There is increased use of cognitive technologies to solve business problems; many executives believe that Artificial Intelligence (AI) will substantially transform their companies within three years as it is slowly making its way into everyday business. From workflow management to trend predictions and providing new business opportunities, AI has various functions in an organization.
There are three essential business needs that AI can address: automating business processes (typically back-office administrative and financial activities), improving insight through data analysis, and engaging with customers and employees. To maximize the benefits of AI, companies must understand which technologies perform which types of tasks, create a prioritized portfolio of projects based on their business needs, and develop plans to scale up the technology across the company.
The three business needs that AI can address
Automating Business Processes: The most common business that needs to be addressed by AI is process automation for digital and physical tasks – typically for back-office administrative and financial activities – using Robotic Process Automation (RPA) technologies. The technology behind RPA is more advanced than earlier business-process automation tools because here, the code on a server (robots) consumes and inputs data from multiple IT systems much more efficiently than a human being.
RPA tasks include:
Transferring data from email and contact center systems to systems of record.
Replacing lost credit or ATM cards, updating customer records, and coordinating customer service.
Extracting information from multiple document types to reconcile service failures across billing systems.
Using natural language processing to read legal and contractual documents and extract provisions.
Improving Insights with Data Analysis: Machine learning and AI insights differ from traditional analytics in three key ways: they typically make predictions based on a bigger pool of data, they are trained on the part of the set of data, and the models become better over time-that is, their ability to use new data to make predictions or classify things improves. There are versions of AI capable of recognizing speech and images. In addition, AI is capable of generating new data for better analytics. Although data curation has been labor-intensive, AI can now identify probabilistic matches -likely to be associated with the same individual or company, but in slightly different formats - across databases and help eliminate redundancies.
Customer and Employee Engagement: Companies tend to take a conservative approach to customer-facing AI technologies primarily because of their immaturity, but that is about to change as AI advances, and firms get more comfortable turning over customer interactions to machines.
Some of the tasks AI can take over to make customer and employee engagement more efficient are as follows:
Chatbots that offer 24/7 customer support and cover many issues, including password requests and technical support questions - all in the customer's natural language.
Internal sites where employee questions regarding IT, employee benefits, and HR policies are answered.
A product or service recommendation system designed to increase personalization, engagement, and sales, typically including images and rich language.
AI tools are becoming more widely used by companies. They are experimenting with projects that combine elements from the three categories mentioned earlier to reap the benefits of AI.
As AI becomes more sophisticated, information-intensive businesses such as marketing, health care, financial services, education, and professional services could become more valuable and less expensive. Taking care of routine transactions, answering the same questions repeatedly, and extracting data from endless documents can be handled by machines, allowing humans to work more productively and creatively. Additionally, AI technologies are catalysts for the emergence of data-intensive technologies like the Internet of Things, autonomous vehicles, and mobile and multichannel consumer technologies.