These overlap. Never add them up. One hour of work can draw on two or three skills at once.
The future of work deserves its own champions.
Show us what you've changed. We'll show the world.
Recognising organisations making work better with AI. Every month. Across three regions. With evidence, not hype.
Submit your AI success storyNo entry fee · Evidence required · Independent jury · Monthly deadline: the 20th
Know a team changing the way work gets done? Put them on the map.
- 01Work ReimaginedMaking work smarter and more meaningful, by handing the drudgery to AI.
- 02Human PotentialTurning technological change into human opportunity: reskilled, redeployed, elevated.
- 03Inclusive FutureOpening the future of work to more people, including women and people with disabilities.
- 04AI ChallengerSmall organisations. Extraordinary impact.
- 05AI for GoodUsing AI to make a difference beyond business.
The Board of the Future Award
Recognising the boards leading enterprise transformation in the AI age.
- OversightHow the board governs AI across the whole enterprise
- LeadershipThe strategic choices it made, and the people it brought with it
- OutcomesMeasurable results for performance, work and people
Every month an independent regional jury selects outstanding practices from India, the GCC and Africa. Winners are announced in the monthly heat-map issue, starting in November.
A feature in the issue and the video episode, the winner's emblem for your website, reports and hiring, a place in the AIWoW register, and a place on the shortlist for the annual awards.
One AIWoW juror each from India, the GCC and Africa, with judges from global business and consulting. Jurors step out of any decision involving their own organisation or clients.
What government could do to unlock the prize in the GCC
US$2.5 billion a year on offer, 12% picked up. Tellers, contact centres and back offices, where many nationals work, hold 24% of it. Much of what holds it back is cost, skills, data and trust, and governments can move all four. Two options, each drawn from something another country has already done.
A shared platform for banks to flag financial crime
Each bank sees only its own slice of fraud and laundering. In Saudi Arabia 53% of fraud teams still investigate by hand, and half of banks lose more than US$10 million a year to fraud.
A regulator-run platform where banks share red flags on customers, with AI analysis on top and clear legal safeguards.
The UAE central bank and the Saudi Central Bank, with their financial intelligence units.
Singapore's MAS launched COSMIC in April 2024 with six major banks sharing information on customers showing several red flags. MAS BioCatch, 2026
KYC, fraud and compliance work: about US$258 million a year (10% of US$2.5 billion).
A supervised generative AI sandbox for banks and insurers
Firms are stuck before scale: only 9% of Gulf finance functions are scaling generative AI, and 1% of organisations say they are fully ready.
A sandbox where banks and insurers test generative AI with supervisors watching, on computing hosted in the country.
The UAE central bank, the Saudi Central Bank and the Insurance Authority, with national AI bodies.
Hong Kong's monetary authority and Cyberport ran a generative AI sandbox for banks from January 2025 and widened it across financial services in March 2026. Hong Kong Government, 2025 Crowdfund Insider, 2026
Credit, claims and compliance work: about US$516 million a year (21% of US$2.5 billion).
| ID | Option | Where | Opened | Status |
|---|---|---|---|---|
| P-030-01 | Kiranas Go Digital drive | India | Issue 030 | Proposed |
| P-030-02 | Half-price, pre-approved AI tools | India | Issue 030 | Proposed |
| P-030-03 | Job-redesign grants tied to nationalisation | UAE, Saudi Arabia | Issue 030 | Proposed |
| P-030-04 | Shared test kit for shopper-facing AI | UAE, Saudi Arabia | Issue 030 | Proposed |
| P-030-05 | Consent-based sharing of mobile money records | Kenya, Nigeria | Issue 030 | Proposed |
| P-030-06 | Open language models for traders | Kenya, Nigeria | Issue 030 | Proposed |
| P-031-01 | RBI AI sandbox for smaller lenders | India | Issue 031 | Proposed |
| P-031-02 | Legal gateway for sharing fraud signals | India | Issue 031 | Proposed |
| P-031-03 | Shared platform to flag financial crime | UAE, Saudi Arabia | Issue 031 | Proposed |
| P-031-04 | Supervised generative AI sandbox | UAE, Saudi Arabia | Issue 031 | Proposed |
| P-031-05 | AI sandboxes at central banks | Kenya, Nigeria, South Africa | Issue 031 | Proposed |
| P-031-06 | Live, consent-based open banking | Nigeria | Issue 031 | Proposed |
Options for India and Africa are in their editions. These are options for discussion, not advice to any government. Precedents are described as published by their sources; pools are our estimates from this issue's figures. No one pays to appear in this section.
Where the unclaimed prize sits, and who is funding it
Most of the prize has not been picked up, so most of the market is still unserved. Two theses for investors, the disclosed funding we found, and dated calls we will score in public.
AI decisions for credit, fraud and AML, hosted in the country
Banks and finance companies that must keep data at home and explain their decisions under the UAE's AI guidance.
Credit underwriting copilot and fraud and financial crime monitor.
Moderate to high. Banks are buying; in-country computing is arriving.
Policy options P-031-03 and P-031-04, and national AI computing such as HUMAIN's.
A large Gulf bank naming a regional vendor for credit or fraud decisions.
Training nationals to supervise and check AI
Banks and insurers with nationalisation targets: UAE financial firms hired 2,901 Emiratis in 2025 against a target of 1,816.
Supervising AI and checking its work, the new skills in this edition.
High. The money for training nationals already exists; the AI content is new.
Nationalisation targets and the central banks' training institutes.
A regulator counting AI supervision roles towards nationalisation targets.
Mal, an AI-native Islamic digital bank launching from the UAE, raised US$230m led by BlueFive Capital in January 2026 (FinTech Global). Abu Dhabi's Synapse Analytics raised a US$13m Series A led by Partech in September 2026 for AI decisions on credit, fraud and AML (Wamda). OCTA raised a US$3.5m seed led by MEVP for AI agents that do bookkeeping and reconciliation (Dealroom). One large round, then small ones: the back office is underfunded.
| ID | Call | Check by | Confidence | Status |
|---|---|---|---|---|
| I-030-01 | At least one disclosed round of US$5m or more for an AI tool built for Indian kirana stores. | 30 Jun 2027 | Moderate | Open |
| I-030-02 | At least one GCC retail software company launches an AI product sold to retailers it signed up for e-invoicing. | 31 Mar 2027 | Moderate-high | Open |
| I-030-03 | A disclosed round of US$10m or more for an African company offering AI bookkeeping or credit to informal traders. | 30 Jun 2027 | Moderate | Open |
| I-030-04 | A sovereign-linked fund outside Saudi Arabia leads a retail AI round of US$20m or more in the GCC. | 31 Dec 2027 | Low-moderate | Open |
| I-031-01 | A disclosed round of US$10m or more for an Indian company selling AI model governance or model risk tools to banks. | 30 Sep 2027 | Moderate | Open |
| I-031-02 | A Gulf central bank or financial regulator opens a supervised AI or generative AI sandbox for banks. | 30 Jun 2027 | Moderate | Open |
| I-031-03 | At least one bank in South Africa, Nigeria or Kenya announces it is licensing an outside AI credit engine. | 30 Jun 2027 | Moderate | Open |
Sector and market theses only. Nothing here rates, recommends or values any company or security, and none of it is investment advice. Companies are named only as examples of disclosed funding, from the public sources linked; some figures are not confirmed by the companies. No one pays to appear in this section, and it is separate from the AIWoW Awards jury.
Dated. Falsifiable. Scored in public.
Every forecast
Two minutes, two games: this week's AI word and AI crossword
A new word and a new crossword every Friday, Issue . Play here, then share your result without giving away the answers.
How we got these numbers
Every figure in this issue comes from public sources and our own analysis of how the work is done. Open any section to see the working.
AHow we sized the work
BThe new skills, and why banking needs more of someSupervising AI, checking its work, writing its instructions and looking after data.
CWhat we could not confirmRead this before you quote a number.
DSources
R Reported: a named report, filing or news story. A Our analysis of how the work is done. E Our estimate from the named sources.