This story originally appeared in the February 2026 issue of Logistics Management. Click here to sign up for the Logistics Management newsletter and stay up to date on the latest news. 

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Supply chain management (SCM) software influences how quickly companies respond to disruptions, how work gets prioritized inside warehouses and how decisions get made across global networks. As these systems take on more responsibility, buyers are judging them less on promise and more on performance.

That reality is reshaping what companies look for in SCM software. Speed, visibility and execution matter more than feature breadth, while implementation, integration and human oversight remain central to success. Here are eight important SCM software trends shaping how companies plan, execute and adapt their supply chains:

1. Faster disruption response is becoming a core software requirement 

Speed of response is emerging as one of the clearest gaps between supply chain expectations and reality, according to Shashank Mane, VP, go-to-market leader for manufacturing at Capgemini. Citing recent industry survey data, he says that just 17% of global supply chains can respond to disruptions within 24 hours, and some top performers take much longer than expected to recover after a disruptive event.

“Even the 17% of supply chain organizations that can respond quickly can take an average five total days to respond,” says Mane. Regional data paints an even starker picture, with 57% of industries requiring up to six months to recover from a one-week transportation disruption.

This growing mismatch is shaping the evaluation process for supply chain software, with buyers placing greater emphasis on tools that shorten the time between disruption detection and action. So rather than relying on static planning cycles, companies are looking for platforms that integrate real-time alerts, live dashboards and decision support into a single workflow, says Mane, who expects response speed is becoming a practical benchmark for SCM platform performance in 2026—and beyond.

2. Intraday execution is becoming more responsive inside the four walls of the warehouse 

For years, warehouse and logistics managers have depended on experienced supervisors to spot imbalances and reassign labor during a shift. That approach still matters, but Howard Turner, director of supply chain execution systems at St. Onge Co., says SCM software is starting to close the gap between visibility and action.

Turner singles out workload balancing as one of the most practical advances now reaching the floor. Systems can track productivity and remaining work across zones and flag when labor needs to move. “Intraday planning has been something that shippers have been after for a long time,” he explains, “but it was really difficult to do before.”

By monitoring conditions continuously instead of relying on periodic dashboard checks, SCM platforms are helping teams respond while work is still recoverable, and not after service levels slip. Turner sees this as a practical step forward for execution teams, especially in environments that are handling mixed order profiles, where workload can shift quickly between e-commerce and wholesale operations.

3. Digital twins and AI add context to SCM decision-making 

Clearly, AI is now embedded across most supply chain platforms, but Mane cautions that the technology can’t actually solve core supply chain problems on its own. In fact, most implementations are still narrow and tied to individual functions. “Most of the AI use involves point solutions,” he says, noting that common uses include demand forecasting and route optimization.

This year, SCM buyers are increasingly asking whether AI can support decisions across planning and execution instead of just being used within those isolated modules. Mane says interest is also growing in digital twin capabilities, which let companies simulate disruptions and test responses before acting. Digital twins provide context, he explains, while AI helps teams evaluate options and trade-offs more quickly.

Looking ahead, Mane sees integrated use of data, AI and digital twins as a step toward more adaptive operations. “That is where I think companies will be able to drive continuous optimization,” he says, “and even greater supply chain resilience, in certain cases.”

4. Agentic AI is moving into day-to-day SCM workflows

Agentic AI is starting to show up in real supply chain operations, not just pilot projects, according to Rishabh Narang, director analyst, supply chain practice, at Gartner. Unlike traditional AI tools that make recommendations for humans to review, agentic AI uses software agents that can monitor conditions, make decisions and take action within defined limits.

Gartner projects that by 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024, and at least 15% of day-to-day work decisions will be made autonomously through these agents. “That’s not incremental change,” Narang adds, “it’s a structural transformation in how logistics technology operates.”

Here’s how that transformation plays in the real world: Instead of routing every decision through large warehouse or transportation management systems, for example, companies may be able to offload specific tasks to agents that handle discrete workflows.

Narang says organizations are also deciding which decisions stay inside core platforms and which can be handled externally—a choice that affects governance, vendor relationships and the evolution of systems over time.

Narang adds that companies are taking different approaches when integrating agentic AI into their supply chain operations. Some are using bolt-on applications from niche vendors to automate standardized tasks like freight tendering or exception handling. Others are using agents embedded within their existing WMS or TMS platforms.

A smaller but growing group is using low-code tools to build agents for specialized needs. Regardless of the approach, he says the broader conversation has shifted from “should we explore AI agents?” and over to “which deployment model fits our operational maturity?”

5. Reporting and network visibility are shifting from static outputs to operational dialogue 

There’s been a fundamental change in how operators access and use supply chain information across facilities and networks, according to Turner. He says traditional reporting models relied on predefined templates that pulled fixed data sets and required IT involvement whenever needs changed.

“The previous model was very static,” Turner says, “and it often lagged the pace of daily operations.” Today’s SCM platforms increasingly allow users to query systems directly and get immediate, context-aware answers. So instead of running a standard report, for example, an operator can ask how many inbound trucks to expect on a specific day, whether that volume is typical and how it might affect staffing or dock capacity.

Turner says this shift matters because it reduces dependence on IT resources and shortens the time between question and action. “You’re no longer waiting on someone to build a report,” he says. “Instead, you’re asking the system and getting a fast answer you can act on.”

As companies push for better network-wide visibility, Turner adds that the approach will also help companies connect real-time data with day-to-day execution, versus treating reporting as a separate, back-office function.

6. Limited visibility across supplier networks persists

Mane also says that most organizations still lack insight beyond their closest suppliers. “Sixty percent of companies have visibility into their tier-one suppliers,” he says, noting that visibility drops sharply beyond that point, falling to 21% at tier two and dropping to just 2% at tier three.

Even large enterprises often operate with limited awareness of conditions deeper in their supplier networks, he adds, leaving them reactive rather than proactive when issues arise upstream.

SCM providers are working to close those gaps, but Mane says progress on that front remains “uneven” at best. Internal enterprise data from systems such as ERP, WMS and TMS platforms is relatively straightforward to consolidate, for example, but the greater challenge lies in integrating external data from suppliers, carriers, plants, warehouses and sensor-based sources such as GPS, IoT and RFID. While platforms are improving their ability to merge these data streams into usable views, Mane describes the effort as “a mammoth of a task.”

7. SCM buyers are paying closer attention to the software implementation process 

Narang says companies are paying closer attention to how SCM actually gets implemented, and not just what it promises to do. Cautious buyers want to know how long systems really take to roll out, how much internal effort is required and whether platforms work as advertised once they’re live.

“The evaluation process has matured considerably,” Narang says. Rather than rely on feature checklists, for example, companies are spending more time talking to customer references, reviewing implementation approaches and asking how systems perform in live operating environments.

The scrutiny extends beyond rollout timelines. For example, Narang says buyers are looking closely at how well systems connect to existing WMS, TMS and ERP platforms rather than evaluating features in isolation. “This is particularly critical as organizations consider agentic AI deployment,” says Narang, “[because] agents require seamless data integration across WMS, TMS and IoT platforms to function effectively.”

8. The next leap in SCM software isn’t technical. It’s organizational and human-led

Gartner projects that by 2028, at least 15% of day-to-day work decisions will be made autonomously through agentic AI. This year, Narang says leading organizations will have multiple agents in production across freight procurement, exception management, labor planning and dock scheduling, and all operating within well-defined guardrails.

Narang also expects legacy SCM platforms to face capability gaps. “Leading logistics technology providers are delivering embedded AI agents as cloud-first solutions, [while] organizations still running legacy or on-premises systems will find themselves unable to access advanced capabilities,” he points out. “Platform upgrades will become essential for organizations seeking to capitalize on agent-driven innovation.”

For now, at least, Narang says that the vision of the “fully autonomous supply chain operation” remains a distant dream. “The complexity, variability and consequence of most supply chain decisions require human judgment for the foreseeable future,” he concludes. “Automation of specific tasks within human-defined parameters will advance; replacement of human decision-making will not.”