AI in 2020: how use cases will stimulate the use of artificial intelligence

Discover why predictions about trends in artificial intelligence include face recognition, genetics, privacy and AR.

Image: Igor Borisenko, Getty Images / iStockphoto

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As more companies realize the benefits of artificial intelligence (AI) in their daily activities, the demand for use cases will increase and drive the AI ​​market. The leaps forward in AI will continue as we see this young technology flourish into wider and more advanced use.

In 2020, companies will monitor proven AI use cases that can help their businesses – they must accelerate ROI and minimize risk. Look for 2020 as a year of AI expansion to companies and from the proof-of-concept labs.

Here are seven leading use-case trends that I see for AI in 2020.

1. More industries use face recognition technology
Face recognition is already being used in retail, banking, and insurance to identify customers and deter fraud, and with the police to deter crime. Expect more face recognition technologies to be deployed in areas such as security and ID control, transportation logistics, healthcare, fast food restaurants, airlines, food and beverage companies, hotels, cars and the energy industry.

SEE: Roadmap digital transformation (free PDF) (TechRepublic)

2. More privacy procedures
Customers will consider what they believe is infringing their right to privacy as technologies such as face recognition are applied in more places. In 2019, a federal appeals court rejected Facebook’s attempt to destroy a class-action lawsuit alleging that the company had illegally collected and stored biometric data for millions of users without their consent.

The ACLU is ready to go after organizations that use facial recognition for purposes that could potentially threaten the constitutional privacy rights of individuals. Organizations considering the implementation of face recognition technology should have their legal and compliance departments investigated before starting such projects.

3. Breakthroughs in medicine and genetics
Using AI, gene processing becomes more accurate and can pave the way for eliminating or modifying the effects of future diseases.

3. More use of augmented reality
In 2019, NASCAR transformed racing entertainment with augmented reality (AR) presentations of Burnout events for racing tires for fans with mobile devices with AR. Arifical neural networks and the ability to derive the positions of objects in real time made the experience possible.

In 2020, more companies in entertainment and other industrial sectors will launch 3D AR experiences to engage customers with their brands.

4. Progress in transport and logistics
By 2025, AI in transport is expected to deliver $ 173 billion in cost savings across the entire automotive OEM supply chain, and self-driving technology is expected to be a market of $ 556 billion by 2026. In warehouses, self-navigating robots use AI to move pallets without human intervention, and en route, shipping companies track and track trucks and goods to ensure timely deliveries on the safest routes.

In 2020 we continue to see progress in transport automation – from software-driven programs to more sustainable sensors to lighter light detection and varying (LiDar) devices.

SEE: Autonomous vehicles and the company (ZDNet / TechRepublic special function) Download the free PDF version (TechRepublic)

5. Your next cubemate can be virtual
In 2019, some companies started assigning employee IDs to virtual digital employees, and then assigning these digital employees to projects and workloads. AI-powered robots and digital assistants take over many tasks in offices, on production floors, in call centers and in military fleets. In some cases, digital workers will replace their human counterparts. Usually, human and digital employees will work together at work, with people assuming responsibilities for complicated decision making and dealing with exceptions.

6. Robot automation is becoming more popular
As part of the digital work revolution, more companies will implement robotic process automation (RPA), a software-driven automation technology that adopts employee-defined work rules and instructs a virtual robot to perform work tasks. Office tasks such as keying in data from one system to another can be automated or a form can be checked for completeness; this allows people to do the more complicated office jobs.

SEE: How to integrate robot automation in big data projects (TechRepublic)

7. Automated preventive maintenance
The Quality 4.0 initiative launched in Germany will continue to expand globally, and with it automated maintenance controls of production equipment that send warnings to factory managers when equipment needs to be serviced. Predictive maintenance allows companies to shut down and / or repair equipment before it fails, and keeps production lines moving.

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