Every industry that uses AI also needs to use data annotation services. That is vital to the data training and machine learning used to produce new useful AI for some specific industrial application. Each industry has different needs for AI.
The list provided here is far from complete as AI is increasingly adopted. In time almost every human job can be completely automated away. It is more likely that those jobs will change. Productivity will continue to increase as AI and automation advance. Profits will increase as productivity increases and new industries adopt AI.
Automating away jobs doesn't have to be a bad thing. Sometimes we lack important expert professionals like doctors. If an AI "autodoc" is just as good as a real doctor, then it is certainly better than no doctor at all. Ideally, AI will assist human doctors, not replace them.
The adoption of AI is growing rapidly and has already changed the economy. Behind that is an increasing amount of data collection and data annotation. The fact is that pretty much every industry and type of business can benefit from the adoption of AI.
An AI can compose music and make art, automating creative tasks that we used to think that only a human can do. AI and machine learning algorithms rely on data annotation services in their creation.
That means that every industry needs new, innovative AI. Of course, every AI needs scale data annotation services in order to be made. That also means it would be hard to give a complete list of every industry that currently uses AI or could benefit from it.
A List of 40+ Industries That Use AI
4. Cancer Screening
5. Research and development of medications
6. Research and development of new cosmetics
7. Life Sciences
8. Predict the spread of diseases
10. Prescribe Medication and prevent drug abuse.
15. Food Tech
17. Financial Services
18. Fraud Detection
19. Algorithmic Stock Trading
21. Insurance Underwriting
22. Claims Processing
26. Waste Management
30. Law Enforcement
31. Justice Systems
32. Criminal Law
33. Civil Law
34. Automotive Industry
35. Document Annotation
36. Industrial Agriculture
42. Industrial Design
43. Augmented Reality
44. Virtual Reality
The Future of Data Annotation and AI in Industry and Commerce
The adoption and advancement of AI in every industry are inevitable. AI will continue assimilating into our economies and societies for better or worse. Overall, AI does much better than worse.
This future of AI is big enough to massively raise productivity without humans having to work any harder or smarter. Markets and businesses require constant growth and productivity in order to succeed and turn a profit.
That means there will be plenty of room for competing companies, products, and services to grow. New AI will need to be created and trained to drive that future productivity and profit increase. Vital data annotation services are what make this possible.
For example, AI in Security requires things like facial recognition and gait recognition. It will also need diverse data from people of all ages, ethnicities, and walks of life. An AI "autodoc" requires medical data annotation for machine learning to learn the equivalent of years of medicine rapidly.
A self-driving car requires an incredible amount of data and data annotation. The required data can change with the region for which the car is manufactured. So for another example, a car that navigates a desert state like Nevada or New Mexico probably has fewer obstacles to recognize. The roads and environment differ from other states. Other countries and regions will have different rules of the road and different obstacles to recognize and avoid. Making a car that can drive itself everywhere would be a tremendous task. As it is now, an autonomous vehicle would at least take software updates depending on its regional location.
Every industry and AI has its own unique challenges. The solution to those many challenges is more data, more data annotation, and more variety of data in the used datasets. That data can be collected and provided to get all the tools you need to do your own machine learning data annotation. So you can take on that enormous job yourself if you want.
Creating a new innovative AI that fills some unmet needs in an industry is already a large job. So, you can always allow us to do your data creation and collection and provide all the outsource data annotation services you need.