As more businesses realize the benefits of artificial intelligence (AI) in their daily operations, 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 blossom into wider and more advanced uses.
In 2020, companies will keep an eye on proven AI use cases that can help their businesses–they should speed ROI and minimize risk. Look for 2020 to be a year of AI expansion into businesses and out of the proof-of-concept labs.
Here are seven leading use-case trends I see for AI in 2020.
1.More industries will use facial recognition technology
Facial recognition is already being deployed in retail, banking, and insurance to identify customers and deter fraud, as well as in law enforcement to deter crime. Expect more facial-recognition technologies to be deployed in areas such as security and ID checking, transportation logistics, healthcare, fast food restaurants, airlines, food and beverage companies, hotels, automobiles, and the energy industry.
SEE: Tech Predictions For 2020: More must-read coverage (TechRepublic on Flipboard)
2. More privacy lawsuits
Customers will weigh in on what they feel are intrusions into their rights to privacy as technologies like facial recognition get deployed in more places. In 2019, a federal appeals court rejected Facebook’s attempt to nullify a class-action lawsuit that alleged the company had illegally collected and stored biometric data for millions of users without their consent.
The ACLU is poised 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 facial recognition technology should have their legal and compliance departments do due diligence before starting such projects.
3. Breakthroughs in medicine and genetics
With the help of AI, gene editing is becoming more accurate and could pave the way to eliminating or altering the effects of diseases in the future.
SEE: Digital transformation road map (free PDF) (TechRepublic)
3. More uses of augmented reality
In 2019, NASCAR transformed racing entertainment with augmented reality (AR) presentations of race car tire Burnout events for fans with AR-enabled mobile devices. Arificial neural networks and the ability to infer the positions of objects in real time enabled the experience.
In 2020, more companies in entertainment and other industry sectors will launch 3D AR experiences to engage customers with their brands.
4. Advances in transportation and logistics
By 2025, AI in transportation is projected to deliver $173 billion in cost savings across the automotive OEM supply chain, and self-driving technology is projected to be a $556 billion market by 2026. In warehouses, self-navigating robots use AI to move pallets without a need for human intervention, and on the road, transportation companies track and trace trucks and goods to assure on-time deliveries over the safest routes.
In 2020, we’ll continue to see advances in transportation automation—from software-controlled programs to more durable sensors to lighter-weight light detection and ranging (LiDar) devices.
5. Your next cubemate could be virtual
In 2019, some companies began assigning employee IDs to virtual digital workers, and then assigned these digital workers to projects and workloads. AI-powered robots and digital assistants are taking over rote tasks in offices, on manufacturing floors, in call centers, and in military fleets. In some cases, digital workers will replace their human counterparts. Most often, human and digital workers will collaborate on work, with humans assuming responsibilities for complicated decision-making and exception handling.
6. Robotic process automation will become more popular
As part of the digital work revolution, more companies will implement robotic process automation (RPA), a software-driven automation technology that takes the employee-defined work rules and directs a virtual robot to do work tasks. Office tasks such as keying in data from one system to another could be automated, or a form could be checked for completeness; this enables humans to do the more complicated office jobs.
SEE: How to integrate robotic process automation in big data projects (TechRepublic)
7. Automated preventive maintenance
The Quality 4.0 Initiative that started in Germany will continue to expand worldwide, and with it, automated maintenance checks of production equipment that send alerts to plant managers when equipment needs to be serviced. Predictive maintenance enables companies to switch out and/or repair equipment before it fails, and keeps production lines moving.