Subject: Information System Science
Title: Designing and Deploying Generative AI Agents for Sustainable Performance Gains in B2B Knowledge-Intensive Service Firms
Abstract:
By 2026, generative artificial intelligence has become organizational infrastructure in most large firms, yet only a small minority of organizations record net-positive outcomes from their deployments. This thesis addresses the resulting gap between robust individual-level productivity gains and weak organizational performance, asking how those individual gains can be converted into durable organizational value in B2B knowledge-intensive service firms.
The central research question asks how generative AI agents can be systematically designed and deployed to generate sustainable performance gains, and what organizational conditions determine their effectiveness. It is operationalized through three sub-questions concerning design principles, measurable outcomes, and the organizational conditions that moderate effectiveness across tasks and employee profiles.
The research follows an action research design conducted within Praxedo, a B2B SaaS firm, across three phases: a qualitative diagnostic, the design and deployment of six purpose-built AI agents, and a before-andafter quantitative evaluation drawing on historical Salesforce baselines and matched consultant samples.
The interventions produced substantial gains, including task-time reductions of roughly 53 to 72 percent, an 85 percent reduction in CR filing delay for junior consultants, a 30.6 percent reduction in time-to-value, and a 2.4-point NPS improvement. Gains were consistently larger for junior than for experienced consultants, confirming a leveling-up effect. The findings indicate that sustainable AI value depends less on the technology itself than on the surrounding governance ecosystem: task-specific design, a Generate / Verify / Refine / Validate governance cycle, progressive deployment, and deliberate investment in human capability.
Keywords: generative AI, AI agents, organizational performance, B2B SaaS, action research, AI governance, knowledge transfer, productivity, customer success, leveling-up effect