How AI Might Affect Demand

Artificial intelligence is often portrayed as a technology that will lower costs by replacing skilled workers, but ophthalmology provides an interesting counterexample. AI can now perform one relatively routine task, screening patients with diabetes for diabetic retinopathy, without requiring an ophthalmologist to examine every patient. In the ACCESS randomized trial, offering an autonomous AI eye exam during a diabetes visit increased screening completion from just 22% with conventional referral to 100%. Among patients receiving an abnormal AI result, 64% subsequently visited an eye-care provider. AI therefore substitutes for some ophthalmologist labor while dramatically increasing the number of patients who make it through the first stage of the eye-care supply chain. (Nature)

AI has lowered the cost of one link in the screening → referral → treatment supply chain. That cost reduction need not appear as lower overall expenses. Instead, it can appear as improved quality that increases demand: screening becomes easier, more patients are screened, and ophthalmologists can concentrate on patients who actually need their expertise. A 2026 Johns Hopkins study of 3,745 adults with diabetes provides evidence of this downstream effect, finding that AI screening in primary-care offices increased presentation to specialist eye care among an at-risk population. A recent meta-analysis of AI diabetic-retinopathy screening likewise concludes that it is generally cost-effective, particularly when it expands screening to underserved populations. (Nature)

The interesting result is that a cost-reducing technology can increase rather than decrease demand for expensive downstream services. Cheaper screening means more screening; more screening discovers more disease; and more detected disease generates referrals and treatment. Total spending on eye care could therefore rise even as the cost of producing a given level of eye health falls. The productivity gain results more in demand augmented by higher quality (shifting demand out) rather than lower price (moving along the demand curve). This may be a useful lesson for thinking about AI throughout the economy. When innovation improves one stage of a supply chain, its benefits need not appear primarily as lower prices or fewer workers. They may instead appear as better matching, greater use of complementary services, and higher-quality final output, in this case, healthier eyes.