Is profitable AI as rare as a unicorn? When it comes to practical business uses, we put artificial intelligence (AI) technologies into three categories:
- Cool, but in futuristic prototype mode
- Cool, but no person or business can afford to deploy it
- Cool, deployed and actually making money
Okay, we’ve established that it’s cool. But how many organizations, big or small, are recognizing true, measurable ROI from deploying it? Not as many as you’d think. We’ve identified three of our favorite money-making AI uses from real (but anonymized in this article) organizations.
Top AI uses right now:
1) Mitigating mental health issues
One forward-thinking mental health center leverages AI predictive technology to forecast patient aggression with accuracy and reliability. Since computers can comb through patient data much faster than busy doctors and staff, AI provides the center with a daily ranked list of high, medium and lower-risk patients. This report is based on both historical and recent data on the patient, including potential triggers for aggression, giving insight to clinical staff to develop a risk mitigation plan.
The center successfully leverages AI to forecast patient aggression by capturing the knowledge of their best clinicians and using that for the best possible decision-making across the organization. In its ongoing mission to adorn its patients with respect and dignity, not restraints, the center has measurably mitigated violent behavior, staff and patient injuries, suicide attempts, and litigation.
2) Automating the call center
A large telecom call center, at any given time, receives 4,000 to 7,000 calls worldwide. They need to address thousands of questions accurately within a short amount of time, or customer satisfaction decreases. Furthermore, customer satisfaction scores plummet when issues fail to be resolved by the first agent engaged (via chat or phone).
With a focus on the chatbot, one global telecom giant leverages AI, combined with cognitive analytics software, to dramatically elevate call resolution across its call center. Upon deployment of the new solution, the company reported an immediate and positive impact around call resolution, call-handled time and customer satisfaction across its call and help center. For example, although a “real person” is still optimal is complex cases, a common password reset request can be resolved by AI. Through machine learning, this technology trains data to handle that issue, freeing up an agent’s time to address other questions.
3) Revolutionizing digital banking
As the growing number of millennial consumers demand mobile payment and banking solutions that are automated, secure, fast and simple—one FinTech firm is leading the digital banking revolution with AI and advanced automation.
Back to computers doing what humans can’t, the firm automates “knowledge worker” intelligence with cognitive models. The technology platform consolidates payment card processing and disparate back-end systems, using a software layer that provides omnichannel access, real-time customer interactions and a large library of value-added tools. This allows for rapidly deployable new product innovations—and shifts the paradigm from transaction-centric payment products to user-experience-centric products.
In terms of scaling beyond human capabilities, the flow of money, along with several terabytes of data, is now moving rapidly between banks and customers. Advanced automation enables the firm to help banks complete transactional tasks in seconds, not hours or days.
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