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Construction companies need 499,000 new workers in 2026 to meet project demand. They won't find them. The labor shortage that has plagued the industry for years shows no signs of easing, and the firms that survive the next decade won't be the ones that somehow solve the hiring crisis. They'll be the ones that figure out how to do more with the teams they have.
That calculation explains why Acumatica's announcement of an "AI-first" product strategy matters for construction. At Summit 2025 in Las Vegas, the company outlined a plan to embed artificial intelligence directly into enterprise resource planning workflows, specifically targeting the inefficiencies that drain resources from mid-market companies. For an industry where 42% of firms cite skilled labor shortages as their most significant financial struggle, the timing reflects urgency rather than trend-chasing.
Construction operates differently than other industries where AI has gained traction. Software companies can iterate and fix mistakes post-launch. Construction has no undo button. Once concrete is poured or steel beams are placed, changes cost millions and delay timelines by weeks. The industry needs precision at the planning stage because the margin for error after execution is essentially zero.
This reality has made construction historically slow to adopt new technology. Recent research shows only 27% of architecture, engineering, and construction professionals currently use AI in their operations, even as 94% of that group plans to increase usage in 2026. The gap between awareness and adoption stems from legitimate concerns about complexity, cost, security, and whether new tools will integrate with existing systems.
Acumatica's approach addresses these barriers through what Chief Product Officer Ali Jani describes as a customer-first philosophy. According to the company's March 2025 press release, "While others rush AI to market to serve their interests, we focus on capabilities that solve real-world problems." The distinction matters because construction companies don't need AI features for the sake of having them. They need tools that reduce the 11 hours per week project managers spend on administrative tasks, improve the accuracy of job costing that determines profitability, and help finance teams process payroll faster without adding headcount.
Acumatica structures its AI capabilities around three functions, each addressing specific operational needs. The company refers to these as Intelligent Advisors, AI Automation, and Interactive Assistants.
Intelligent Advisors identify issues and recommend solutions. The flagship example is Anomaly Detection, introduced in the 2024 R2 release and currently available in production. The system continuously scans transactional data to flag unusual patterns. For construction companies, this means catching situations where a vendor's invoice is significantly higher than historical averages, or where material costs spike unexpectedly on a project. Chief Engineering Officer Miten Mehta describes these advisors as "on-demand data scientists" that automatically find patterns human reviewers would take hours to spot.
The system learns from company-specific data patterns over time, improving accuracy as it processes more transactions. When anomalies appear, managers see them highlighted immediately rather than discovering problems weeks later during month-end close or project reviews.
AI Automation handles repetitive tasks with minimal human intervention. Current examples include invoice categorization and upcoming features like case resolution summary generation. For construction companies managing hundreds of vendor invoices across multiple projects, automation reads supplier invoices, extracts information including vendor details, amounts, and dates, then populates the correct fields in the accounting system. When approvers make changes during review, the system learns from those modifications and applies the knowledge to future invoices.
Interactive Assistants allow users to interact with ERP systems through natural language rather than navigating menus and screens. The assistant retrieves information and presents it in context, reducing the cognitive load required to complete complex activities. According to Acumatica's blog post on AI Interactive Assistants, these tools enable users to ask questions and receive instant answers with visualized results. Development for interactive assistants is planned for 2025 and beyond.
The introduction of AI Studio in Acumatica 2025 R2 as an experimental feature represents a shift in who can implement automation. Traditional ERP customization required programming expertise and IT department involvement. AI Studio uses a low-code framework that allows business users to create automated workflows without writing code.
The system works through a five-stage process. Users define which fields an automation should update, specify the data sources it should consider, and set conditions that trigger the automation. Configuration happens through visual interfaces with testing capabilities that let administrators preview how automation will behave before enabling it for production use.
Jeremy Larsen, Acumatica's VP of Product Management, explained the philosophy in a December 2024 interview: "The 2025 R2 release solves a core challenge facing many mid-market companies—how to make AI more accessible, meaningful, and truly usable in day-to-day workflows." The system embeds assistive AI directly into the interface, allowing users to apply automation anywhere regardless of which product feature they're using.
Currently, AI Studio focuses on document-level automation for sales orders, cases, inventory items, and similar record types. The system updates or deletes field values within a single document but does not yet create detail lines or work across multiple records simultaneously. Full production release is planned for 2026 R1.
For construction companies, this means finance staff can configure automations for common tasks without waiting for developer resources. A project accountant could create a workflow that suggests cost codes based on vendor history and item descriptions, or validates timecard entries against employee certifications and prevailing wage requirements.
The construction industry faces challenges where AI automation delivers measurable impact. Project margins are tight, often in the 2-5% range for commercial work. Small errors in job costing, payroll, or billing compound into significant losses. Manual processes for tracking labor hours, validating prevailing wages, processing certified payroll, and managing union reporting create opportunities for mistakes that affect profitability.
Consider payroll validation. Construction workers often move between job sites with different prevailing wage rates, work classifications, and compliance requirements. A worker might be classified as a journeyman electrician on one project and a foreman on another, with different hourly rates and fringe benefit calculations for each. Manual systems require payroll administrators to verify that each timecard reflects the correct classification, location, and rate. Mistakes trigger costly corrections and potential compliance violations.
AI-powered systems validate timecards against employee history, project schedules, and regulatory requirements before processing payroll. If a timecard shows an employee working 14 hours in a single day or present at two locations simultaneously, the system flags the discrepancy for review. When prevailing wage rates differ between project locations, the system verifies that pay rates match the correct jurisdiction.
Job costing presents similar opportunities. Construction projects involve hundreds of transactions—labor hours, material purchases, equipment rentals, subcontractor invoices. Each transaction needs proper coding to track costs against budgets at the phase and cost code level. Workers might use incorrect codes, or vendors might bill materials to the wrong project. AI systems suggest appropriate cost codes based on vendor history, item descriptions, and project context, reducing coding errors that distort project profitability data.
According to Deloitte's 2026 Engineering and Construction Industry Outlook, the industry faces potential losses of nearly $124 billion if labor shortages persist. Construction wages have increased 4.2% year-over-year as of August 2025. These pressures make operational efficiency critical. Companies that reduce the time spent on manual data entry and validation can redirect those resources to higher-value activities like project planning, client relationships, and business development.
Construction companies handle sensitive project data, employee information, and financial records. Moving this data to AI systems raises questions about security and privacy. Acumatica addresses these concerns through architectural decisions and transparency about data handling.
The AI Service Gateway serves as a controlled connection point between Acumatica instances and AI services. When using external large language models from providers like OpenAI or Azure, the gateway manages the communication. Customer data passes through Acumatica's secure cloud infrastructure rather than connecting directly to external services.
For AI Studio automations, only the specific data included in prompt templates leaves the customer's Acumatica instance. Administrators can see exactly what information the system will send before enabling an automation. The LLM Prompts configuration screen shows the generated prompt text, allowing review to verify that sensitive data isn't inadvertently included.
Data masking capabilities, planned for 2026, will automatically anonymize sensitive information before sending it for AI processing. The system replaces actual values with masked tokens, processes the request with the masked data, then reverses the masking when applying results back to the original records.
Chief Information Officer Jeff Smits addressed security concerns in the Summit 2025 Day 2 Keynote: "We understand that you have entrusted us with your most sensitive business data. That's why, at Acumatica, security isn't just a feature. It is fundamental to our architecture." He confirmed that Acumatica will not expose customer business data to public large language models, and that AI systems are built with privacy-by-design principles.
For construction companies subject to data privacy regulations and client confidentiality requirements, these safeguards matter. Project data often includes proprietary information about costs, methods, and competitive advantages. Employee data includes Social Security numbers, wage rates, and personal information protected under various privacy laws.
AI adoption changes workflows, which means it affects people. Construction companies implementing AI automation need to address both technical and human factors.
The technical implementation follows a phased approach. Rather than attempting full-scale deployment across all processes simultaneously, successful implementations start with one or two high-impact areas. Accounts payable invoice processing is a common starting point because benefits are measurable—fewer data entry hours, faster approval cycles, reduced payment errors. Companies can demonstrate value with this initial project before expanding to payroll validation, job costing, or other areas.
The human factor requires attention to how automation affects individual roles. An accounts payable clerk might worry that automation eliminates their job. In practice, automation typically shifts the role from data entry to exception handling and vendor relationship management. The clerk reviews flagged exceptions, resolves discrepancies with vendors, and focuses on process improvement. This shift requires different skills—less typing accuracy, more analytical judgment.
Training needs differ from traditional software training. With AI systems that learn and adapt, users need to understand not just what buttons to push but how the system makes decisions and when to override its suggestions. If an AI system suggests an incorrect cost code, users should know how to make corrections that help the system learn.
According to survey data from Bluebeam, 69% of architecture, engineering, and construction professionals say uncertainty around potential AI regulations has affected plans to implement the technology. The skills gap is real, with 23% of respondents mentioning difficulty keeping up with rapidly changing technologies. Bluebeam CEO Usman Shuja notes that "the biggest barriers to AEC technology adoption in 2026 aren't cost—they're complexity, culture, and connection."
Construction firms can address these barriers through structured change management. Clear communication about how automation affects roles, comprehensive training programs, and visible support from leadership help ease transitions. Companies that treat AI implementation as a people initiative supported by technology tend to see better adoption than those that treat it as a technical project imposed on users.
Acumatica's AI-first strategy reflects broader patterns in enterprise software. IBM reports that global AI adoption surged from 50% to 72% in the past year, with professional services seeing the most significant growth. The construction industry lags other sectors in adoption but is expected to become one of the most AI-first industries in 2026. Research from IFS found that 91% of construction and engineering firms expect to increase AI investment in 2026.
This acceleration stems from converging pressures. Labor shortages continue, material costs remain volatile, and project complexity increases as clients demand faster delivery and better documentation. Digital transformation is no longer optional for construction companies that want to remain competitive.
The global AI market in construction is projected to reach $1.6 billion in 2026, with growth expected to exceed $20 billion by 2034, according to Precedence Research. This investment reflects recognition that AI addresses fundamental industry challenges rather than providing marginal improvements to existing processes.
For mid-market construction companies specifically, AI levels the playing field. Large enterprises have IT departments that can build custom automation using programming tools and APIs. Small companies lack the transaction volumes that make automation worthwhile. Mid-market companies occupy the space where automation delivers significant benefits but traditional implementation approaches are too complex or expensive.
Low-code AI tools like Acumatica's AI Studio change this equation. When business users can configure automations through visual interfaces rather than requiring developer resources, implementation becomes faster and less expensive. When AI systems provide pre-trained models for common tasks like invoice processing or cost code suggestion, companies avoid the data science work required to build these capabilities from scratch.
Acumatica Summit 2026, taking place January 25-28 in Seattle, will provide construction companies with detailed information about AI capabilities and implementation strategies. The conference moves from Las Vegas to Seattle's Convention Center to accommodate growth. More than 3,500 attendees are expected, up from previous years.
The agenda includes AI-focused content throughout. The Hackathon, running January 24-25, challenges participants to build solutions using AI Studio. Last year's winning project created AI-powered automation that extracted sales orders from customer emails. Construction-specific sessions examine how AI addresses industry challenges in payroll validation, job costing, and project management.
Lumber, a workforce management platform that integrates with Acumatica, presents a session titled "Intelligent Back Office: Reinventing Construction Finance with AI" from 1:30 PM to 2:30 PM. The session examines how the finance role in construction is being rewritten, shifting from paper trails and manual workflows to predictive insights and automation. Finance leaders will learn what new skills they need and how integrating workforce management with AI-powered job costing unlocks competitive advantages.
Click here to prebook a meeting with Lumber Experts
Technical sessions will cover AI Studio's evolution from experimental feature to production capability. Attendees will learn about new automation capabilities, additional business processes that support AI workflows, and tools for monitoring and managing automated actions in production environments. Partners in the Summit Marketplace will demonstrate how integrated solutions extend Acumatica's AI capabilities for construction-specific needs.
Construction companies evaluating Acumatica's AI-first strategy should focus on specific business outcomes rather than AI capabilities in abstract. The relevant questions are practical: How much time do project managers spend on administrative tasks that automation could handle? How often do coding errors in job costing distort project profitability data? How many hours does payroll processing take, and how many corrections are required after each pay period?
Companies with clear answers to these questions can evaluate whether AI automation addresses their specific pain points. The experimental status of AI Studio in the 2025 R2 release provides an opportunity to test capabilities with real data before committing to production use. When the feature reaches full release in 2026 R1, companies that participated in the experimental phase will have concrete experience informing their decisions.
The construction industry's slow adoption of AI reflects legitimate concerns about complexity, cost, and integration with existing systems. Acumatica's approach addresses these concerns through practical applications that solve real business problems, low-code tools that reduce implementation barriers, and security measures that protect sensitive data. Whether this approach overcomes industry resistance remains to be seen, but the strategy aligns with the operational realities construction companies face.
For construction firms planning to attend Summit 2026, the focus should be on understanding how AI automation fits into existing workflows, what implementation requirements exist, and what measurable benefits can be expected. The conference provides opportunities to see demonstrations, speak with other construction companies that have implemented AI capabilities, and evaluate whether the technology addresses specific business challenges.
Construction companies looking to prepare for the event can access Lumber's comprehensive checklist.
Register for Acumatica Summit 2026 in Seattle (January 25-28) to see these AI capabilities in action.
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