection (MDC) system with hundreds of customizable reports and charts that can be used to track jobs, parts, operations, work centers, OEE, scrap, costs, downtime and people. That is the first step towards industry 4.0.

 According to Market Research Future research microgrid monitoring market is expected to expand at ~ 12.05% CAGR during the period 2018 to 2023. The human-machine interface (HMI) market is projected to grow at a CAGR of 8.33% over the forecast period of 2017-2023. By industry vertical, the global human machine interface market has been segmented as manufacturing, automotive, oil & gas, utilities, and healthcare among others.

 Mitsubishi Electric Corporation, Omron Corporation, Rockwell Automation, Zyfra Group, – all are headed this direction. And this one is a good way to avoid a greater number of failures when starting automation process.

For reference: