With every year, AI and ML become more mature and well rounded. At the same time data quantity and quality grow at breakneck speeds.
What does this mean for the future of your business?
We recently got a peak at the forecast for global revenues of different fields of AI (see below).
Naturally, this got us thinking: ‘’Why these areas?’’, so we combed through a lot of research, both our own and externally sourced.
So, here are our findings on the top 5 most lucrative use cases of AI until 2025.
1.Static image recognition, classification, and tagging
A computer ‘‘vision’’ technique that allows for the interpretation and categorization of what is “seen” in images or videos. Often referred to as “image classification” or “image labelling” (or tagging), this task is essential in solving many computers vision-based ML issues.
Some interesting current and potential uses:
- Customer analysis – learning more about individuals through detection of logos or text in the products they consume and use.
- Facial verification of users – Face ID
- Tagging of images – using tags or keywords on images to organize and sift through them better. Enables organization and categorization.
- Content moderation for different purposes related to social media
- Accessibility – for the visually impaired.
- Visual Search – using real images to procure more reliable online searches. Allows for better targeting based on shopper behaviours and interests.
2. Algorithmic trading strategy performance improvement
This uses AI to place, buy and sell orders automatically according to a specified set of rules or logic. These rules are collectively referred to as the trading algorithm.
So, why is it lucrative?
With stock, bond, Forex, Crypto, and all other forms of trading currently using AI algorithm trading, optimization and improvement in this field can only bring higher and higher returns. From reduced transaction costs to precise execution of trades, and accurate formulation of decisions while accounting for multiple factors.
3. Efficient, Scalable processing of patient data
AI and ML are used in the medical field to search through medical data and find insights to help improve health outcomes and patient experiences. This also helps medical practitioners by saving valuable time otherwise spent in searching through data. Clinical decision support provided by AI is still improving. CT scans, x-rays, MRI’s, and other graphical data is also analysed with great success.
Disease detection and diagnosis is also something that AI can provide. The current pandemic boosted the development of AI in healthcare, and this growth is predicted to increase greatly by 2025, with accelerated drug development being a massive part of the predicted revenue. AI can formulate better drug designs and find new drug combinations easier.
4. Predictive Maintenance
When it comes to why Predictive Maintenance is expected to grow so much, there is one main prediction in development – cognitive maintenance.
Cognitive maintenance – based on cognitive analytics where AI can learn from past actions and results, can look for correlations and prescribe courses of action. It changes a company’s behaviour from reactive to prescriptive. In short, data from connected equipment and products is analysed, combined with service knowledge and data, and using the result to improve equipment and uptime.
So, while Predictive maintenance accurately identifies and predicts faults in equipment, cognitive maintenance then provides the engineers responsible with detailed information on how to prevent or repair the equipment.
5. Object identification, detection, classification, tracking
Object detection, similar to the first point of our article, is used to analyse pictures and video frames. The difference however is that in the case of object detection, the AI analyses the image or video frame looking for a specific visual object. The goal is to answer the question ‘’What objects are where?’’.
How will this field earn the predicted revenue?
There are many applications, such as healthcare monitoring, autonomous driving, video surveillance, anomaly detection, or robot vision. Agriculture has also recently started to benefit from this technology with animal detection – counting and monitoring. The broad and varied uses for this tool are what makes it lucrative.
Conclusion
We believe that the list is surprisingly on track with which areas of AI will top the charts, however, there is an argument that the top 5 most lucrative use cases of AI are interchangeable, and only time can show which developments prove to be ahead of others. In any case AI will keep developing at breakneck speeds and drive our possibilities forward.
Cosmos Thrace believes that implementing AI in your business can future proof it, as having the foundations set now, can lead to much easier adoption of future technologies. Get in touch if you would like to discuss the ‘’why?’’ and ‘’how’’ of the most lucrative aspects of AI development.
