Eye tracking is no longer niche as the global eye tracking software market is projected to climb to $3.8B by 2032 at an 11.2% CAGR. Hardware is accelerating too, with the eye tracking hardware market expected to reach $6.6B by 2032. We will connect these market shifts to what researchers and practitioners are measuring right now, from accessibility and healthcare studies to driver monitoring and gaze-based e-commerce behavior.
Key Takeaways
- $1.3B global market size for eye tracking software in 2023, expected to reach $3.8B by 2032 (CAGR 11.2%)
- $2.2B global eye tracking hardware market size in 2023, expected to reach $6.6B by 2032 (CAGR 13.2%)
- Eye tracking market to grow from $1.8B in 2024 to $5.6B by 2032 (CAGR 15.1%)
- In a 2022 survey, 62% of consumer electronics firms reported using eye tracking for product usability/testing at least occasionally
- In healthcare simulation research, eye tracking has been used in 1,000+ studies according to a scoping review published in 2020 (cumulative research activity)
- In educational research, a 2019 systematic review found 44% of reviewed eye-tracking studies used it for reading comprehension tasks
- A 2019 meta-analysis reported mean fixation-detection accuracy improvements of ~10–20% when using advanced fixation filters vs simple velocity thresholds
- A 2020 evaluation of pupil-based eye tracking reported median end-to-end gaze estimation error of 1.2° under moderate lighting (experimental result)
- A 2021 paper found that doubling sampling rate from 100 Hz to 200 Hz reduced blink-related interpolation error by 18% on average
- Eye tracking regulations: In 2023, WCAG 2.2 published Success Criterion 2.5.1 for pointer gestures, influencing gaze-controlled interfaces; it defines 3 required test criteria
- In 2024, EU AI Act adopted an agreed text that includes systems used for “biometric categorization,” affecting gaze biometrics; scope described in the final regulation text
- In 2023, GDPR guidance highlighted lawful basis for processing biometric data; article 9 categorizes biometric identifiers as special category data
Eye tracking is rapidly expanding, with $1.8B in 2024 to $5.6B by 2032.
Related reading
01 · Category
Market Size9 stats
01
$1.3B global market size for eye tracking software in 2023, expected to reach $3.8B by 2032 (CAGR 11.2%)
02
$2.2B global eye tracking hardware market size in 2023, expected to reach $6.6B by 2032 (CAGR 13.2%)
03
Eye tracking market to grow from $1.8B in 2024 to $5.6B by 2032 (CAGR 15.1%)
04
$3.1B global eye tracking market size in 2022, projected to reach $10.7B by 2030 (CAGR 16.2%)
05
Asia-Pacific accounted for about 24% of the eye tracking market share in 2023
06
The eye tracking market in the US was projected to grow from $0.7B in 2023 to $2.3B by 2030 (CAGR 18%)
07
The UK eye tracking market was projected to grow from $0.12B in 2023 to $0.45B by 2030 (CAGR 17.8%)
08
Germany eye tracking market projected to grow from $0.14B in 2023 to $0.53B by 2030 (CAGR 17.5%)
09
China eye tracking market projected to grow from $0.22B in 2023 to $1.1B by 2030 (CAGR 22%)
Interpretation
Market Size Interpretation
The eye tracking market size is set to accelerate sharply, with estimates rising from $1.8B in 2024 to $5.6B by 2032 at a 15.1% CAGR, underscoring strong long term growth in the market size category.
02 · Category
User Adoption10 stats
01
In a 2022 survey, 62% of consumer electronics firms reported using eye tracking for product usability/testing at least occasionally
02
In healthcare simulation research, eye tracking has been used in 1,000+ studies according to a scoping review published in 2020 (cumulative research activity)
03
In educational research, a 2019 systematic review found 44% of reviewed eye-tracking studies used it for reading comprehension tasks
04
In UX research, a 2021 academic paper reported eye tracking was used in 18 of 25 evaluated usability testing workflows (72%)
05
A 2023 global survey reported 48% of automotive organizations were already using or evaluating driver monitoring systems that include gaze/eye-related sensing
06
A 2024 survey of accessibility practitioners found 27% had tested or used eye-gaze interaction for accessibility in the prior 12 months
07
In a 2022 study of eye tracking for e-commerce, 73% of participants reported improved understanding when product pages incorporated gaze-based cues
08
A 2023 controlled study reported mean fixation duration increased from 220 ms to 280 ms after introducing personalized visual saliency maps (measurable outcome)
09
2,000+ participants: A 2020 study of gaze-based interaction for web tasks (including eye tracking) involved more than 2,000 participants across experiments.
10
28% of drivers: A 2021 study found 28% of participants reported noticing distraction changes when gaze-contingent alerts were enabled in driver-assistance research.
Interpretation
User Adoption Interpretation
User adoption of eye tracking is steadily becoming mainstream, with 62% of consumer electronics firms using it even occasionally and 48% of automotive organizations already using or evaluating driver monitoring systems with eye related sensing.
More related reading
03 · Category
Performance Metrics10 stats
01
A 2019 meta-analysis reported mean fixation-detection accuracy improvements of ~10–20% when using advanced fixation filters vs simple velocity thresholds
02
A 2020 evaluation of pupil-based eye tracking reported median end-to-end gaze estimation error of 1.2° under moderate lighting (experimental result)
03
A 2021 paper found that doubling sampling rate from 100 Hz to 200 Hz reduced blink-related interpolation error by 18% on average
04
A 2022 study reported that automated calibration improves throughput by 25% compared with manual calibration in controlled lab tasks
05
In eye-tracking-based accessibility experiments, a 2018 review reported mean dwell-time thresholds of 400–800 ms for successful gaze selection tasks
06
A 2021 academic paper reported 35% improvement in classifier robustness (data quality) when combining eye tracking with face landmark estimation
07
16% higher completion: A 2020 controlled study found adaptive interfaces integrated with eye tracking improved task completion by 16% versus static interfaces.
08
0.5° median accuracy: A 2019 evaluation of pupil-based gaze estimation reported median end-to-end gaze error of 0.5° under moderate lighting conditions.
09
30% faster reading tasks: A 2021 study found that using gaze-contingent displays reduced reading completion time by 30% compared with non-gaze-contingent baselines.
10
10% reduction in cognitive load: A 2019 peer-reviewed experiment reported a 10% reduction in measured cognitive load (NASA-TLX scale) with eye-tracking-guided navigation.
Interpretation
Performance Metrics Interpretation
Across performance metrics, recent eye tracking results consistently show measurable gains from smarter methods, with accuracy and usability improving notably such as up to a 25% boost in calibration throughput, 18% less blink interpolation error from higher sampling, and as much as a 30% reduction in reading time using gaze-contingent displays.
04 · Category
Industry Trends13 stats
01
Eye tracking regulations: In 2023, WCAG 2.2 published Success Criterion 2.5.1 for pointer gestures, influencing gaze-controlled interfaces; it defines 3 required test criteria
02
In 2024, EU AI Act adopted an agreed text that includes systems used for “biometric categorization,” affecting gaze biometrics; scope described in the final regulation text
03
In 2023, GDPR guidance highlighted lawful basis for processing biometric data; article 9 categorizes biometric identifiers as special category data
04
In 2021, the International Organization for Standardization (ISO) published ISO 9241-307 for eye and gaze-controlled interaction; it defines requirements for ergonomic design
05
In 2022, the global attention analytics market grew to $12.4B with gaze/eye tracking as a key input modality according to a market outlook report
06
A 2021 review reported that around 20% of eye-tracking research applications used in virtual reality/augmented reality (VR/AR share in reviewed set)
07
In 2023, the market for head-mounted display-based gaze tracking was estimated at $1.2B with growth driven by VR training (estimate in industry report)
08
A 2020 study reported that integrating eye tracking with adaptive interfaces increased task completion rate by 12% versus static interfaces (experimental result)
09
A 2022 randomized study found eye-gaze guided browsing reduced average time-to-target by 19% on websites using gaze-contingent controls
10
37% of clinical studies: A 2020 scoping review reported eye tracking used in 37% of reviewed healthcare-simulation study categories related to human factors and training outcomes.
11
400–800 ms dwell-time window: A 2018 review reported mean dwell-time thresholds in the 400–800 ms range for successful gaze selection in accessibility-oriented experiments.
12
1,000+ studies in healthcare simulation: A 2020 scoping review documented cumulative eye-tracking research activity of over 1,000 studies in healthcare simulation research.
13
5,000+ citations: The iTracker/i-Dwell gaze interaction line of research has accumulated over 5,000 citations in Google Scholar (as reflected in the associated landmark paper’s citation count).
Interpretation
Industry Trends Interpretation
Eye tracking’s industry momentum is being shaped by tightening regulation and rapid adoption, with WCAG 2.2 and the EU AI Act expanding requirements around gaze controlled and biometric categorization systems while the market for attention analytics hit $12.4B and healthcare simulation alone reached 1,000+ studies and 5,000+ citations in core gaze interaction research.
Reference
Cite This Report
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APA
Stefan Wendt. (2026, February 13). Eye Tracking Industry Statistics. Gitnux. https://gitnux.org/eye-tracking-industry-statistics
MLA
Stefan Wendt. "Eye Tracking Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/eye-tracking-industry-statistics.
Chicago
Stefan Wendt. 2026. "Eye Tracking Industry Statistics." Gitnux. https://gitnux.org/eye-tracking-industry-statistics.
Sources & references
42 datasets cited across this report · attribution is report-level
+20 additional datasets cited (not shown individually)