Research intelligence for enterprise AI transformation.
Organizational science, management research, AI capability, enterprise adoption, Human–AI work, agents, operating models and implementation evidence — organized around the problems enterprises must actually solve.
How DENFORTH moves from operational evidence to implementation architecture.
A practical path from observed operating friction to decision architecture, Human–AI allocation, bounded implementation, measured operation and justified scale.
Read the implementation note →Four connected bodies of work.
How work, decisions and enterprise systems evolved
Scientific management, bounded rationality, sociotechnical systems, reengineering, ERP, automation and the transition from foundation models to enterprise agents.
Explore foundations →CURRENT ENTERPRISE EVIDENCEWhat enterprises are testing, scaling and learning now
Current evidence on AI and agent adoption, productivity, operating-model change, value realization and the recurring gap between pilots and scaled capability.
Explore current evidence →TRANSFORMATION / IMPLEMENTATIONHow evidence becomes an operating intervention
Decision-first transformation, Human–AI work design, implementation architecture and the organizational conditions required to turn capability into performance.
Explore implementation →EVIDENCE / CASESEvidence and implementation surfaces
Designed cases, technical demonstrations, benchmark evidence and field evidence connected to practical transformation decisions.
Explore Insights →Read by problem, not by publication date.
The corpus is organized by the kind of question each piece helps answer. Historical foundations establish the lineage; current evidence tracks what is changing; transformation notes turn evidence into operating choices.
From Scientific Management to Human–AI Work Systems
A century-long genealogy of work design, management systems and the changing boundary between human and machine contribution.
1911–2026 · Timeline Field →Bounded Rationality to AI Decision Support
What AI changes in organizational choice—and which limits of attention, authority, uncertainty and judgement remain.
1947–2026 · Architecture Field →Where enterprise AI value is emerging—and why scaling still stalls
Evidence on the transition from local task gains to workflow redesign, operating change and enterprise-level value.
2026 · Evidence + Matrix Field →What enterprises are actually testing with AI and agents now
A field view of where experimentation is concentrating and what separates trials from operational capability.
2026 · Evidence Field →Decision-first Enterprise AI Transformation
A practical architecture for selecting consequential decisions, bounding interventions and connecting AI to accountable operating change.
2026 · Architecture Field →From operational evidence to implementation architecture
How observed friction becomes a bounded Human–AI intervention, operating test and evidence-backed scale decision.
2026 · Intervention Path →From organizational foundations to operating AI systems.
The research program connects historical management and organization science with current AI capability and enterprise evidence. The through-line is practical: how work is structured, how decisions are made, how technology changes the feasible design space, and how interventions become measurable operating capability.
Historical notes carry the period analysed and actual publication date. Current evidence notes are refreshed through new releases and enterprise signals.
Start with the question you are trying to answer.
- How did work design arrive at Human–AI systems?1911–2026 · historical research
- What changed when decision support became generative and agentic?1947–2026 · decision science
- What are enterprises actually testing with AI and agents?Current enterprise evidence
- Where is value emerging — and why does scaling still stall?Current enterprise evidence
- How should an enterprise choose and bound an AI intervention?Transformation architecture
- How should work be divided between people and AI?Human–AI work design