PhD Researcher & AI Strategist

Augmenting Strategy with Collaborative AI

Bridging human cognitive strengths with Generative AI capabilities to navigate complex decision environments. Developer of the AI-Augmented Strategic Reasoning Framework (AI-SRF).

Academic Biography

Pioneering frameworks for socio-technical decision systems and human-machine strategic coordination.

Bright Sikazwe

I am a PhD Candidate at the University of Johannesburg, affiliated with the Department of Information and Knowledge Management. My research resides at the intersection of Knowledge Governance, Decision Theory, and Human-AI collaboration.

Faced with volatile and complex operating environments, traditional static models fail. My work concentrates on how AI can serve as a collaborative thought partner, helping leaders sense, frame, deconstruct, and iterate solutions dynamically.

PhD
UJ Candidate
5-Stage
AI-SRF Pipeline

Research Pillars

Human-AI Collaboration

Designing workflows where AI is not merely an automated executor, but a dialectical partner that challenges framing assumptions and expands lateral thinking.

Cynefin Framework Applications

Operationalizing Dave Snowden's Cynefin quadrants (Obvious, Complicated, Complex, Chaotic) to dictate how AI is prompted and integrated based on system constraints.

First Principles Thinking

Deconstructing ambiguous business challenges into fundamental truths before prompt generation, preventing LLM hallucinations and alignment drift.

The AI-SRF Model

An interactive walkthrough of the five stages of the AI-Augmented Strategic Reasoning Framework.

01 Sense & Frame
02 Analyze & Understand
03 Ideate & Innovate
04 Evaluate & Decide
05 Act & Learn
STAGE 01

Sense & Frame

Determine the system characteristics. We categorize the problem statement using dave Snowden's Cynefin Framework to ensure we match our problem's nature to our solving methodology.

Theoretical Foundations

Cynefin Framework Sensemaking Socio-Technical Systems

Recommended AI Collaboration Prompt

Act as an organizational sensemaker. I am facing the following challenge: [Describe challenge]. Classify this issue into one of Dave Snowden's Cynefin domains (Obvious, Complicated, Complex, Chaotic). Provide the strategic reasoning for your classification.

AI-SRF Sandbox Simulator

Walk through a live, interactive simulation of the framework to frame and tackle your own strategic problems.

1 Sense & Frame
2 Deconstruct
3 Ideate
4 Evaluate
5 Summarize
Categorize the problem domain (Cynefin):

Obvious / Clear

Linear, highly predictable. Cause and effect are clear. Solution rules: Sense - Categorize - Respond.

Complicated

Requires expert analysis. Multiple right answers exist. Solution rules: Sense - Analyze - Respond.

Complex

Unpredictable, emergent patterns. Cause & effect only clear in retrospect. Solution rules: Probe - Sense - Respond.

Chaotic

Turbulent, immediate danger. No clear cause-and-effect relationship. Solution rules: Act - Sense - Respond.

*Unsure? If the issue is completely uncategorized, it resides in Disorder until framed.
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First Principles Breakdown

To solve complex problems without alignment drift, we deconstruct the problem into foundational, undeniable facts before prompting the AI.

Your AI First-Principles Prompt:

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Co-creating with Design Thinking

Now we leverage the AI as an ideation thought partner to brainstorm lateral options, ensuring empathy, human-centricity, and diversity of thought.

Your AI Ideation Prompt:

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Evaluate Strategic Options

Use the rubric scorecard below to rate the viability of possible response directions for your Cynefin domain.

Option Pathway Impact (1-5) Feasibility (1-5) Risk Mitigation (1-5)
Pathway A: Standard Optimization
Pathway B: AI-Augmented Restructuring

AI-SRF Executive Summary Report

Problem Statement

Reviewing problem...

Cynefin Classification

Complex

Option Scorecard Evaluation

Pathway A: Average 3.3 | Pathway B: Average 4.0

Research & Publications

Academic literature contributing to Information and Knowledge Management domains.

Featured PhD Work

The AI-Augmented Strategic Reasoning Framework (AI-SRF): A Theoretical Framework for Socio-Technical Systems

Bright Sikazwe

University of Johannesburg, Department of Information and Knowledge Management, 2025.

This research proposes the AI-SRF framework, an iterative methodology allowing humans and LLMs to interact dialectically. By framing challenges via Cynefin categorizations and resolving them via First Principles deconstruction, it addresses organizational friction points, preventing decision-making paralysis in high-velocity operating environments.

View on ResearchGate

Get in Touch

Collaborate on AI strategy, Socio-Technical systems research, or consult on operationalizing AI-SRF.

Contact Information

Feel free to reach out for academic collaborations, speaking engagements, or advisory requests.

Email

bright.sikazwe@uj.ac.za

Affiliation

University of Johannesburg, Dept of IKM, South Africa