LANITUM INTELLIGENCE — INSIGHTS
Thinking on AI, identity, and what comes next.
Perspectives on the intersection of artificial intelligence, organisational identity, and the future of enterprise. Written for leaders who are serious about the decisions ahead.
LATEST
Recent perspectives.
STRATEGY — JANUARY 2026
Why Identity Comes First
Every organisation that has attempted to adopt AI at scale has encountered the same obstacle — not technical, but cultural. The systems that last are those designed to fit the organisation that actually exists.
READ MORE →STRATEGY — JANUARY 2026
The Alignment Problem Is Not Technical
When organisations talk about AI alignment, they almost always mean the technical kind. But there is a prior alignment problem that goes unaddressed — and it is the reason so many AI initiatives stall.
READ MORE →OPERATIONS — FEBRUARY 2026
What Change Management Gets Wrong About AI
The standard playbook for change management was designed for a world where change had a beginning, a middle, and an end. AI does not work that way.
READ MORE →OPERATIONS — MARCH 2026
The Hidden Cost of Generic AI
What off-the-shelf AI tools rarely disclose about the organisational friction they introduce — and why the full cost only becomes visible after deployment.
READ MORE →OPERATIONS — MARCH 2026
When Data Quality Is a Culture Problem
Every data quality initiative eventually arrives at the same conclusion: the data is only as good as the behaviour that produces it. And behaviour is a culture question.
READ MORE →STRATEGY — APRIL 2026
The Question Before the Use Case
Most AI initiatives begin with a use case. But the use case is never actually the starting point. There is always a question behind it — and whether it has been honestly asked determines everything.
READ MORE →MEASUREMENT — APRIL 2026
Measuring AI Impact That Actually Matters
Defining success in terms of operational outcomes — before a single line of code is written. The metrics that matter are rarely the ones that are easiest to track.
READ MORE →OPERATIONS — APRIL 2026
Why AI Pilots Fail to Scale
The gap between pilot success and operational scale is where most enterprise AI investment disappears. A pilot succeeds because it is an exception. Scale requires the opposite.
READ MORE →LEADERSHIP — MAY 2026
The Governance Gap in Enterprise AI
Most organisations that have deployed AI have not yet answered a basic governance question: who is accountable when the system is wrong? The absence of an answer compounds over time.
READ MORE →LEADERSHIP — MAY 2026
Building AI Literacy That Lasts
AI literacy programmes are proliferating. Most of them will have a limited effect — not because the content is wrong, but because they treat a capability problem as a training problem.
READ MORE →More perspectives
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