JobRiskAI

Opticians, Dispensing

SOC 29-2081Healthcare PractitionersData vintage 2026-07
Moderate exposure AI applicability score 0.136, higher than 46% of the 785 occupations measured · #23 most exposed of 69 in Healthcare Practitioners

AI touches this job. It does not define it.

AI meaningfully touches parts of this work, yet the majority of its activities remain outside observed AI usage. That's balanced exposure: real efficiency gains are available without wholesale overlap.

Where this occupation sits among all 785 measured. Bands are quintiles of the real distribution. Applicability measures task overlap with observed AI usage. It is not a probability of job loss.

What this job involves

Design, measure, fit, and adapt lenses and frames for client according to written optical prescription or specification. Assist client with inserting, removing, and caring for contact lenses. Assist client with selecting frames. Measure customer for size of eyeglasses and coordinate frames with facial and eye measurements and optical prescription. Prepare work order for optical laboratory containing instructions for grinding and mounting lenses in frames. Verify exactness of finished lens spectacles. Adjust frame and lens position to fit client. May shape or reshape frames. Includes contact lens opticians.

Where AI overlaps this work, activity by activity

The occupation's most important work activities (O*NET weights, normalized to this set), each with its measured AI performance across 200,000 real conversations: how often AI is used for it, how well it completes it, and how much of the activity it covers.

Work activityShare of roleAI performance
Fabricate medical devices.16.7%Not observed 0.00
Advise others on products or services.12.2%High overlap 0.79
Fit assistive devices to patients or clients.11.8%Not observed 0.00
Perform administrative or clerical activities.9.8%Moderate 0.58
Train others to use equipment or products.9.1%Not observed 0.00
Sell products or services.7.6%Not observed 0.00
Examine people or animals to assess health conditions or physical characteristics.6.8%Not observed 0.00
Maintain health or medical records.5.6%Not observed 0.00
Operate medical equipment.5.4%Not observed 0.00
Collect information about patients or clients.5.1%Not observed 0.00
Verify personal information.5.1%Moderate 0.41
Execute financial transactions.4.7%Moderate 0.52

"Not observed" is a measurement, not missing data: that activity does not meaningfully appear in the usage sample. AI performance = completion × scope × coverage (user-goal view), 0–1.

What drives this score: the biggest AI-overlapped activity in this role is advise others on products or services; the most important activity AI is not observed doing is fabricate medical devices. The plan below is built around exactly that split.

Balanced exposure: take the gains, deepen the moat.

Next 30 days

  • Harvest the easy wins. Parts of this role, led by Advise others on products or services, are already AI-assistable. Claim those hours back this month.
  • Map your own mix. Your split may differ from the occupation average. Run the six-question personalization above and read your range, not the headline.

Next 90 days

  • Invest saved time in the human core. The majority of this occupation's activities show no observed AI usage. Deepen exactly those, starting with Fabricate medical devices.
  • Stay current, lightly. A monthly hour trying new tools on your real tasks beats panic-learning later.

The longer game

  • Own a niche. Moderate exposure means AI will not define this occupation, but specialists who pair domain depth with tool fluency will out-earn generalists in it.
  • Watch the boundary activities. If the 'Emerging' rows in your table above turn 'High' in a future data update, revisit the plan. No countdown clocks, just recheck.

Compare this occupation with another

Sources for this page:
  • AI applicability score and per-activity metrics: Tomlinson, Jaffe, Wang, Counts & Suri, Working with AI: Measuring the Applicability of Generative AI to Occupations, Microsoft Research 2025 (arXiv:2507.07935), data CC BY 4.0.
  • Occupation description and activity structure: O*NET 30.0 Database, USDOL/ETA, CC BY 4.0.
  • Bands, personalization weights and action plans are JobRiskAI editorial layers; method and limitations on the methodology page.