Reliance on AI to Drive Tasks and Bolster Customer Experience Grows; Success Driven by Strong AI/SaaS Partnerships, Connected Data and Processes
Propel Software, creator of the first product value management (PVM) platform that transforms how businesses create, market, sell, and service products, provides its annual business and technology predictions for the coming year. Propel CEO Ross Meyercord identifies five key trends for 2027.
AI Shifts From SaaS Killer to SaaS Kingmaker
The SaaSpocalypse narrative will give way to a new reality: AI and SaaS grow stronger together. AI companies will find more value in partnering with established SaaS providers, while SaaS companies will use AI to create sharper, more valuable customer experiences. The gap will widen between platforms with deep, connected capabilities and those with cursory bolt-on features. SaaS providers that move quickly to connect their data, workflows, and AI strategy will be positioned for sustained growth. Those with disconnected data and processes will lose out on the next round of AI-driven growth.
AI Evolves from Human in the Loop to Human in the Audit Trail
As experienced subject matter experts train AI on proven processes, their knowledge will become embedded in the systems teams use every day. Over time, newer employees may not have the same depth of experience to challenge AI recommendations. For established, repeatable work, organizations will increasingly trust AI to make the right call and complete tasks faster without constant human review. These tasks will be flagged as AI generated with detailed audit logs to allow for periodic reviews and audits by humans. Human expertise will remain essential for designing new processes, handling exceptions, and setting the standards AI follows.
Care Continues its Move From Facilities to the Home
Healthcare delivery will continue shifting beyond hospitals and ambulatory surgery centers and into patients’ homes. An aging population, combined with advances in wearables, remote monitoring, connected implants, and home diagnostics, will make this model more practical, necessary and cost effective. MedTech companies will need to design products and product experiences for continuous use outside clinical settings. That requires reliable product data, connected teams, and a clear view of every change across the product lifecycle. AI-assisted monitoring of this data is a must as the volume of inbound data will overwhelm human teams.
Manufacturers Rebuild Their Tech Stacks to Optimize AI
Companies will shift from adding AI that supports their systems to adding systems that support their AI. That means cleaning data, connecting sources, and investing in solutions AI needs to do useful work. AI and Model Context Protocol (MCP) connections will help bridge some systems, but they won’t replace missing data or capabilities. Expect manufacturers to invest in system of record solutions, such as product lifecycle management (PLM) and application lifecycle management (ALM), that give AI access to bills of materials, connect quality records to product changes, or link service history to engineering data. Investment will focus on giving AI reliable context, not simply adding another tool.
AI Moves From Boardroom Sizzle to Everyday Results
AI priorities will shift from high-visibility demonstrations to practical applications that improve daily work. Manufacturers will focus less on occasional, headline-grabbing challenges and more on repetitive, cross-system tasks that consume time and slow operations. The next round of agents will automate routine engineering handoffs, verification tasks, and delivery workflows, with success measured by shorter cycle times, less rework, smoother delivery, and lower cost per change. Executive teams will judge AI by its impact on throughput, quality, risk, and margin, not the attention a pilot attracts.
To arrange an interview with Ross Meyercord to discuss any of these trends further, please contact laurap@chapmancommunicationsgroup.com.
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