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December 31, 2025 · The Bloomfield Team

Predictions for Manufacturing in 2026: What We're Watching

Predictions are easy to make and hard to be held accountable for. We are going to make five, explain the reasoning behind each, and commit to revisiting them at the end of 2026 to see where we were right and where we were wrong.

These predictions are based on patterns we observed across small and mid-size U.S. manufacturers throughout 2025, combined with technology adoption data, workforce trends, and conversations with shop owners, operations managers, and estimators. They reflect what we believe will happen, not what we hope will happen.

1. AI Adoption Will Reach 35% Among Manufacturers Under 500 Employees

AI adoption among small and mid-size manufacturers roughly doubled from 12% to 22% between 2024 and 2025. We expect another 60% increase in 2026, driven by three factors: the tools have gotten easier to implement, the business case is now proven by early adopters, and the vendor ecosystem has matured to focus on manufacturing-specific use cases rather than generic AI platforms.

The adoption will concentrate in three areas: quoting and estimating, quality documentation, and customer communication. These are the use cases where the data already exists, the ROI is measurable, and the implementation does not require disrupting production.

2. The Workforce Crisis Will Force Technology Investment

The manufacturing workforce aging curve is not a future problem. It is a current one. The shops that have been discussing it for five years without acting will hit an inflection point in 2026 as the baby boomer retirement wave steepens. An estimated 600,000 manufacturing workers will retire in the United States in 2026 alone.

This will force technology investment that economic arguments alone could not. When the estimator with 25 years of pricing knowledge gives notice, the question shifts from "should we invest in knowledge capture" to "how fast can we implement it." We expect knowledge management and institutional expertise preservation to become the fastest-growing technology category in manufacturing by the second half of 2026.

3. Reshoring Will Accelerate, but the Winners Will Be Shops That Quote Fast

The reshoring trend will continue. Geopolitical risk, supply chain complexity, and domestic manufacturing incentives are all pulling work back to U.S. suppliers. But the shops that capture this demand will not be the ones with the most machines or the lowest prices. They will be the ones that respond to RFQs fastest.

Buyers reshoring supply chains are evaluating five to ten domestic suppliers simultaneously. Response speed is the first filter. The shop that quotes in 24 hours gets shortlisted. The shop that quotes in five days gets ignored. We expect quoting speed to become the primary competitive differentiator for shops pursuing reshored work.

4. ERP Replacement Cycles Will Continue Lengthening

We do not expect 2026 to be the year that manufacturers finally replace their aging ERPs. The cost, risk, and disruption are too high relative to the alternatives. What we do expect is a significant acceleration in the ecosystem of tools that sit alongside or on top of legacy ERPs, extracting data and delivering it through purpose-built applications.

The ERP becomes the system of record. Everything else, the analytics, the AI, the dashboards, the automated reporting, runs on data extracted from the ERP without changing the ERP itself. This approach eliminates the biggest barrier to technology adoption for most manufacturers: the fear of disrupting the system that runs their daily operations.

5. The Gap Between Early Adopters and Laggards Will Become Visible in Financial Results

Through 2024 and 2025, the difference between manufacturers who adopted AI and those who did not was measurable in operational metrics but not yet visible in financial results. In 2026, the compounding effects of faster quoting, better knowledge retention, and data-driven decision-making will start showing up in revenue growth rates, margin improvement, and win rates that are measurably divergent.

The shops that invested in 2024 will enter 2026 with 18 to 24 months of compounding advantage. Their systems are trained on their data. Their teams have adopted the tools. Their processes are optimized around the new capabilities. The shops that start in 2026 will be playing catch-up, and the gap will widen with each quarter.

What We Are Watching

These predictions could be wrong. The economy could slow manufacturing demand. AI adoption could stall if early implementations fail to deliver promised ROI at scale. Reshoring could decelerate if overseas pricing drops. We are watching these risks alongside the trends.

What we are most confident about: the manufacturers that move fastest on information, the ones that turn data into decisions in hours rather than days, will outperform regardless of macroeconomic conditions. Speed in an information-rich environment is the closest thing to a permanent competitive advantage. The tools to achieve it exist now. The question is who builds first.

For a deeper look at how these ideas connect across the shop floor, see our complete guide to AI in manufacturing.