There are a number of barriers to implementing AI on a wide scale. Most notably, the cost of developing AI applications is prohibitive. With fewer than 10,000 accomplished AI scientists in the world, the cost of employing AI specialists is beyond the reach of most IT organizations.2
Instead, companies like Google, Microsoft and Amazon, which have the resources to pay the high salaries commanded by AI engineers, are leading the industry in developing the complex AI algorithms and the APIs that will allow business software developers like K2 to integrate the technology into their own platforms.
Using these tools to add AI to existing BPM tools helps reduce the amount of time spent on certain tasks, improving customer experience and reducing costs − without building a pool of data scientists and data modeling toolsets in-house.
This cost-effective approach opens up at least two broad categories of AI benefits to users deeper in the organization: natural language interfaces, and data-driven insights derived from the larger context in which the business exists.
AI-driven natural language interfaces make interacting with the application easier and speeds up the process. The AI interface could automate many of the steps just by understanding the words spoken and the business context of the request. In addition, AI and machine learning make it possible for the application to learn from each interaction and streamline the process for the next time.
One major advantage of AI is its ability to employ natural language responses, conversational dialogue and language translations along with the ability to gauge intent to streamline and automate common tasks such as filling out forms. AI can analyze key phrases within the text of a user’s request to get an idea of a person’s intent and automatically fill in a form with the appropriate information.
AI’s machine learning component will have a huge impact on productivity. With each interaction, the system acquires more data about how decisions are made and applies statistical analysis to develop rules around decisions and how they are made. Productivity gains are achieved because machine learning looks at historical data and uses predictive analytics to spot trends and make business decisions based on this data.
It is helpful to look at how this technology might play out in a practical application. The primary critical asset of any company is its workforce. The amount of paperwork involved in managing employee schedules and processing time off requests can be a challenge for even the most efficient human resource departments.
This is an area that AI can help improve efficiency. Instead of having to sit down and manually complete a form, employees can simply speak to their computers or devices and specify the dates they want to take personal time off. The AI interface will understand the context of the request, access data regarding an employee’s schedule, approve the request and automatically complete and submit the form.
The AI-enabled business process management (BPM) application can also access data regarding upcoming events, such as critical customer meetings or other potential conflicts, and suggest alternate dates that would be a better time for the employee to take time off.
In this case, AI goes beyond simple voice recognition. It must actually understand the context of the request and take into account an employee’s life, schedule and their role in the company and apply the appropriate business process rules to the situation.
BPM for healthcare is another area that AI can have a huge impact by helping doctors and nurses capture information about a patient’s symptoms, medications and other health issues, organize this information, and fill in the appropriate forms.
With natural language processing, doctors can simply speak to a device that translates and interprets the information and automatically fills in the appropriate forms. By eliminating the need to manually enter the information, AI would improve productivity by saving time and reducing errors and ultimately saving lives.
2 Metz, Cade. Tech Giants Are Paying Huge Salaries for Scarce A.I. Talent. October 22, 2017. The New York Times.
With natural language processing, doctors can simply speak to a device that translates and interprets the information, and automatically fills out the appropriate forms.
