Four enterprise software franchises that defined the last software decade entered the summer of 2026 carrying the same wound. Salesforce trades near $152, down roughly a third on the year and off 38% from where it stood twelve months ago. ServiceNow, having executed a five-for-one split in December, changes hands around $95 after surrendering more than half its value from the 2025 peak. Atlassian sits in the low $80s, down some 45% year to date and roughly 74% off its one-year high. Monday.com, the smallest of the group, has lost about 73% over a year and trades in the mid-$60s against a 52-week high near $317.

The May–June 2026 technology conference window is unusually dense, reflecting the sector’s attempt to process several simultaneous inflection points: the industrial deployment of AI beyond the pilot phase, the semiconductor supply chain’s geographic rebalancing, and the maturing of open hardware architectures from academic interest into commercial infrastructure. For investors and operators tracking these transitions, the conference calendar functions less as a social calendar and more as a forward indicator — announcement timing, speaker cancellations, and floor traffic are often more informative than the formal presentations.

ServiceNow has expanded its platform into manufacturing with a suite of AI-native capabilities covering the full value chain from sales and configuration through quality, warranty, and factory-floor operations. The announcement, made alongside the unveiling of Industrial Connected Workforce and ServiceNow EmployeeWorks for manufacturers, positions the company directly against the fragmented stack that characterizes most industrial enterprises.

The core argument is structural. Manufacturing AI investments have accelerated over the past two years, but quality data, warranty claims, order workflows, and shop-floor processes typically run on separate systems with no shared governance layer. ServiceNow’s pitch is that AI cannot deliver end-to-end execution when the data it needs is distributed across siloed tools—and that a single platform with unified workflows changes that calculus.

The manufacturing sector’s AI problem has never been a shortage of tools — it has been the absence of tools that understand what manufacturing actually is. Infor and AWS are now pushing a direct answer to that gap, announcing a collaboration to deploy industry-specific AI agents built natively on AWS infrastructure, targeting discrete and process manufacturing enterprises that need to move from pilot programs to production at scale.

The core argument is that generic AI fails on the shop floor. Manufacturing workflows involve bill of materials hierarchies, vendor pricing cycles tied to annual model changes, returns processing chains, and procurement-to-payment pipelines that off-the-shelf models cannot navigate without substantial domain grounding. Infor’s position is that it supplies the industry-specific intelligence while AWS provides the enterprise infrastructure — Amazon Bedrock AgentCore, Amazon Bedrock, and Amazon SageMaker — to run it at mission-critical reliability.