The AI use cases that fail in UAE enterprises rarely fail on the model. They fail because the field the business case depends on is 40% null in production, because the process the agent was going to automate has four undocumented exception paths, or because nobody agreed what "resolution time" means before the KPI was promised to a board. None of this is visible in a business case. All of it is visible in two weeks of evidence work.
The instinct is to build a pilot and find out. That instinct costs six to nine months and an executive's credibility. A5 spends two to three weeks profiling the actual source systems, testing feasibility against the real process rather than the documented one, mapping regulatory exposure, and establishing a KPI baseline — then returns a verdict per use case with the evidence attached. Yes, we do recommend against use cases when the evidence supports it. We have closed engagements where all three candidate use cases came back no-go, and that was the correct outcome.
Six streams,
ending in a verdict per use case.
Discovery and use-case framing front-load week 1. Data profiling and feasibility testing run through week 2. Risk mapping, KPI baseline, and verdict issue close week 3.
Use-case framing
Each candidate written down as a testable claim — what decision changes, for whom, measured how. Ambiguous framings get resolved here or they contaminate every later stream.
Data readiness profiling
The actual source systems profiled on the specific fields the use case depends on — completeness, freshness, lineage, ownership, known defects. Queries attached, not questionnaires.
Technical feasibility testing
Feasibility tested against the real process including exception paths, not the documented happy path. Where a rules engine or a report would do the job, we say so.
Risk & regulatory mapping
PDPL, sector obligations, and internal risk appetite mapped to each candidate — data residency, personal-data exposure, model explainability, human-in-the-loop requirements.
KPI baseline
Current-state measurement of the metric the use case claims to improve. Without a baseline, the pilot cannot be judged and the business case cannot be defended.
Verdict & readout
Go, go-with-remediation, or no-go per use case — with the evidence attached and named remediation actions where relevant. Delivered in an executive readout, not a document drop.
Three weeks maximum.
Two minimum. Three phases.
Phase count is fixed. Duration flexes with use-case count, source-system access, and data-owner availability. Milestones are signed gates — not aspirations.
The assessment,
run on queries not questionnaires.
Every A5 engagement follows a fixed methodology tuned to your source systems in the first three days. Not a maturity interview; not a vendor bake-off. The sequence that produces a verdict a CFO and a regulator can both read.
From asserted feasibility
to evidenced verdict.
A typical pre-engagement state has a business case, an assumed data quality, and a feasibility claim nobody tested. The engagement produces the evidence pack under a decision the CFO, the risk committee, and the delivery team can all read.
Reference pattern. Some engagements return no-go on every candidate. That is a legitimate deliverable — the alternative is a build funded on evidence that was never gathered.
A UAE financial services firm,
three candidates tested.
Representative pattern for a UAE financial services firm of this scale — three shortlisted AI use cases, board pressure to start, no evidence base. Ranges reflect target outcomes NexITC underwrites in scope for this class of engagement. N=1 — illustrative composite, not a specific client.
Four artifacts,
each with signed acceptance.
Every deliverable has documented acceptance criteria signed at engagement kickoff. Nothing more, nothing less.
Data Readiness Profile
Field-level profiling of the actual source systems on the dependent fields — completeness, freshness, lineage, ownership, defect rates. Queries retained so the finding is reproducible.
Feasibility & Alternatives Assessment
Technical feasibility tested against the operated process including exception paths, with cheaper non-AI alternatives assessed alongside rather than ignored.
Risk & Regulatory Map
PDPL, sector obligations, and internal risk appetite mapped per candidate — residency, personal-data exposure, explainability, human-in-the-loop and audit-logging requirements.
Go/No-Go Verdict Pack
A verdict per use case — go, go-with-remediation, or no-go — with the evidence attached, remediation actions named and sized, and a signed KPI baseline for every candidate that proceeds. The pack your investment committee accepts without asking for supplementary analysis, and the one your delivery team can scope against without rediscovering the same facts at kickoff.
Six outcome metrics,
measured pre and post.
Success is not "the assessment happened." It is measured against six specific outcomes captured at engagement start and re-measured at handover and the 30-day check-in.
Honest scoping.
A5 is a fit when specific conditions are met. It is not a fit when other conditions are — and "you have already decided to build regardless of the evidence" is a legitimate not-a-fit answer we surface before scoping, not after.
Above three, evidence depth per candidate drops below decision grade. Where the list is longer, [[A1|A1 Boardroom-to-Backlog™]] produces the shortlist first.
Profiling runs against production or a faithful copy. Interview-only access produces an opinion, not evidence — and we will say so rather than deliver one.
The person accountable for the metric must sign the baseline. Without that signature, the verdict cannot be held to at build.
Exception paths live with operators, not in documentation. Two to three hours per candidate with the operating team is the minimum.
If the build is already funded and committed regardless of findings, the assessment produces friction rather than value.
That's A1 Boardroom-to-Backlog™ — portfolio scoring across the full initiative inventory with signed charters.
That's A9 AI Safety & Red-Teaming Sprint™ — adversarial testing by hand against your actual system.
That's B4 Data Platform Foundation Sprint™ — A5 names and sizes the remediation; B4 executes it.
Hard scope conversation. A5 exists to change a decision when evidence warrants. If it cannot, scope the build engagement directly.
Fixed fee.
Milestone-based. No surprises.
Every A-tier engagement is scoped and priced upfront against defined deliverables. Milestones tied to signed gates. Change orders negotiated through the Practice Lead, not surfaced as invoice surprises.
Five, most asked.
Q_01Do you ever recommend against a use case?
Yes, we do recommend against use cases when the evidence supports it. We have closed engagements where all three candidate use cases came back no-go — data not fit for the claimed purpose in two, and the third solvable with a rules engine at a fraction of the cost.
A no-go is a legitimate deliverable. It is cheaper to learn it in week three than in month nine of a build.
Q_02How deep does the data readiness profiling go?
Q_03Can you assess use cases we have already started building?
Q_04How does this differ from A1?
Q_05What happens on a go verdict?
One name.
Six accountabilities.
Specialist consulting means the person who scopes the work is the person who delivers it — with escalation to CEO on any material issue within 24 hours.
Practice Lead — AI
Present at every phase gate, every scope decision, every difficult conversation. Available for 30/60/90-day post-handover check-ins as part of the engagement.
Including scope amendments.
Signs off all 4 deliverables.
With executive sponsor.
Authorised to negotiate.
CEO within 24 hours.
30/60/90-day check-ins.
Prior. Peer. Next.
Boardroom-to-Backlog™
Portfolio-level engagement that produces the ranked shortlist and signed charters. Frequently precedes A5, which then pressure-tests the top-priority candidate before build commitment.
AI Safety & Red-Teaming Sprint™
Peer assessment for systems already built or in pilot — adversarial testing by hand against the actual system. A5 tests whether to build; A9 tests what was built.
Pilot Factory™
The natural build engagement on a go verdict. Data remediation actions, KPI baseline, and acceptance criteria from A5 carry over directly as scope input.
30 minutes.
One use case.
Bring the use case you are closest to funding. The clinic establishes whether the evidence you already hold is decision-grade, what the profiling would need to touch, and whether A5 is the right shape at all. If the answer is that you should just build it, we will say that too.
- —Candidate count and framing check
- —Source-system access feasibility
- —Regulatory scope check
- —Fit assessment against alternatives