Propel Software has outlined five business and technology trends for 2027, according to CEO Ross Meyercord. The predictions examine how AI could reshape relationships between software providers, change how companies oversee automated decisions, influence the shift toward home-based healthcare, drive changes in manufacturers’ technology systems and sharpen the focus on applying AI to routine operational tasks and measuring its business impact.
AI trends: SaaS moves from threat to strategic partner
AI and SaaS are expected to grow stronger together rather than compete. Propel forecasts that AI companies will find more value partnering with established SaaS providers, while SaaS vendors will use AI to deliver more valuable customer experiences. The gap will widen between platforms with deep, connected capabilities and those offering cursory bolt-on features. SaaS providers that quickly connect their data, workflows and AI strategy will be positioned for sustained growth; those with disconnected data and processes risk losing out on the next round of AI-driven growth.
Human in the audit trail replaces human in the loop
As experienced subject matter experts train AI on proven processes, that expertise will become embedded in day-to-day systems. For established, repeatable work, organizations will increasingly trust AI to make decisions and complete tasks faster without constant human review. These AI-generated tasks will be flagged and recorded with detailed audit logs to allow periodic human review and compliance checks. Human expertise will remain essential for designing new processes, handling exceptions and setting the standards AI follows.
Care continues its shift from facilities to the home
Propel expects healthcare delivery to keep moving beyond hospitals and ambulatory surgery centers into patients’ homes. An aging population and advances in wearables, remote monitoring, connected implants and home diagnostics will make home-based care more practical, necessary and cost effective. MedTech companies will need to design products and experiences for continuous use outside clinical settings, backed by reliable product data, connected teams and a clear view of every change across the product lifecycle. AI-assisted monitoring of incoming data is considered essential as the volume of inbound data will overwhelm human teams.
Manufacturers rebuild tech stacks to optimize AI
Manufacturers are predicted to shift from adding AI on top of existing systems to building systems that support AI. That shift requires cleaning data, connecting sources and investing in the solutions AI needs to do useful work. Propel notes that AI and Model Context Protocol (MCP) connections can bridge some systems, but they will not replace missing data or capabilities. Investments are expected to focus on system-of-record solutions such as product lifecycle management (PLM) and application lifecycle management (ALM) so AI has reliable access to bills of materials, quality records, service history and engineering context.
AI moves from boardroom sizzle to everyday results
AI priorities will move away from high-visibility demonstrations toward practical applications that improve daily work. Manufacturers will concentrate less on headline-grabbing challenges and more on repetitive, cross-system tasks that consume time and slow operations. Propel predicts 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 rather than by the attention a pilot attracts.
