From startups to enterprises racing to get new products launched, AI and machine learning (ML) are making solid contributions to accelerating new product development. There are 15,400 job positions for DevOps and product development engineers with AI and machine learning today on Indeed, LinkedIn and Monster combined. Capgemini predicts the size of the connected products market will range between $519B to $685B this year with AI and ML-enabled services revenue models becoming commonplace. Rapid advances in AI-based apps, products and services will also force the consolidation of the IoT platform market. The IoT platform providers concentrating on business challenges in vertical markets stand the best chance of surviving the coming IoT platform shakeout.

From startups to enterprises racing to get new products launched, AI and machine learning (ML) are making solid contributions to accelerating new product development. There are 15,400 job positions for DevOps and product development engineers with AI and machine learning today on Indeed, LinkedIn and Monster combined. Capgemini predicts the size of the connected products market will range between $519B to $685B this year with AI and ML-enabled services revenue models becoming commonplace. Rapid advances in AI-based apps, products and services will also force the consolidation of the IoT platform market. The IoT platform providers concentrating on business challenges in vertical markets stand the best chance of surviving the coming IoT platform shakeout.

Perceiving the pandemics' hard reset as a chance to grow stronger, more resilient, and resourceful dominates manufacturers' mindsets who continue to double down on analytics and AI-driven pilots. Combining human experience, insight, and AI techniques, they're discovering new ways to differentiate themselves while driving down costs and protecting margins. And they're all up for the challenge of continuing to grow in tough economic times. Boston Consulting Group's recent study The Rise of the AI-Powered Company in the Postcrisis World found that in the four previous global economic downturns, 14% of companies were able to increase both sales growth and profit margins as the following graphic shows: AI Is Core To Manufacturing's Real-Time Future Real-time monitoring provides many benefits, including troubleshooting production bottlenecks, tracking scrap rates, meeting customer delivery dates, and more. It's an excellent source of contextually relevant data that can be used for training machine learning models.

Bottom Line: The leading growth strategy for manufacturers in 2019 is improving shop floor productivity by investing in machine learning platforms that deliver the insights needed to improve product quality and production yields. Using machine learning to streamline every phase of production, starting with inbound supplier quality through manufacturing scheduling to fulfillment is now a priority in manufacturing. According to a recent survey by Deloitte, machine learning is reducing unplanned machinery downtime between 15 – 30%, increasing production throughput by 20%, reducing maintenance costs 30% and delivering up to a 35% increase in quality. Accenture, Manufacturing The Future, Artificial intelligence will fuel the next wave of growth for industrial equipment companies (PDF, 20 pp., no opt-in) How the IIoT can change business models. How emerging technologies can transform the supply chain.

The robotics market is growing at an unprecedented pace and vague worries about job loss due to automation--however misguided--often take shape in visions of robots replacing individual workers on production lines. However, there's a much less tangible form of automation that's poised to make an even bigger impact on manufacturing in the near future: artificial intelligence (AI). The concept is notoriously difficult to pin down. "I would say it's as difficult to define as intelligence itself," noted Philippe Beaudoin, SVP research at Element AI. But for manufacturers, what matters most is what AI can do.