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Ted Krantz, CEO of Interos Interos , a company providing supply chain resilience and risk management software, emailed me to say that there was a supply chain risk everyone seemed to be ignoring – AI-related risks. Most argue that when the UI is trained with the companys own data, the risk of hallucination is small.
The current AI landscape can be viewed as a series of wars,” where companies and organizations are battling for dominance across various technological and market battlefronts. Datacenter Hardware: The demand for powerful computing to train ever larger and more accurate AI models is insatiable.
Paula Natoli leads Google Cloud’s Supply Chain & Logistics Industry Solutions for the Americas regions, partnering with customers to deliver exceptional customer satisfaction through supply chain technology excellence. Cloud fleet routing leverages Google’s technology, data, and Google Maps product to improve fulfillment and delivery.
These sensors capture precise data on factors like location, speed, fuel usage, and driver behavior, transforming fleet management from reactive to data-driven decision-making. The IoT data allows managers to detect inefficiencies, predict maintenance needs, and even assess driver performance.
While we have made progress to solve this, it’s potentially at risk due to advancements in AI technology. Research shows that the hiring process is biased and unfair. This eBook covers these issues & shows you how AI can ensure workplace diversity.
Enterprise IT is on the cusp of a transformation the likes of which we havent seen since the transition to Software-as-a-Service (SaaS). In fact, Id argue this transition to what is increasingly being dubbed Service-as-Software has more profound implications for industries and workforces than anything thats come before.
This is where pest control business software comes in as part of a robust pest control strategy, offering tools to optimize processes, enhance customer satisfaction and drive profitability by bypassing old manual processes. Disclaimer: The information below is accurate as of February 12th, 2025.
Chuck is the CEO and Co-founder of High Definition Vehicle Insurance (HDVI) , where he leads an experienced team of insurance, technology, and trucking industry experts who deeply understand the challenges of today’s fleets. HDVI’s Shift tool uses a fleet’s own real-time telematics data to charge a fleet the cost of their actual risk.
Three months into 2025, we have seen a barrage of on-again, off-again tariffs that have supply chain and logistics teams reeling, as they must rethink everything from next weeks shipping route to their foundational network models. That may sound impossible, but new technology places this capability within the reach of every organization.
Curtis is also the Founder of Understand LTL , an LTL training firm. Curtis is also the Founder of Understand LTL, an LTL training firm. Curtis is on a career-long mission to advance LTL via technology, process and relationships while simplifying and demolishing the silos that have existed for decades.
From sourcing and bid evaluation to warehouse slotting and dynamic routing, AI tools support faster and more consistent outcomes by processing large volumes of operational data and identifying patterns that human decision-makers may overlook. These capabilities are now being integrated into mainstream TMS, WMS, and ERP platforms.
In response, many organizations have shifted toward decentralized and regionalized supply chain models, distributing production and sourcing across multiple regions. However, recent disruptions including health crises, trade disputes, logistics bottlenecks, and climate-related events have exposed significant vulnerabilities in this model.
Digital twins are emerging as digital transformation accelerators for supply chain and logistics organizations seeking enterprise-level visibility, real-time scenario modeling, and operational agility under disruption. These are not static dashboards or simple visualizationstheyre living, data-rich models of real-world operations.
Retrofitting existing infrastructure with energy-efficient technologies further enhances sustainability efforts. Critical practices include: Circular Supply Chains: Designing systems that minimize waste and emphasize recycling and reuse. Advanced route optimization tools further support these goals.
Companies find it difficult to fully trust the data from suppliers, complicating efforts to ensure product authenticity, safety, and ethical sourcing. Blockchain technology is supporting this by providing a secure, decentralized, and tamper-proof method for real-time product tracking.
Today, data and software programs can be saved or run in any data processing center in the world. Cloud computing has made installation, administration, and updates significantly easier and has thereby laid the foundation for Software as a Service (SaaS). Rapid integration. Access to latest features.
As anyone who’s experienced change in supply chain technology over the past five-to-ten years can attest, we’ve come a long way, baby. Artificial intelligence, neural networks, machine learning, robotics, mobile apps, big data, the cloud and Software-as-a-Service (SaaS). The software is still under your control.
This includes the debut of a new highperformance ServiceNow reasoning model, Apriel Nemotron 15Bdeveloped in partnership with NVIDIAthat evaluates relationships, applies rules, and weighs goals to reach conclusions or make decisions.
1: From Support Role to Centre Stage At the point of sale, customers today enjoy an unprecedented degree of choice in the range, price, and quality of products on offer, primarily due to the development of mobile technology, connectivity, and platform-based commerce.
Disruptions have become the norm, rather than the exception, and the only organizations that can thrive in this new reality are those with the right tools. One consistent theme emerged from these discussions: the need to move away from disconnected logistics technology silos toward a much more connected ecosystem.
The combination of SAP agent technologies and Databricks data fabric solution, sets the stage for end-to-end enterprise orchestration. Every ten years or so, there is a technology that truly shakes up the enterprise and supply chain software markets. Vendors that embrace the new technology take market share.
Manufacturers have adopted innovative solutions and technologies to deal with these issues. Artificial intelligence (AI) and machine learning (ML) in manufacturing ERP have recently added a new realm of technology that can address the complex operations found in manufacturing. What is AI and ML?
Knowledge Graphs are emerging as an important tool for building advanced AI capabilities. Agentic AI involves creating a system of interacting agents, each trained on a specific task or dataset. We needed to model the data in a way that we can do simple searching. Agentic allows for much greater flexibility.
Enter the industrial data scientist, a new breed of data analyst with access to more industrial data than ever before and the advanced technology to translate that information into actionable intelligence. Therefore, unlocking the value of industrial data through AI requires a hybrid approach.
In a recent Wall Street Journal op-ed, Elon Musk and Vivek Ramaswamy outlined their proposal for a Department of Government Efficiency (DOGE), emphasizing streamlined governance and technological transformation. Training in areas such as robotics, AI, and data analytics would be crucial.
Businesses are replacing manual processes with automated material handling systems to improve efficiency, reduce costs, and enhance accuracy. From automated guided vehicles (AGVs) to robotic picking systems , these technologies streamline operations and minimize human intervention. What Is an Automated Material Handling System?
One of the key approaches to simulating warehouse operations is based on employing discrete event simulation (DES) techniques and tools. DES allows the modeling of complex warehouse operations at various levels of detail. Typically, modeling is done by highly trained engineers with an industrial engineering background.
Every time technology takes one step forward, its accompanied by increased vulnerabilities that companies need to be aware of and plan for. While cybersecurity should be a priority for every business in any industry, digital security is of utmost importance in these areas because it directly impacts customer trust and data.
When you begin researching Warehouse Management System ( WMS ) software, you’re probably running into some difficulties in the budgeting process because pricing is not always readily available. Transitioning from legacy systems presents hurdles that add to the true cost. SaaS or cloud will also influence this pricing.
More Resources Home Is AI Hype or a Truly Revolutionary Technology Set to Transform Logistics? (AI Like all innovations, however, developing technology as complex as the human brain requires time and significant investment.Here, too, the journey of AI began as far back as 1956 at a workshop on Dartmouth College’s campus in the U.S
Transparent data prepared especially for your logistics operation will get you easily through your peaks. The hype usually revolves around just one item and can easily be managed by a modern logistics system. Logistics software is your ace in the hand, before, during and after the peaks. Peaks are all so different.
It can be incredibly frustrating when the software you use to run your supply chain will become unsupported. Some tools may be acquired by competitors, who then incorporate them in a vastly more expensive package. Attempting to run your supply chain on unsupported software is like walking a tightrope without a net.
Transportation Technology Maturity Curve This is the time of year when industry analysts and technology pundits make predictions about the future. The survey covered what technologies they are currently using as well as their planned investments. Implementing new systems is not easy.
Secondly, why should shippers and logistics service providers consider using machine learning in their transportation management systems, and why now? Due to the complexity, most organizations revert to a more simplistic, static model. IoT technology is making visibility data more robust and readily available.
In the first issue of our AI popup newsletter series, Matt Motsick, CEO of Rippey AI and a long-time logistics technology leader, explores buying or building AI models. Matt was previously the founder/CEO of Catapult International, the industry leading ocean shipping rate management system.
Staying up-to-speed in leading technology requires time and investments. With all the current and upcoming logistics technology, it can be confusing for shippers to identify what will have the best impact to stay competitive now and in the future. HOW LOGISTICS TECHNOLOGY CAN HELP. WITH CAPACITY. WITH RISK MANAGEMENT.
It’s a system that can create new patterns based on the interpretations of learned patterns. Foundational Model This is where the training/learning takes place, where you’re teaching the AI how to look at things and look at input. This model component is generally a conversational chatbot leveraging the LLM to create content.
She has led programs ranging from acquisitions to technology deployment with a strong focus on lean manufacturing and data management. CarrierDirect builds organizations and relationships, providing strategy and technology designed to maximize efficiency, reduce cost, and make your business stand out. About CarrierDirect.
Today, the steel manufacturing leader has an ambitious digital transformation agenda and is leveraging AIMMS technology to optimize operations in its home country. I belong to this second division and work mostly on mathematical modeling, simulation and supply chain analytics. . The software supports scalability.
The German software colossus has 27,000 customers and 300 million users that rely on their software. 27,000 customers are regularly using SAP Business AI, either as part of the SAP business flow or they have used SAP’s Business TechnologyPlatform to create a custom AI solution.
The integration of drone technology holds the potential to revolutionize how businesses approach pest management, presenting both opportunities and considerations. However, the adoption of this consumer-driven technology faces hurdles, including technical limitations and regulatory concerns that must be navigated.
In a previous blog AI and Machine Learning in Manufacturing ERP: Key Benefits , we discussed the benefits of using AI in manufacturing and how it could be enhanced with an ERP system. Despite the hype around AI, many manufacturers have still to implement it in their manufacturing systems. Manufacturers who implemented Industry 4.0
The past thirty years have seen several notable (re)evolutions in enterprise software, including client-server, Web X.0, Brief comparison of AI technologies When discussing AI and how it applies to ERP, it’s important to understand that AI has been leveraged by ERP software providers (and users) for some time.
These challenges necessitate extensive configuration within Advanced Planning Systems (APS) test environments to assess their impacts. APS are complex, live production environments requiring extensive configuration to accurately model a business’s operational reality.
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