Tech Explained: Here’s a simplified explanation of the latest technology update around Tech Explained: AI Won’t Replace Demand Planners, It’ll Decide Which Ones Succeed in Simple Termsand what it means for users..
2026 is shaping up to be a year of ongoing disruption and unpredictability, and for small and mid-sized businesses (SMBs), that’s already a reality. The World Economic Forum calls this “structured volatility,” meaning disruption isn’t episodic or unexpected but is embedded in the system itself.
In the 2025 Netstock Benchmark Report, nearly two-thirds (63%) reported that tariffs affected their operations, often increasing costs as they worked to keep customers satisfied.
Yet teams still rely on planning methods built for a calmer world. Historical averages, static forecasts, and quarterly planning cadences were built for stability that no longer exists. These tools and techniques, which worked when variability was the exception, are struggling in an environment where change is constant. Today, success for supply chain leaders depends on the ability to predict disruption and optimize resources to operate proactively, rather than reactively.
Why volatility hits SMBs first and hardest
Not all volatility is created equal, and its impact is not evenly distributed. Large enterprises often respond with larger planning teams, dedicated data science resources, or complex scenario models. SMBs don’t have that luxury.
SMBs operate with lean planning teams by necessity. In some cases, demand planning is handled by a single individual balancing forecasting alongside purchasing, inventory management, and supplier coordination. Budgets are tighter, and time becomes the most constrained resource of all. In this environment, the cost of being reactive is higher but so is the cost of overcorrecting. SMBs can’t afford to chase every signal or hold excess inventory “just in case.”
Yet these teams are expected to respond to the same level of volatility as global enterprises, often with fewer buffers and far less margin for error. The challenge isn’t simply forecasting better, it’s doing so without adding headcount, without expanding budgets, and without burning out the people responsible for keeping the business running.
What high-performing SMB teams do differently
Despite these constraints, some SMBs consistently outperform their peers. Adaptability, a unique strength of these smaller teams, is moving the needle. While real-time visibility is a pipe dream amidst fast-moving supply chains, refreshing forecasts more regularly to stay current with changing conditions is a meaningful step in the right direction.
Netstock’s 2025 Benchmark Report found that top-performing teams have the visibility from the right tools to update their forecasts 3.2 times more frequently than lower-performing peers. Crucially, these gains are not driven by larger teams or more complex processes. They come from removing friction, reducing the manual effort required to refresh forecasts, and focusing attention where it matters most. Rather than attempting to predict demand perfectly months in advance, these teams prioritize staying aligned with current conditions. Signals are reviewed more often, risks are identified earlier, and adjustments happen before problems cascade.
For SMBs with limited resources, this shift can make a real difference. Lighter processes mean frequent updates don’t feel like extra work. And when volatility is the norm, being able to react quickly is more valuable than having a complicated model.
AI as a critical advantage for resource-constrained teams
Much of the conversation around AI in planning centers on automation and end-to-end decision-making. For lean teams, the more practical value lies elsewhere: in AI’s ability to act as a digital assistant, handling repetitive, time-consuming work that small teams simply don’t have the capacity to manage manually.
Modern demand planning generates more data than a single person, or even a small team, can realistically process. AI tools are designed to recognize patterns across that complexity, continuously evaluating signals and surfacing risks that require attention.
Instead of reviewing every product, every location, every time period, planners can focus on a prioritized set of issues – those most likely to impact inventory, service levels, or cash flow. AI provides immediate focus, offering critical context and allowing human judgment to be applied where it matters most.
When teams can see demand risks in dollars and cents, decisions are made faster. It empowers planners to focus on anticipating challenges rather than responding after the fact. Anticipating tariff pressures, 30% of SMBs in 2025 classified a substantial portion of excess inventory as a strategic buffer against volatility, while others are balancing service levels and growth, with nearly half achieving over 90% service and 93% expanding product lines despite market headwinds.
For SMBs operating with one or two planners, this clarity is business-critical. With limited resources, every decision matters. AI doesn’t replace planners; it gives them back the time they’d otherwise spend on constant manual monitoring.
The expanding role of the demand planner
Structured volatility is the new baseline, but that doesn’t mean SMBs are destined to fall behind. AI is no longer a possibility for SMBs; nearly half are already using AI in supply chain planning, and over 75% are open to delegating inventory processes to AI. This suggests a practical, confidence-building shift toward human-machine collaboration.
Success in demand planning will increasingly favor teams that adapt quickly, update frequently, and leverage technology to expand their capacity. AI won’t replace demand planners, but it may be what separates teams that forecast with confidence from those perpetually reacting to surprises.
The biggest advantage today isn’t size or data. It goes to lean teams with full visibility and the speed to act before conditions shift.