Insights
Reports, whitepapers, and field notes from across our practice areas.
Coderex Launches Africa AI Advisory Practice
Coderex Consulting International is formalising an Africa AI Advisory practice, led from Lagos and supported by the firm's Abuja office and international remote advisory network.
Current State of African AI Investment: Where We Are
A draft cut for the first quarter of 2026, built from verified 2024 full-year totals, the partial 2025 picture, and the five national AI strategies that came online in twelve months. Quarterly totals from the trackers will land in May or June; this is the version we can verify in the meantime.
Six patterns from CEO conversations about AI
Six patterns I keep hearing in CEO conversations about AI. The vignettes are illustrative composites drawn from across multiple discussions, not transcripts. The published evidence is what holds the patterns up.
The AI mass layoff story does not survive a spreadsheet
Headlines say AI is replacing a third of corporate work. The trackers and the BLS data say something more specific. The real pressure is concentrated, and the slow-burn risk is in entry-level pipelines.
Africa's AI Adoption Map: What the Public Indices Actually Say About 14 Markets
We pulled the major public indices that already score African AI readiness, lined them up across 14 markets, and looked at where they agree, where they disagree, and what they all leave out.
Why Africa is the next AI investment frontier (and why the case is narrower than the headlines)
London and New York clients keep asking whether the African AI thesis is real or whether it is the next frontier-market story that fizzles. The honest answer sits between the two.
The boring AI revolution happening in back offices
The AI demos that get the most press are rarely the deployments that pay back. The unglamorous wins are in accounts payable, contract review, and internal knowledge search. The published evidence agrees, even if the keynote stages do not.
Patient Data Consent Is Broken. AI Is About to Make It Worse
Healthcare consent forms were drafted for a world of named clinicians, named studies, and named purposes. AI training does not fit any of those categories cleanly. We propose a layered fix.
AI in African healthcare: what 18 months of published deployments actually show
Eighteen months of published African healthcare AI work, read alongside our practitioner experience, points to five durable lessons. None of them are about model architecture. Most of them are about data, trust, and the buildings the systems run inside.
What CEOs Keep Asking Me About AI (And What I Actually Tell Them)
Six questions come up in almost every senior leadership conversation about AI. Here are the ones I hear most often, and the answers I give when the slide deck is closed.
Why programme governance fails at scale, and how to fix it
Most governance frameworks were designed for single projects, not portfolios. The structural patterns that let governance scale are well documented in the public record. The problem is that they are rarely all in place at once.
Data governance in healthcare: beyond compliance to capability
Healthcare data governance often stops at the regulatory floor. The harder work, and the work that returns clinical value, is building the data capability underneath the compliance paperwork.
From Waterfall to Agile: A Practitioner's Guide for Regulated Industries
Sprint training and a Jira board do not move a regulated business off waterfall. Funding, governance, procurement and capability all have to move at the same time. Here is what we see actually working.
Technology Readiness Levels for Distributed Energy: A Practitioner's Framework
Standard TRL was built for one-off aerospace systems, not for distributed solar, biogas, and storage operating across patchy grids and uneven regulation. This whitepaper sets out a practical extension.