Enterprise AI & Agentic Systems
Investigating how enterprise security professionals build trust, delegate decisions, and collaborate with increasingly autonomous AI systems during complex firewall management.
Task Comfort × Amount of Pain
An anonymized representation of how enterprise security professionals calibrated willingness to delegate work to AI across representative workflow categories.
Why this research mattered
Enterprise AI is evolving from answering questions to taking actions. As autonomous systems become capable of reasoning, planning, and executing workflows, organizations face a fundamental challenge: determining which decisions professionals are willing to delegate, where human oversight remains essential, and how trust should be established in high-risk environments.
"How do security professionals decide what to delegate to increasingly autonomous AI?"
Rather than treating trust as a single metric, this research program investigated it from multiple perspectives—including mental models, workflow analysis, design validation, and adoption behavior—to build a comprehensive understanding of human–AI collaboration in high-risk enterprise environments.
Mental Models
How experts reason about trust, risk, and delegation.
Workflow Analysis
Understanding where automation creates value—or introduces risk.
Design Framework
Evaluating whether a unified agentic design framework supports real-world needs.
Adoption
Understanding how design influences willingness to collaborate with AI.
Research Program
Connected studies conducted progressively answered different aspects of the central research question.
Identifying Agentic Use Cases
"Where across firewall management do professionals actually want AI?"
Prioritized agentic opportunities across seven workflow stages.
Validating the Agentic Design Framework
"How should AI interactions be designed to align with user expectations?"
Validated framework, identified coverage gaps, refined design principles.
Insights from the first study directly informed the hypotheses and validation strategy of the second study, allowing the program to evolve from identifying opportunities to validating design guidance.
Validating the Unified Agentic Design Framework
Background
Several product teams building agentic workflows operated under conflicting assumptions regarding task automation comfort. The central design framework needed empirical evidence and rigorous validation to drive aligned product roadmaps.
Research Questions
- How do enterprise professionals interpret different touchpoints within agentic workflows?
- Which principles of the unified design framework align—or conflict—with user expectations?
- Does exposure to well-designed agentic workflows increase willingness to adopt AI assistance?
Research Approach
Key Findings
Due to NDA and intellectual property considerations, specific qualitative findings and metrics are generalized or omitted.
This case study generated empirical evidence that strengthened the unified enterprise agentic design framework, identified previously unaddressed interaction patterns, and informed future product direction across multiple enterprise AI initiatives.
Research Artifacts
Empirical assets and frameworks generated to guide future enterprise-wide design and engineering direction.
Journey Maps
A comprehensive step by step flow for each of the seven stages of firewall management
Agentic Principles Framework
List of gaps and improvements for each of the touchpoints in the framework
Trust Calibration Matrix
Empirical thresholds plotting amount of pain against security professional's delegation comfort.
Touchpoints vs Agentic Principles
A matrix aligning agentic principles and agentic touchpoints
Interview Framework
Semi-structured protocol used to query expert mental models of automation.
Survey Instrument
Attitude scaling questionnaire deployed to validate quantitative comfort shifts.
Additional Studies in this Research Program
This representative deep dive is one part of a much larger program of research.
Firewall Agentic Use Cases
Research Impact
The structural, organizational, and methodological contributions generated by this program.
Product Contributions
- Validated unified agentic framework
- Prioritized enterprise roadmap
- Identified high-value automation opportunities
Organizational Alignment
- Shared across multiple product teams
- Created common vocabulary
- Aligned design decisions
Methodological Value
- Established reusable evaluation methodology
- Created trust metrics
- Provided reusable research framework