The year 2025 was seriously crazy for US businesses, and though the chaos may start to feel like “the new normal” simply due to familiarity over time, that doesn’t actually help much when planning for the coming weeks and months. For demand and S&OP teams, it’s worth considering some top trends that have become relevant for the coming year. We’ve selected 5 demand and forecasting trends that we feel deserve your attention.

1. AI can augment human expertise, but doesn’t replace it

If 2025 was the year of AI adoption (or at least intense buzz and consideration), 2026 might be the year of the bursting of the AI bubble in many industries. In October 2025, Yale leadership wrote “the tangle of AI deals among tech giants could be signs of dangerous overinvestment in the developing technology.” As more businesses have been testing and using AI in various applications across organizations, the limitations and benefits of the burgeoning technology are becoming more clear.

The well-known programming axiom GIGO (garbage in, garbage out) has never been more appropriate. AI learning can become limited depending on the resources it uses to “learn” and the parameters it is asked to work within. Moreover, generative AI is now making way in some applications for agentic AI, with the power to make decisions and take actions when appropriate. Agentic AI is given the capacity to act proactively instead of waiting for direct input. While legacy systems are reactive in nature, agentic AI systems are able to anticipate needs and identify patterns, and then enact processes or make decisions to address potential issues. Obviously, this is not ideal in every industry nor for every company. For S&OP and demand planning, we feel that AI-assisted tools and data analysis enable company leadership to stay flexible by providing human decision-makers the ability to simulate scenarios, run more analytics, and make more strategic judgments.

2. Collaboration across teams is a requirement

For 2026, cross-team collaboration and regular company-wide S&OP updates are not just a good idea… they’re an absolute must. Demand planning must be an integrated function of effective S&OP (ideally as a part of a holistic, cohesive integrated business planning or IBP process) and all parties should be prepared for weekly, if not daily updates and potential revisions to the plan as more data is gathered and forecasted vagaries become more clear. Compartmentalized silos or workflows where data and planning are not integrated into all aspects of the process, or where departments’ tasks are immune from innovation or constructive criticism from other departments, are outdated.

• Marketing and sales teams should provide timely and accurate demand assumptions to the demand team: Demand planners rely on accurate and timely data. Much of that data comes from the sales and marketing teams (and often production teams have relevant data to contribute to demand planning). If sales or marketing can’t provide timely or accurate demand assumptions or sales data, then the demand team can’t develop a relevant forecast.
• Sales and marketing teams should actively work to sync their marketing and sales efforts with the demand forecast: Just as the demand team relies on sales and marketing for accurate forecast data, the respective marketing and sales teams must trust the demand manager’s forecast, assumptions, and recommendations when developing marketing efforts and/or sales strategies. All teams benefit from this structured strategy.
• All functions in the business should utilize the demand planner’s numbers: When the demand manager/planner provides a data-supported, scenario-tested forecast, the other teams in the business should use that data as the basis for developing their own strategies and action items (until additional data or circumstances require a revision/redirection). They shouldn’t second-guess the demand planner’s figures or develop their own plans. Concerns or discrepancies will be addressed during the analytics and data-gathering phases of the planning cycle, and of course the demand manager should take all differing opinions and data into account when preparing the final forecast. However, once those concerns have been addressed and scenarios tested sufficiently, the numbers presented by the demand team should be considered gospel, until further data becomes available and any tweaks are made during the normal monthly cadence.

3. Flexibility is more important than raw process efficiency

Today, reacting and adjusting quickly, along with flexible thinking/strategizing, is more valuable than a “perfect” initial forecast (which experienced planning leaders know is impossible to achieve anyway), or a rigid, but efficient plan. Demand planners (along with supply chain managers and everyone else across today’s organizations) must not only try to accurately predict or forecast for future events and trends, but must also immediately react and readjust those forecasts when new data is available. Just as it is often said in business management that it’s not the big that eat the small, but it’s the fast that eat the slow, it could be said in modern demand planning that being flexible is more important than being perfectly “accurate,” especially if that supposed accuracy is based on outdated data gathering strategies and habit-bound processes.  

4. Scenario planning (and running intelligent simulations) is vital

In concert with number 3, today’s planners need to remain flexible and not be married to just one forecast scenario. Certainly, the planning team and the business needs to determine the most likely course and act on it. However, the best AI enabled data tools allow multiple scenario simulations and provide teams with the ability to remain flexible, harmonize data, run more analytics, and make more effective strategic decisions in today’s rapidly changing, often chaotic business environment. As a fluid market begins to solidify in some areas and more reliable data becomes available, teams can use that data to run updated scenarios in order to make better decisions.

5. Maintaining a large buffer inventory can backfire and cause supply chain disruptions in some cases

Let’s be clear: When planning for inconsistent demand or to mitigate serious supply chain disruptions, creating a data-supported, reasonable stockpile or buffer inventory can be appropriate in many cases. Based on the craziness of 2025’s volatile market space, many companies are opting to transition a bit further away from just in time (JIT) manufacturing or inventory management to more scenario-based philosophy that provides a greater cushion against supply chain disruptions.

Many businesses whose supply chains rely on international trade were left holding the proverbial bag in 2025 due to the near-daily shifts in tariff rates, off-again, on-again duties, and catastrophic supply interruptions. In this uncertain environment, organizational leadership may insist on increasing inventory/warehousing. However, this isn’t always the best way to go and can itself result in significant disruptions and additional costs/losses, particularly in the case of Food & Beverage firms and adjacent businesses that must account for expiration dates and/or spoilage as well as the normal resources required for greater inventory maintenance. Rather than investing in a blanket increase in inventory without reconsidering its operational validity, a better approach is to utilize AI-informed scenario/simulation generation, use more informed analytics, and make data-supported, more profitable strategic decisions.

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