yoshitaka272 - Fotolia
Many people associate artificial intelligence technology with the Terminator's infamous Skynet system that takes over the world and attempts to eliminate mankind. Yet these technologies can provide services that are far more practical and desirable today.
By submitting your personal information, you agree that TechTarget and its partners may contact you regarding relevant content, products and special offers.
Artificial intelligence (AI) has been a hot topic of debate since the 1960s. Now, AI has resurfaced in the form of machine learning and cognitive computing, which essentially allow computers to learn information by detecting patterns based on algorithms. These technologies have a better chance of success today because of the ubiquity of mobile technology and powerful cloud-based analytics.
Mobile and cloud-based applications provide fertile ground for AI technology, such as chat bots and virtual assistants, to take advantage of internet algorithms. Credit card fraud detection and compromised password recognition for social networking sites are two examples of machine learning at work.
Apple, Google and Microsoft all highlighted how machine learning can improve messaging services at their developer conferences this year. Companies such as Baidu and WeChat already have virtual assistant messaging apps that allow consumers to use voice and text commands to find information, book services and purchase goods. Meanwhile, Amazon surprised everyone in the retail world with the success of the Alexa voice service and Echo speaker system.
Machine learning powers mobile apps
Bots, voice navigation and machine learning have the opportunity to change how users interact with information in three major ways:
- Improved product discovery;
- Faster completion of workflows and transactions; and
- More satisfied user experiences with lower support costs.
These technologies will also change how companies approach user engagement within their mobile apps and websites. It's difficult to get users to download a mobile application for a specific use, and the mobile web experience is often poor. So how can organizations make their services top of mind with customers and employees while they're on the go?
By 2025, automation technologies such as AI, cognitive computing and robots will replace 16% of jobs.
Source: "The Future of Jobs, 2025: Working Side by Side With Robots," Forrester Research
Bots -- software that runs automated tasks, often via scripts, to offer information faster -- provide one way of improving the experience without requiring users to download specific mobile applications. Bots enable users to access services easily by embedding them in software they already use, such as a messaging app. This approach connects many different experiences and creates a clear app workflow for the user. For example, a small retailer could embed access to its services via a bot within a banking app to push local promotions.
But there are also challenges. A company must ensure that its partners won't compromise the experience when its bot is embedded in another service.
The development team must construct its products and services in a manner that is accessible to third-party apps. This means embracing APIs and a microservices architecture, in which individual services exist separately but share common infrastructure to connect with one another. Additionally, developers need to work together to build the algorithms that allow a bot to recognize patterns and then aggregate and present data. Data scientists and business analysts can use machine learning to construct their initial algorithms, but developers need to review the output to ensure the outcome was as they expected.
Bots can help businesses create more personalized interactions. So regardless of the market your company serves, business leaders should evaluate how bots can improve the customer and employee experience.
This article originally appeared in the October issue of the Modern Mobility e-zine.
Gartner: Mobility entering the post-app era
IT's intro to machine learning
Guide to AI applications