Will AI replace Photonics Engineers?

AI can do 38% of the work Photonics Engineers do at least twice as fast. People already use it for 2 of their 26 tasks, while 9 more are ready but barely used so far. Robots can technically handle 5 physical tasks. 10 still need a person.

AI is already doing this2 · 12% of time

People already use AI for these tasks in real work, based on Anthropic's analysis of how Claude is used.

  • Analyze system performance or operational requirements.Mostly automated8% of time
  • Read current literature, talk with colleagues, continue education, or participate in professional organizations or conferences to keep abreast of developments in the field.Mostly assisted4% of time

AI could do this next9 · 26% of time

AI can speed these up by at least half, but real use has not caught up yet. These are next in line.

  • Conduct research on new photonics technologies.5% of time
  • Document photonics system or component design processes, including objectives, issues, or outcomes.5% of time
  • Determine applications of photonics appropriate to meet product objectives or features.4% of time
  • Assist in the transition of photonic prototypes to production.4% of time
  • Write reports or proposals related to photonics research or development projects.4% of time
  • Determine commercial, industrial, scientific, or other uses for electro-optical applications or devices.2% of time
  • Create or maintain photonic design histories.1% of time
  • Design solar energy photonics or other materials or devices to generate energy.1% of time
  • Develop photonics sensing or manufacturing technologies to improve the efficiency of manufacturing or related processes.1% of time

Robots can technically do this5 · 33% of time

Physical tasks that today's robots can perform in at least some settings. Robots are cost competitive for very few tasks so far, so this change moves slower.

  • Design, integrate, or test photonics systems or components.Robots: purpose built settings13% of time
  • Conduct testing to determine functionality or optimization or to establish limits of photonics systems or components.Robots: purpose built settings8% of time
  • Develop or test photonic prototypes or models.Robots: purpose built settings8% of time
  • Analyze, fabricate, or test fiber-optic links.Robots: purpose built settings2% of time
  • Select, purchase, set up, operate, or troubleshoot state-of-the-art laser cutting equipment.Robots: purpose built settings1% of time

Still needs a person10 · 29% of time

No real AI use, no proven AI speedup and no robot that can do it yet. This is the part of the job to build on.

  • Develop optical or imaging systems, such as optical imaging products, optical components, image processes, signal process technologies, or optical systems.8% of time
  • Design electro-optical sensing or imaging systems.5% of time
  • Design gas lasers, solid state lasers, infrared, or other light emitting or light sensitive devices.4% of time
  • Oversee or provide expertise on manufacturing, assembly, or fabrication processes.4% of time
  • Train operators, engineers, or other personnel.2% of time
  • Design laser machining equipment for purposes such as high-speed ablation.1% of time
  • Develop laser-processed designs, such as laser-cut medical devices.1% of time
  • Design or develop new crystals for photonics applications.1% of time
  • Design or redesign optical fibers to minimize energy loss.1% of time
  • Design photonics products, such as light sources, displays, or photovoltaics, to achieve increased energy efficiency.1% of time

Your week is not the average

Describe what you actually do and get a personal report: your own tasks, what AI can already do, what stays yours and a 90 day plan.

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What this means

AI can speed up parts of this job, mostly the paperwork and information work around it. The core still depends on hands, presence or relationships. Robots are the other change to watch: they can technically do 38% of the working time.

What to do next

  • Do the 2 tasks AI is already handling with AI yourself. Your peers already are, and it is quickly becoming the baseline.
  • Get ahead on the 9 tasks AI could do next. These move as tools improve, so learning them early pays off.
  • Keep an eye on the 5 physical tasks robots can technically do. Cost keeps most robots out of work today, so this shift is slower.
  • Build on the 10 tasks that stay human. This is where your judgment, skill and relationships matter most.
Energy Engineers, Except Wind and Solar79%Mechatronics Engineers57%Microsystems Engineers71%Robotics Engineers68%Nanosystems Engineers67%Wind Energy Engineers73%

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