AI Savings Calculator
Estimate potential efficiency gains from AI adoption across NZ government agencies. Adjust the adoption rate to see how savings and workforce impact change.
AI Adoption Rate
25%Adoption rate represents the percentage of addressable work where AI tools are actually deployed. At 25% adoption with 30% efficiency factor, each $100 of addressable spend yields $8 in savings.
$198M
Estimated Annual Savings
1319
FTE Capacity Freed
not job losses — redeployable capacity
0.4%
% of Total Expenses
21
Agencies Modelled
Per-Agency Savings at 25% AI Adoption
| Agency | AI Score | Addressable | Est. Savings | FTE Freed | Total Expenses | Current FTE |
|---|---|---|---|---|---|---|
| Health New Zealand — Te Whatu Ora Crown Entities | 62 | $1913M | $143M | 957 | $29024M | 82000 |
| Commissioner of Police Crown Entities | 64 | $229M | $17M | 114 | $2780M | 15733 |
| Department of Corrections Central Government | 57 | $191M | $14M | 95 | $3000M | 10976 |
| Ministry of Social Development Central Government | 62 | $100M | $8M | 50 | $1631M | 8866 |
| Inland Revenue — Te Tari Taake Crown Entities | 68 | $47M | $4M | 24 | $753M | 4380 |
| Te Tāhuhu o te Mātauranga | Ministry of Edu... Central Government | 43 | $33M | $2M | 17 | $4247M | 3835 |
| Ministry of Foreign Affairs and Trade Central Government | 59 | $29M | $2M | 15 | $542M | 1480 |
| Te Tari Taiwhenua Department of Internal Af... Central Government | 50 | $26M | $2M | 13 | $1013M | 3459 |
| Department of Conservation Te Papa Atawhai Central Government | 52 | $22M | $2M | 11 | $1126M | 2827 |
| Ministry of Business, Innovation and Employ... Central Government | 56 | $17M | $1M | 9 | $1210M | 5804 |
| Te Tai Ōhanga | The Treasury Crown Entities | 47 | $8M | $563K | 4 | $456M | 1644 |
| Oranga Tamariki—Ministry for Children Central Government | 47 | $6M | $433K | 3 | $1443M | 4586 |
| The Ministry of Transport Te Manatū Waka Central Government | 66 | $5M | $402K | 3 | $51M | 206 |
| Te Tūāpapa Kura Kāinga-Ministry of Housing ... Central Government | 62 | $4M | $330K | 2 | $65M | 320 |
| Tertiary Education Commission – Te Amorangi... Crown Entities | 57 | $4M | $323K | 2 | $74M | 299.2 |
| Ministry of Defence Manatū Kaupapa Waonga Central Government | 44 | $1M | $88K | 1 | $92M | 184 |
| Ministry for Ethnic Communities Te Tare Māt... Central Government | 47 | $69K | $5K | - | $18M | 58.7 |
| Kāinga Ora–Homes and Communities Crown Entities | 54 | - | - | - | $2175M | 2609 |
| Te Tāhū o te Ture - Ministry of Justice Central Government | 54 | - | - | - | $1363M | 3559 |
| ACC Crown Entities | 47 | - | - | - | $12M | - |
| Chief of the New Zealand Defence Force Central Government | 52 | - | - | - | - | 11683.1 |
| TOTAL (21 agencies) | - | - | $198M | 1319 | $51073M | 164,509 |
About "FTE Freed"
This is not a job loss estimate. It represents the equivalent staff capacity that could be freed from routine tasks and redirected to higher-value work: better citizen services, deeper policy analysis, proactive outreach, and innovation. International evidence suggests AI-augmented public services improve both efficiency and service quality when implemented with workforce transition support.
How This Calculator Works
This calculator estimates potential efficiency gains, not actual savings projections. It uses a simple model:
- Addressable spend = (AI score % x contractor spend) + (15% x personnel costs x AI score %). This represents the theoretical maximum spend that AI could augment.
- Savings at adoption rate X% = addressable spend x adoption rate x efficiency factor (30%). Not all addressable work will be fully automated — the 30% efficiency factor reflects partial augmentation.
- FTE equivalent = estimated savings / average cost per FTE ($150K). This represents capacity freed up for higher-value work, not necessarily job losses.
Important caveats:
- AI augments human work — it doesn't replace it 1:1. Freed capacity should be redirected to service improvement, not headcount reduction.
- Implementation costs (technology, training, change management) are NOT included. Actual ROI will be lower than gross savings shown.
- The model uses proxy metrics from annual reports. Process-level analysis would yield more accurate estimates.
- Some work cannot and should not be automated: policy judgment, democratic accountability, empathetic service delivery, complex negotiations.
Based on McKinsey (2023) "30% of work hours automatable by 2030", OECD (2024) "40-60% back-office automation potential", adjusted for NZ public sector context.
Data sourced from publicly available NZX filings and annual reports. Our datasets may not be complete. Automated analysis can produce errors. Scores are calculated using disclosed methodology and are analytical tools, not investment ratings or recommendations. If you believe any data on this page is incorrect, please contact us at hello@nzxplorer.co.nz. For informational purposes only. Not investment advice.