Author: Peggy Smedley
For the better part of three years, the manufacturing conversation has centered on one question: Should we adopt AI (artificial intelligence)? That question has now been answered. It is a clear yes. Now comes the hard part. The reality is the more important question today is much more difficult: Can manufacturers actually scale AI in a way that transforms the business? That is the trillion-dollar question on the table today for the manufacturing industry. A recent Parsec global survey of 1,200 manufacturing leaders across executive, operational, and technical roles found 72% of manufacturers have adopted AI in some capacity, yet…
For years, contractors and project owners have invested heavily in technology—from project management software and ERP (enterprise-resource planning) systems to drones, connected equipment, sensors, dashboards, and now AI (artificial intelligence). Every new investment has generated more information. Yet despite this explosion of data, many construction organizations still struggle to answer fundamental questions: What is happening? Why is it happening? And perhaps most importantly, what should we do next? Simply, construction companies are drowning in data but starving for insights. Several trends are accelerating this transition. First, AI infrastructure investments continue to grow at an unprecedented pace. McKinsey & Co., has…
The conversation around digital transformation has evolved a lot in the past decade. We began by digitizing drawings and leaning into CAD (computer-aided design). Then we embraced BIM (building information modeling). Next came digital twins, connecting the physical and digital worlds in ways we could only imagine years ago. Then we saw explosive growth of data in many vertical industries such as construction, utilities, infrastructure, and manufacturing, just to name a few. Today, we stand at yet another turning point. The question is no longer whether organizations should collect more data. The real question is this: How can businesses unlock…
The future of construction depends on the industry rethinking how we build the workforce that will construct the homes, buildings, cities, and infrastructure of tomorrow. As we move closer to the year 2030, the industry’s greatest competitive advantage won’t just be AI (artificial intelligence), automation, or robotics. It will be people with the skills to work alongside these technologies. Throughout the past several years, we have watched AI and automation move from experimentation to implementation. In the construction industry, AI is already helping monitor jobsites, optimize schedules, identify safety risks, and improve project outcomes. But AI is not replacing construction…
The freight rail industry is one of the most critical yet often overlooked pillars of the global economy. In the United States alone, railroads move roughly 40% of long-distance freight when you measure it by 10 miles, transporting everything from agriculture products and chemicals to automobiles and consumer goods to so much more. V Krishnan, industry advisor for manufacturing and mobility, Microsoft, says, “Freight rail is this invisible backbone of the whole economy.” Also, its efficiency is unmatched. A single train can move a ton of freight roughly 400 miles on just one gallon of diesel, making rail one of…
Even the most sophisticated AI (artificial intelligence) models are constrained by data trapped in information silos and legacy systems. The challenge is every new data source requires its own custom implementation, making connected systems difficult to scale, which is something that could slow building the next-gen infrastructure projects we so desperately need. Enter MCP (model context protocol). In November 2024, Anthropic introduced the model context protocol, which is a standard for connecting AI assistants to the systems where data lives. Anthropic suggests MCP provides a universal, open standard for connecting AI systems with data sources. The objective is to replace…
For decades, manufacturers have been on a journey to greater automation, connectivity, and intelligence. First came digitization. Then came the IoT (Internet of Things), enabling machines, systems, and people to share data in realtime. Today, we are entering the next phase of that evolution: agentic AI (artificial intelligence). Across many industries, companies are moving beyond using artificial intelligence simply to analyze data. Instead, they are deploying AI agents that can assist workers, automate workflows, and help organizations make faster, more informed decisions. This shift has the potential to redefine how industrial businesses operate. The latest examples are emerging in manufacturing,…
Data centers and AI (artificial intelligence) are fueling one of the largest infrastructure shifts we have seen in decades. While much of the conversation centers on computing power and innovation, a bigger story is emerging behind the scenes—one that involves electricity, water, and the critical infrastructure needed to support the evolution of technology. The reality is simple: Data centers are growing at an unprecedented pace, and our infrastructure systems must evolve just as quickly. Easier said than done, right? Recent research from Gartner highlights the magnitude of the challenge. Global data center electricity consumption is expected to reach 565 terawatt-hours…
As we look ahead to the second half of 2026, OEMs (original-equipment manufacturers) have a real opportunity to reset and focus on actions that provide meaningful business outcomes. The question often becomes, where exactly do we start with connected products, data, and AI (artificial intelligence)? Dave Moelker, CEO, Twisthink, recently told me organizations frequently approach innovation from the wrong direction. Instead of starting with a business problem and working backward to determine how technology can help solve it, many begin with the technology itself and search for a use case. “Customer expectations continue to move forward, and these technologies have…
Every transformative technology cycle comes with a familiar debate: Are we witnessing the next great economic opportunity—or the formation of a bubble? We have had this conversation before. From the dot.com era to emerging technology booms that followed, periods of rapid investment often spark concerns about whether expectations are outpacing reality. Today, AI (artificial intelligence) finds itself at the center of that discussion. The most important question may not be whether AI itself is a bubble. Instead, it is whether the market can support the pace of growth that businesses, investors, and customers expect. New research from AI infrastructure provider CUDO…