The Canadian fertilizer company Nutrien, for example, operates two dozen manufacturing and processing facilities spread across the globe and nearly 2,000 retail stores in the Americas and Australia. To collect underutilized data from its industrial operations, and gain greater visibility into its supply chain, the company relies on a combination of cloud technology and artificial intelligence/machine learning (AI/ML) capabilities. "A digital supply chain connects us from grower to manufacturer, providing visibility throughout the value chain," says Adam Lorenz, senior director for strategic fleet and indirect procurement at Nutrien. This visibility is critical when it comes to navigating the company's supply chain challenges, which include seasonal demands, weather dependencies, manufacturing capabilities, and product availability. The company requires real-time visibility into its fleets, for example, to identify the location of assets, see where products are moving, and determine inventory requirements.

One of the biggest challenges to deploying and scaling artificial intelligence is ensuring the data being used to train AI algorithms is accurate and timely. Using bad data hampers an organization's ability to predict future trends and make meaningful business decisions. Only when high-quality datasets drive AI algorithms can businesses gain valuable information and insight that can help them make critical decisions that could improve customer experience, brand loyalty, supply chain flow and more. At its core, an accurate dataset provides a representative sample of the population. Given that 97% of the population owns some type of mobile device and 85% have smartphones, location data is well-positioned to provide an accurate accounting of the activities of a given population, especially when used to complement other data sources.

Berkshire Grey Inc, the leading AI-enabled robotic solutions, has announced its partnership with North Highland, a worldwide management consulting firm, to solve global supply chain challenges and enhance the throughput of eCommerce fulfillment. With surging demand in the E-Commerce Industry, lack of labor issues, and increasing customer expectations for speed and quality, chief supply chain officers (CSCOs) are under more stress than ever to optimize supply chain operations and enhance supply chain resiliency. Berkshire Grey offers solutions to customers that support order fulfillment over the entire supply chain by providing the most extensive portfolio of (IER) Intelligent Enterprise Robotic solutions available. Berkshire Grey's complete services cover design, installation, testing, and commissioning, as well as ongoing support employing cloud-based AI solutions for auspicious maintenance, system operations management, analytics, and integration. Major retailers and consumer product companies trust North Highland consultants to advise and deliver cutting-edge technology, which is why North Highland chose Berkshire Grey's innovative robotic solutions.

Artificial intelligence has made noticeable changes to technologies around the world. Perhaps AI's most notable potential, however, is its role in the supply chain industry. AI has changed the supply chain process from reactive to proactive, which creates a larger change in how data-driven processes will operate in the future. The true role of AI in the supply chain is to enhance and augment human intelligence and decision making. That is much different than what some people view as making human intelligence obsolete, according to experts at Supplyframe.

The astonishing speed of digital disruption today calls for new and emerging technologies that are capable of long-term value creation. Poised at this intersection of digital revolution, business and accelerated scientific discovery, leaders across verticals have formulated a vision to begin their transformative journey. Though laggards at the beginning, the pharmaceutical industry has eventually started taking advantage of new-age technologies in areas from clinical trials to manufacturing. AI is already known to be speeding and improving the drug discovery process, owing to its capability of sifting through and making sense of heaps of scientific data related to research and development. It has also started making inroads into newer and more diverse areas like drug manufacturing and supply chains, which are the least explored in the Life Sciences space, yet have the capability to offer maximum benefits.

In the last decade, Machine Learning has come roaring out of the textbook to become an integral part of the healthcare industry. In addition to contributing to the increased efficiency of routine administrative procedures and reducing operational costs, it is also beneficial for managing the supply chain and logistics. The Indian healthcare sector is expected to reach ₹19,56,920 crore ($280 billion) by 2020. Rising income level, greater health awareness, increased precedence of lifestyle diseases and improved access to insurance are set to be the key contributors to its growth. The report also states that spending on AI in healthcare is projected to grow at an annualised 48% between the year 2017 and 2023.

London, Dec. 10, 2019 (GLOBE NEWSWIRE) -- According to a new market research report "Artificial Intelligence in Supply Chain Market by Component (Platforms, Solutions), Technology (Machine Learning, Computer Vision, Natural Language Processing), Application (Warehouse, Fleet, Inventory Management), & End User - Global Forecast to 2027", published by Meticulous Research, the AI in Supply Chain Market is expected to grow at a CAGR of 39.4% from 2019 to reach $21.8 billion by 2027. Today supply chain networks are becoming more and more complex owing to progressive globalization. Various well-established supply chain organizations across the globe are increasingly struggling with rising cost of operations, dissatisfied customers, declining sales, and unidentified competition. Therefore, the adoption of artificial intelligence technologies in supply chain operations is on the rise in order to create new opportunities & enhance operational capabilities by leveraging new possibilities, fastening processes, and making organizations adaptable to changes in the future. Realizing the fact, various end-use industries are investing heavily in order to reap the profits in highly dynamic and competitive market environments.

In the past decade, supply chain management has skyrocketed across verticals. With e-commerce becoming a critical economy booster, its success depends heavily on an efficient decision-making platform. With advanced technology solutions making steady inroads into businesses every day, the era of supply chain management has evolved. Several companies are thriving today as they capitalize on a robust technology architecture to support large-scale supply chain operations, and are providing analytical insights on route optimization freight tracking and analytics, sales beat optimization. Locus is a state-of-the-art decision-making platform for logistics, optimizing a range of operations to provide consistency, efficiency & transparency.

IT professionals involved in shaping, implementing, and managing their organization's supply chain operations are counting on artificial intelligence (AI) to help make those operations more efficient and effective. Just how much they're expecting from AI became evident in a recent IDG survey of 150 IT professionals across the U.S. AI clearly topped all emerging technologies: 57% of the respondents said AI would have the greatest impact on their supply chain in the coming two years. In practice, of course, AI technologies such as machine learning, natural language processing, and pattern recognition will often work hand-in-hand with data analytics, IoT, and other technologies. For example, AI is already helping data analytics systems identify trends and other valuable information--information that often is buried in massive volumes of data that comes from many diverse sources, IoT sensors included. The intersection of AI and the supply chain will be multifaceted and wide-ranging.

Optimization of supply chain operations has become an imperative, as organizations grapple with customer demands, unpredictable events, and spiraling costs. On top of these persistent challenges, complexities are magnified by the myriad of tools required to manage everything from workforce schedules to resource allocation. To meet competitive demands, business decisions are needed quickly and accurately against an ever-evolving list of requirements and dependencies. But all too often, supply chains break down in the face of unanticipated factors or messy and incomplete data. To drive greater speed and precision in the supply chain, industry leaders are employing automation technology and visual insight capabilities.