I work with a small number of organisations
navigating AI deployment, typically where the challenge is
structural rather than technical. Engagements are focused,
scoped, and built around a specific decision or problem.
🗺️
AI Strategy Development
From use-case prioritisation
to governance architecture. Built around your
organisation's actual risk tier, decision rights,
and deployment baseline, not a generic framework
applied wholesale.
⚖️
Governance Design
Risk-tiered governance
calibrated to blast radius. Parallel assurance
architecture with veto authority. Mapped to
regulatory context (EU AI Act, sector-specific
frameworks) where relevant.
🚀
Deployment Acceleration
Structural diagnosis of
stalled AI initiatives. Decision rights redesign.
Incentive realignment. Executive alignment
facilitation. The work that unblocks what technical
investment cannot.
🏛️
Board AI Readiness
Leading indicator reporting
design. Board-level AI literacy briefings.
Governance gap analysis against the five
blast-radius dimensions. Built for boards that need
to ask better questions, not just receive better
answers.
Talks built for executive, practitioner, and
mixed audiences. Grounded in research, illustrated with case
evidence, designed to shift the conversation from AI capability
to AI deployment reality.
01
The Deployment Paradox: Why
AI Initiatives Stall, and the Structural Fix
The Organisational Friction
Principle in full. Why the binding constraint on AI
is almost never the model, and what boards, CTOs,
and governance teams can actually do about it.
02
Responsible Speed: Governing
AI Without Sacrificing Velocity
The structural integration of
responsible AI practice into the deployment cycle.
Why sequential compliance gates create delay without
improving safety, and what proportional governance
looks like in practice.
03
Agentic AI in Production:
What a Decade of Research Tells Us
Drawing on research published
over a decade before agentic AI entered mainstream
practice, the coordination problems we described
then are the ones organisations are hitting now.
What the research predicts, and what production is
confirming.
04
Will the Next Generation of
LLMs All Look the Same?
As foundation models converge
on capability benchmarks, competitive advantage
shifts from model performance to deployment
architecture and organisational integration. What
the post-model-wars era requires from leaders.
05
The Problem-First Paradigm:
Why AI Is a Tool, Not the Goal
Why organisations that lead
with AI technology rather than business problems
consistently underdeliver, and the scoping
discipline that separates high-ROI deployments from
the 95% that never reach production at scale.
Corporate AI education and team capability
programmes, drawing on research depth, multi-year university and
professional teaching experience, and direct deployment
observation. Built for organisations investing in AI capability,
not just AI tools.
📐
AI Strategy for Leadership
Teams
Half-day or full-day workshop.
Frameworks for use-case prioritisation, governance
calibration, and deployment readiness assessment.
Built for C-suite and senior leadership audiences
(no technical background assumed).
🔧
AI Deployment Practitioner
Programme
For product, engineering, and
data teams. The Fast AI Deployment Framework applied
to live initiatives. Decision-rights design,
risk-tier classification, and parallel assurance in
practice.
🏛️
AI Governance for Boards
& Risk Functions
Board-level AI literacy.
Leading indicator reporting design. Regulatory
mapping: EU AI Act, sector-specific frameworks.
Built for governance professionals who need rigour,
not simplification.
🧪
Bespoke Programme Design
Custom capability programmes
designed around your organisation's AI maturity,
sector context, and specific deployment challenges.
Draws on 16 years of research, consultancy, and
teaching across academic and professional settings.
Current Affiliation · Active
Research Affiliate: University
of Science and Technology MB - Oran, Algeria
Current research focus: "AI
Powered Data Analytics through Collaborative Decision
Making
using LLM Agents". Affiliated 2010-2015, 2025-Present.
Peer-Reviewed Publications
IJCSI
The Integration Of User
Knowledge To Learn A Specialized
Decision Tree From A Real-Life Data: An Empirical
And Computational Study
R. Semghouni, S. A. Rahal And
O. Benyoucef · International Journal Of
Computer Science Issues, Vol. 9(5): 310-317 ·
September 2012
View paper:
[https://ijcsi.org/papers/IJCSI-9-5-1-310-317.pdf]
Presentations & Invited Talks
Talk
Semantic Clustering for Robust
Predictive Models
University Of Louisville, IEEE
Computer Society - Louisville Chapter · April 3rd
2015 · Louisville, Kentucky
Talk
Efficient Representative
Subsets in Quasi‑Order Spaces
School Of Education, Technische
Üniversität
München · November 5th 2013 · Munich – Germany
Poster
Using Conceptual Clustering To
Improve The Accuracy Of Classification
IEEE International Conference
On Data Mining · December 10-13th 2012 · Brussels –
Belgium
