AI Demands Government Redesign, Not Just Adoption
Artificial intelligence is no longer a distant promise or a technical upgrade. It's becoming the defining force behind how economies grow, how services are delivered and how institutions operate. For governments, this moment calls for more than pilots or platforms. It calls for redesign.
This is the core message of the 2025-2026 Arab Public Management Report, developed with the Arab Administrative Development Organisation and set to be launched at the World Government Summit. The key question isn't whether AI will change public administration. It's whether governments are ready to change themselves.
From "Using AI" To "Designed for AI"
Layering advanced tools on top of 20th-century bureaucracies delivers marginal gains. In some cases, it adds new complexity and delays. True impact appears when we rethink how decisions are made, how services are built and how institutions are structured.
- Reactive to anticipatory: solve issues before they surface.
- Standardised to personalised: meet people where they are, not where forms expect them to be.
- Siloed to integrated: design around life events, not agency boundaries.
- Processing to prevention: shift from requests to outcomes.
What This Looks Like in Practice
Abu Dhabi's Tamm shows the direction. It moved beyond a portal into a self-operating model: AI at the core, services delivered automatically, fewer applications, no document hunting, and less time lost going through multiple agencies. That's a new relationship between the state and the public.
Legislation is evolving too. A dedicated Office of Regulatory Intelligence now uses AI to support drafting and review. The intent isn't to replace judgment. It's to shorten cycles, raise quality and simulate impact before laws go live.
People Are the Multiplier
The myth says AI replaces people. In government, the opposite is true. As systems get smarter, human judgment, ethics and accountability matter more. Public administration runs on trust; if transparency, fairness or responsibility slip, the tech won't matter.
That's why skills sit at the center: national AI upskilling, "chief AI officers" inside ministries and platforms like Jahiz to prepare teams for future roles. Technology amplifies capability only when institutions invest in learning, leadership and culture.
Governance First, Then Scale
Governments need clear guardrails: explainable models, clear lines of responsibility and disclosure when AI is in use. Certification and sector guidelines build confidence, not after the fact, but upfront. Trust is the prerequisite for transformation.
For reference frameworks that many administrations use, see the OECD AI Principles.
What the Regional Evidence Shows
The Arab Public Management Report finds that fast movers weren't the ones with the most pilots. They were the ones that invested early in data governance, interoperability, cybersecurity and institutional readiness. Young populations and ambitious agendas create a rare chance to leap ahead-but only if AI is treated as a policy choice, not a tech project.
A 12-Month Playbook for Government Teams
- Set a clear AI purpose: pick 3-5 outcome metrics that matter (e.g., processing time, citizen effort, preventive impact).
- Redesign one end-to-end life event (birth, job change, new business, retirement) across agencies with shared data and policies.
- Stand up an AI governance board with legal, ethics, delivery, security and civil service representation.
- Adopt human-in-the-loop by default for decisions with material impact; document who is accountable for outcomes.
- Publish an AI use registry so citizens know where and how AI is applied.
- Invest in data quality and interoperability; agree common data models and identifiers across agencies.
- Pilot anticipatory services using risk and event signals to trigger benefits or interventions automatically.
- Appoint or upskill "chief AI officers" in major entities; give them delivery authority, not just advisory roles.
- Update procurement to evaluate explainability, model monitoring, security and exit strategies-not just accuracy.
- Measure and report quarterly: service completion time, citizen steps removed, prevented cases, equity and error rates.
Your First 90 Days
- Pick one high-volume service and map the current journey step-by-step; remove 30-50% of steps through policy and data fixes before adding AI.
- Launch a small model-in-the-loop pilot with clear human oversight and a published risk register.
- Train a cross-functional squad (policy, service, data, legal, security). Give them a weekly cadence and executive air cover.
- Set up monitoring: drift, bias, appeal pathways and redress timelines.
The Principle That Decides Who Wins
The governments that come out ahead won't be the ones with the flashiest algorithms. They'll be the ones willing to redesign how they work-service by service, statute by statute, system by system. Adoption is easy. Redesign is the work.
Upskilling Your Team
If you're planning capability-building for specific roles, explore practical options by function here: AI courses by job. Keep the training close to live projects so learning turns into delivery, fast.
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