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AI Automation Index
Will AI Replace Blockchain Engineers?
Task-level automation exposure for Blockchain Engineers: 17 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
63%
weighted task index
17 of 17 tasks scored
Median Salary
$116,580 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Very High
435,370 people hold this job — size, not growth
Projected 2025–35
+5.1%
employment change
27,000 openings a year · BLS line item
Pay by state
BLS OEWS publishes 54 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$60,470 – $156,590
Highest medians
District of Columbia $156,590
Maryland $144,680
Colorado $139,580
Virginia $139,030
Delaware $137,470
Lowest medians
Puerto Rico $60,470
Tennessee $76,470
Guam $76,770
Louisiana $77,000
North Dakota $78,330
State figures come from the 15-1299 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 63%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 6%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 40%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 0%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 33/100
Moderate
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
17 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 53%
9 tasks
Medium exposure (≥ 35%) 42%
7 tasks
Low exposure (below 35%) 6%
1 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Emerging & rewritten tasks
Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.
- New 08/2026 · Occupational Expert
Develop software tools, such as application programming interfaces (APIs), to integrate applications.
Constituent Tasks
#21815 · Core · 58% automatable
Discuss and plan systems with solution architects, system engineers, or cybersecurity experts to meet customer requirements.
interpersonal — Discussing design features with staff is relational exchange
Discuss design or technical features of products or services with technical personnel.
#21819 · Core · 60% automatable
Implement catastrophic failure handlers to identify security breaches and prevent serious damage.
decision support — Security implementation needs human judgment and deployment
Implement security measures for computer or information systems.
#21821 · Core · 55% automatable
Test the security and performance of blockchain infrastructures.
data analysis — AI interprets test output; human executes tests
Test computer system operations to ensure proper functioning.
#21806 · Core · 70% automatable
Assess blockchain threats, such as untested code and unprotected keys.
data analysis — Security analysis aided; human validates findings
Analyze security of systems, network, or data.
#21808 · Core · 55% automatable
Design and deploy blockchain design patterns to make transactions secure, transparent, and immutable.
decision support — Security implementation needs human judgment and deployment
Design integrated computer systems. Implement security measures for computer or information systems.
#21812 · Core · 70% automatable
Design and verify cryptographic protocols to protect private information.
text generation — AI drafts security policies; human approves
Develop computer or information security policies or procedures.
#21817 · Core · 70% automatable
Evaluate blockchain processes or risks based on security assessments or control matrix reviews.
decision support — Software utility evaluation aided by research and testing
Evaluate utility of software or hardware technologies.
#21820 · Core · 55% automatable
Run infrastructure tests to examine the behavior of large peer-to-peer networks.
data analysis — AI interprets test output; human executes tests
Test computer system operations to ensure proper functioning.
#21816 · Core · 58% automatable
Discuss data needs with engineers, product managers, or data scientists to identify blockchain requirements.
interpersonal — Discussing design features with staff is relational exchange
Discuss design or technical features of products or services with technical personnel.
#21807 · Core · 82% automatable
Automate the deployment of software updates over geographically distributed network nodes.
text generation — Code generation strong; human reviews and integrates
Write computer programming code.
#21814 · Core · 82% automatable
Develop a maintainable code base using object-oriented design principles, practices, or patterns.
text generation — Code generation strong; human reviews and integrates
Write computer programming code.
#21822 · Core · 30% automatable
Update client and server applications responsible for integration and business logic.
physical manipulation — Software side AI-assisted; hardware maintenance is hands-on
Maintain computer equipment or software.
#21811 · Core · 75% automatable
Design and implement data repositories to integrate data.
text generation — Database creation largely automatable; human reviews
Create databases to store electronic data.
#21813 · Core · 72% automatable
Determine specifications for, or implement, logging.
text generation — AI drafts data management procedures; human approves
Develop procedures for data management.
#21818 · Core · 65% automatable
Evaluate new blockchain technologies and vendor products.
decision support — Technology evaluation aided; strategic judgment human
Evaluate new technologies or methods.
#21809 · Core · 50% automatable
Design and develop blockchain technologies for industries such as finance and music.
decision support — Integrated systems need human architecture and stakeholder judgment
Design integrated computer systems.
#21810 · Core · 59% automatable
Design and implement dashboard and data visualizations to meet customer reporting needs.
text generation — Design drafts aided; system architecture needs human judgment
Design software applications. Install computer software.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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