ABCI analytical perspective. Milestones and structural directions below are research propositions, not official forecasts or commitments.
Why It Matters
Connectivity is an enabling condition, not the final outcome of digital transformation. Economic value comes from reliable services, interoperable data, more productive firms and responsible use of automation and artificial intelligence.
Where Iraq Stands
The 2022 ICT survey reported internet use by 79% of people aged five and above and internet access in 87% of households. Government platform figures describe services, accounts and data entries; they do not measure completed transactions, user satisfaction or economic productivity.
The Structural Gap
Access, adoption and economic impact must be measured separately. Approved national baselines for the digital economy’s contribution to GDP and enterprise AI adoption are still needed; account counts should not be used as substitutes.
What Needs to Change
Evaluate service completion, data quality, interoperability, cybersecurity, accessibility and workforce skills. AI use cases should have a defined purpose, accountable oversight and evidence of benefit before being scaled.
2030 Milestone
By 2030, test whether priority services are usable end to end and whether businesses can demonstrate time savings or productivity gains. Establish transparent measures of active use and service outcomes.
Proposed measurement protocol
- Measure and definition
- Completed digital transactions, completion rate and processing time; AI adoption and productivity change for a defined business sample.
- Collection and comparison
- Distinguish listed from active services and unique users from accounts. For AI, define the use case, baseline workflow and sample before repeat measurements.
- Current limits
- Current service counts are retained reference figures with unresolved timing. The edition has no representative AI sample or causal productivity estimate.
2035 Direction
The direction is an integrated digital economy in which data and responsible AI improve institutional and business performance. Numeric adoption targets remain outside the framework until measurement is sufficiently reliable.