Eric Yan is the Senior Director of Business Strategy and Chief of Staff at MaintainX.
I’ve spent the last decade investing in or operating at B2B software companies, and a trend I’ve observed is that B2B software innovation up until this point has centered overwhelmingly on a narrow slice of the workforce: desk-based jobs. This focus led to some of the world’s largest companies—CRM systems like Salesforce and HubSpot, project management tools like Asana and Monday.com, and workflow automation platforms like Atlassian and ServiceNow. Companies like these have driven exponential productivity improvements for knowledge workers—and created trillions of dollars in shareholder value in the process—but their success hinges on an increasingly fragile premise: that the human-centric workflows they support will remain relevant in a world of AI.
Now, as AI advances, these software providers face an existential threat. If AI automates sales outreach, autonomously generates reports or manages projects with little human input, the software tailored to enable those digitally native, desk-based workflows risks becoming collateral damage, whether it be through price erosion or displacement altogether—a dynamic unique to sectors where work exists primarily in the digital realm.
The Permanence Of Physical Work In An AI-Powered World
The next wave of B2B software innovation will empower the workers who keep the physical world running and operate in a realm where outcomes are tied to physical actions. These physical workers, such as those working in manufacturing plants, hospitals, construction sites or warehouses, represent 80% of the global workforce. Yet, they’ve been underserved by software, receiving only 1% of global venture funding.
As AI matures, a seismic shift is underway: The future of enterprise software will belong to platforms that bridge the gap between digital intelligence and physical execution, like repairing machinery, administering patient care and stocking shelves. This creates a durable market for B2B software that enhances (rather than replaces) human labor. AI here isn’t an existential threat, but a force multiplier that can equip front-line workers with superhuman intelligence. In my opinion, the next B2B software decacorns and centicorns will be the ones that successfully bridge AI with real-world execution.
Why Now Is The Tipping Point For Software Built For Deskless Jobs
1. The Aging Workforce Crisis Meets AI’s Knowledge-Capture Power
Deskless industries are grappling with an expertise exodus as seasoned workers retire. According to the Bureau of Labor Statistics, 24% of production workers are over 55 and the median age of U.S. farmers is 55. This threatens operational continuity, but AI offers a solution: Machine learning models can now codify decades of institutional knowledge into real-time decision support. For example, an AI assistant can guide a junior technician through complex repairs by analyzing the corpus of historical maintenance data and OEM manuals, or warn a new construction crew about site-specific safety risks learned from past incidents.
2. AI Finally Speaks The Language Of Physical Work
I’ve seen how early enterprise software struggled to interface with the messy, dynamic realities of deskless environments. However, advances in AI have unlocked tools suited to physical workflows. For example, alwaysAI leverages computer vision to enable defect detection on assembly lines with superhuman accuracy; our company uses generative AI to simplify complex and lengthy OEM manuals into standardized work orders and procedures for technicians via a mobile app; and several venture-backed machine health AI companies are working on predictive analytics to synthesize vast amounts of IoT sensor data into actionable alerts (e.g., “replace this bearing within the next week to avoid machine failure”).
3. Lower Barriers To Software Adoption In The AI Era
I’ve found that digital transformation in deskless industries often stalls due to adoption inertia, typically from lengthy and costly time-to-value. But AI is rewriting the rules of engagement. Intuitive interfaces like voice-to-text, augmented reality overlays and natural language queries eliminate the need for typing or training. Mobile-first presentation layers in a world where the vast majority of deskless workers already carry smartphones make AI-powered mobile applications a natural extension of their routines. And AI is streamlining setup processes that once deterred adoption (e.g., auto-creating maintenance work orders based on IoT sensor data). The result? Deskless workers no longer have to adapt to software—the software adapts to them.
Potential Industry Challenges
1. Fragmentation And Quality Of Input Data
Input data in deskless environments is highly fragmented—from handwritten logs to printed OEM manuals to sensor and operational data on unnetworked machines. Aggregating the corpus of relevant input data will be a key challenge for software companies to navigate, but those who succeed at it will build defensible data moats.
2. Thin Customer Margins And High ROI Thresholds
Deskless industries, such as retail, manufacturing and logistics, typically operate on razor-thin margins—often less than 15% EBITDA margins—compared to the 30%-plus EBITDA margins common in desk-based sectors. This means that ROI is often highly scrutinized and must be measurable to justify adoption. Solutions that demonstrate direct cost savings (e.g., reduce unplanned downtime) or revenue uplift will win.
3. Operational And Financial Complexities From Selling Associated Hardware
Many AI-driven software platforms for deskless industries sell bundled hardware to deliver a turnkey solution. For example, Samsara sells IoT sensors, dashcams and GPS trackers with its fleet management software. Selling hardware introduces operational and financial challenges that desk-based SaaS companies often don’t have to navigate, like supply chain management (including manufacturing), inventory and warehousing, logistics and distribution, and reverse logistics (returns, repairs and refurbishments). Collectively, these challenges can erode margins and are capital-intensive, so it’s critical that bundled hardware-software solutions can sell based on value (rather than cost).
The Path Forward: Building Where Bits Meet Atoms
The deskless workforce represents the final untapped frontier for B2B software—a vast market where AI’s value isn’t about replacing humans, but elevating them. As these industries confront an aging workforce, labor shortages and cost pressures, the companies that thrive will be those delivering AI-powered software that works with humans—not around them—becoming the operating system for entire industries. In B2B software, the greatest opportunity lies where bits meet atoms.
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