Ben Ames has spent 20 years as a journalist since starting out as a daily newspaper reporter in Pennsylvania in 1995. From 1999 forward, he has focused on business and technology reporting for a number of trade journals, beginning when he joined Design News and Modern Materials Handling magazines. Ames is author of the trail guide "Hiking Massachusetts" and is a graduate of the Columbia School of Journalism.
While many companies are launching artificial intelligence (AI) products for use as generic “co-pilots” or consumer-focused gadgets, the Swedish enterprise resource planning (ERP) software vendor IFS says its “Industrial AI” version supports industry-specific processes in “hardcore” sectors based on assets such as power grids, cell phone networks, aircraft maintenance, elevator operation, and construction management.
“Industrial AI is at the very core the solutions we are powering for customers. They are pushing us for ready-to-use AI that they can adopt quickly to solve real industrial challenges like labor shortages, supply chain disruption, [and] stagnated productivity," IFS's Chief Customer Officer, Cathie Hall, said in a release.
In presentations at its user conference in Orlando today, known as "IFS Unleashed," the company said that its latest IFS Cloud 24R2 release supports more than 60 in-depth Industrial AI scenarios. They span generative AI examples like: content generation for training and reports; recommendations for sourcing and suppliers; and contextual knowledge for assembly instruction. The tools also include predictive AI applications like event forecasting; optimization of resources and capacity; and anomaly detection for proactive quality control.
In remarks from the keynote stage, new IFS CEO Mark Moffat—who was appointed to the top office in January—said the company may be less well known than ERP vendors such as SAP, IBM, Oracle, and Infor, but it benefits from a tighter focus on its core users. Instead of selling software across dozens of industries, IFS serves just six industries: aerospace and defense, construction and engineering, energy and utilities, manufacturing, service, and telecommunications.
Thanks to that tight approach, he said the company has earned top Gartner rankings for its software products in field service management (FSM), enterprise asset management (EAM), enterprise resource planning (ERP), and enterprise service management (ESM). And to compound that advantage, Moffat said IFS continues to grow swiftly through acquisition, having bought up a handful of companies in recent months: Assyst, Ultimo, Boka, empowermx, Bolo, Tobin, Merrick, and Copperleaf.
“You need an AI business plan” Moffat told the room. “If you have an AI business plan, that’s terrific, but you can improve it. This area is just moving so fast.”
Artificial intelligence (AI) and data science were hot business topics in 2024 and will remain on the front burner in 2025, according to recent research published in AI in Action, a series of technology-focused columns in the MIT Sloan Management Review.
In Five Trends in AI and Data Science for 2025, researchers Tom Davenport and Randy Bean outline ways in which AI and our data-driven culture will continue to shape the business landscape in the coming year. The information comes from a range of recent AI-focused research projects, including the 2025 AI & Data Leadership Executive Benchmark Survey, an annual survey of data, analytics, and AI executives conducted by Bean’s educational firm, Data & AI Leadership Exchange.
The five trends range from the promise of agentic AI to the struggle over which C-suite role should oversee data and AI responsibilities. At a glance, they reveal that:
Leaders will grapple with both the promise and hype around agentic AI. Agentic AI—which handles tasks independently—is on the rise, in the form of generative AI bots that can perform some content-creation tasks. But the authors say it will be a while before such tools can handle major tasks—like make a travel reservation or conduct a banking transaction.
The time has come to measure results from generative AI experiments. The authors say very few companies are carefully measuring productivity gains from AI projects—particularly when it comes to figuring out what their knowledge-based workers are doing with the freed-up time those projects provide. Doing so is vital to profiting from AI investments.
The reality about data-driven culture sets in. The authors found that 92% of survey respondents feel that cultural and change management challenges are the primary barriers to becoming data- and AI-driven—indicating that the shift to AI is about much more than just the technology.
Unstructured data is important again. The ability to apply Generative AI tools to manage unstructured data—such as text, images, and video—is putting a renewed focus on getting all that data into shape, which takes a whole lot of human effort. As the authors explain “organizations need to pick the best examples of each document type, tag or graph the content, and get it loaded into the system.” And many companies simply aren’t there yet.
Who should run data and AI? Expect continued struggle. Should these roles be concentrated on the business or tech side of the organization? Opinions differ, and as the roles themselves continue to evolve, the authors say companies should expect to continue to wrestle with responsibilities and reporting structures.
Grocery shoppers in Australia will soon be able to zip in and out of the store in record time, bypassing the lines for cashiers or self-checkout kiosks altogether. They can just walk in, make their selections, and walk out with their bags in hand.
The secret to this express shopping experience is the “Caper Cart,” an AI (artificial intelligence)-powered smart trolley from San Francisco-based Instacart. In its first deployment in the Asia Pacific (APAC) region, the system is being tested by Coles Supermarkets, a food and beverage retailer with more than 1,800 grocery and liquor stores throughout the country.
To get started, customers simply grab a grocery cart-sized smart trolley at the store’s entrance and begin shopping, depositing the items directly into shopping bags as they go. The Caper Carts use onboard AI, cameras, and a built-in scale to automatically recognize items as they’re added to the trolley. Customers can watch their running total display on a screen—just as if they were shopping online—then swipe their credit card on the trolley’s payment terminal to complete the purchase.
“As the first retailer in Australia to introduce AI-powered trolleys, we’re excited to offer our customers a convenient and engaging way to shop in-store, helping them save time, manage their budget, and check out faster—or at their own pace,” Coles’ chief digital officer, Ben Hassing, said in a release. “The Coles smart trolley illustrates our omnichannel approach, leveraging digital capabilities to enrich the in-store experience.”
Transportation leaders, policymakers, administrators, and researchers from government, industry, and academia will gather January 5-9, 2025, in Washington, D.C., for the 104th annual meeting of the Transportation Research Board (TRB), sponsored by the National Academies of Sciences, Engineering, and Medicine.
The meeting’s program covers all modes of transportation and features hundreds of sessions and workshops on various transportation-related topics. The theme for this year’s conference is how innovations in technology, business, and processes help support transportation’s role in a thriving society, according to TRB.
Speakers at this year’s event include TRB executives as well as federal, state, and international government leaders and policymakers. Discussions on zero-emissions freight, supply chain shifts, automated vehicles and roadway digital infrastructure, National Transportation Safety Board investigations, and other topics will take place throughout the week, according to TRB. Held every January in Washington, D.C., the TRB Annual Meeting attracts more than 13,000 attendees from throughout the United States and around the world.
The deal will add the Google DeepMind robotics team’s AI expertise to Austin, Texas-based Apptronik’s robotics platform, allowing the units to handle a wider range of tasks in real-world settings like factories and warehouses.
The Texas firm joins other providers of two-legged robots such as the Oregon company Agility Robotics, which is currently testing its humanoid units with the large German automotive and industrial parts supplier Schaeffler AG, as well as with GXO. GXO is also running trials of a third type of humanoid bot made by New York-based Reflex Robotics. And another provider of humanoid robots, the Canadian firm Sanctuary AI, this year landed funding from the consulting firm Accenture.
“We’re building a future where humanoid robots address urgent global challenges,” Jeff Cardenas, CEO and co-founder of Apptronik, said in a release. “By combining Apptronik’s cutting-edge robotics platform with the Google DeepMind robotics team’s unparalleled AI expertise, we’re creating intelligent, versatile and safe robots that will transform industries and improve lives. United by a shared commitment to excellence, our two companies are poised to redefine the future of humanoid robotics.”
A Canadian startup that provides AI-powered logistics solutions has gained $5.5 million in seed funding to support its concept of creating a digital platform for global trade, according to Toronto-based Starboard.
The round was led by Eclipse, with participation from previous backers Garuda Ventures and Everywhere Ventures. The firm says it will use its new backing to expand its engineering team in Toronto and accelerate its AI-driven product development to simplify supply chain complexities.
According to Starboard, the logistics industry is under immense pressure to adapt to the growing complexity of global trade, which has hit recent hurdles such as the strike at U.S. east and gulf coast ports. That situation calls for innovative solutions to streamline operations and reduce costs for operators.
As a potential solution, Starboard offers its flagship product, which it defines as an AI-based transportation management system (TMS) and rate management system that helps mid-sized freight forwarders operate more efficiently and win more business. More broadly, Starboard says it is building the virtual infrastructure for global trade, allowing freight companies to leverage AI and machine learning to optimize operations such as processing shipments in real time, reconciling invoices, and following up on payments.
"This investment is a pivotal step in our mission to unlock the power of AI for our customers," said Sumeet Trehan, Co-Founder and CEO of Starboard. "Global trade has long been plagued by inefficiencies that drive up costs and reduce competitiveness. Our platform is designed to empower SMB freight forwarders—the backbone of more than $20 trillion in global trade and $1 trillion in logistics spend—with the tools they need to thrive in this complex ecosystem."