For decades, enterprise software has focused on supporting humans. However, the growth of AI means a shift from a user-centered design philosophy to a worker- and process-centered design philosophy. In 2026, enterprise applications will move beyond their traditional role of using digital tools to enable employees to respond to a digital workforce of AI agents. Technology leaders will need to decide how far to digitize business processes and orchestrate workflows independently of human workers.
For technology leaders, this means modernizing their technology stacks, breaking free from rigid legacy systems, and building unified, AI-powered workflows. We need to level up workforce planning to treat technology as part of the workforce and drive significant increases in productivity, innovation, and competitiveness.
With all this in mind, here are our predictions for 2026:
- The top five HCM platforms offer digital workforce management capabilities. HR technology plays a key role in integrating digital employees into the workforce. Digital employees or workers independently perform complex tasks and end-to-end processes and act as virtual members of teams to automate skills and improve performance. In 2024, we have overcome the backlash against this concept and the market is now adapting to task-based AI. The next big leap forward will be “role-based” AI agents that coordinate and complete tasks across multiple systems. This shift presents a huge opportunity for HR technology to become a sophisticated employee record system that tracks and optimizes a hybrid workforce. Technology leaders offering labor-intensive services can benefit from improved workforce planning and analytics for hybrid human-digital labor models and should consider the role of human capital management (HCM) now. Large enterprises are currently driving demand, but midsize companies facing immediate pressure to optimize productivity and resources may benefit from this technology sooner.
- 30% of enterprise app vendors plan to launch their own MCP servers. This Model Context Protocol (MCP) server approach enables collaboration between external AI agents and vendor-proprietary enterprise app platforms. Vendors that adopt this open source standard for AI agent collaboration are more likely to quickly adopt cross-platform agent workflows across the enterprise. This creates an open ecosystem where companies are not locked into a single AI provider and can leverage the best agents for specific tasks. The vendor’s MCP server acts as a central hub that allows AI agents to securely connect and correlate data across these disparate systems, enabling new cross-functional intelligence. Because the MCP server works with the platform’s API, AI agents can only access and interact with authorized data, just like human users. Technology leaders should ask business app vendors about their approach to MCP as they begin to address some of the key governance challenges for agentic AI adoption.
- Half of enterprise ERP vendors plan to launch autonomous governance modules. These modules combine explainable AI, automated audit trails, and real-time compliance monitoring. The convergence of autonomous business processes processing mission-critical transactions, high-profile AI disruptions in financial services, and increasing AI regulation create pressures for vendors that cannot be ignored. SAP, Microsoft, and Oracle have already made significant investments in governance infrastructure. Incorporating governance into existing AI-integrated systems while maintaining performance and user experience creates significant development costs and schedule pressures for vendors. First movers will gain a competitive advantage through compliant platforms, while laggards will face customer churn. Technology leaders should immediately evaluate vendors’ governance roadmaps and prioritize those with autonomous compliance modules in development over traditional functional capabilities. Be aware of the governance module’s licensing costs, integration complexity, and staff training requirements.
It’s important to distinguish between genuine highlights and hurdles that the industry has overcome in the past. Although these trends are changing rapidly, we are still years away from systems that can independently manage entire business units without human intervention or adaptability. At the same time, it’s important to actively track how the market is responding to challenges. While computational power, storage costs, and legacy integration barriers are rapidly disappearing, business process standardization and data fragmentation remain major hurdles. Here’s the real job. We advise technology leaders to avoid resistance and continue building governance and operating models for this future.
Forrester clients can read the complete Predictions 2026: Enterprise Software report to learn more about each of these predictions, plus two bonus predictions. Set up a Forrester guidance session to discuss these predictions and plan your path to innovation with enterprise software.
If you’re not already a client, download our free Predictions guide and access additional free resources, including webinars, on the Predictions 2026 hub.
