AI Sector Overviews Articles and Reports
Artificial intelligence “sector overview” reports are designed to help business leaders explore the possibilities and important AI trends across industries. Search our sector overview reports below:
Many of the top Fortune 500 retailers have begun using AI and ML to solve business problems for various departments. Walmart and Costco share one in grocery stocking, which includes the freshness and condition of the products along with timing the restocks for peak hours.
Business process management (BPM) in banking involves the automation of operations management by identifying, modeling, analyzing, and improving business processes. Many banks already have some form of BPM for various process. For example, compliance processes at most banks tend to have some form of software automation in their workflows.
Retailers and financial institutions are adopting artificial intelligence and machine learning in their business to solve various business problems such as cybersecurity and document digitization. However, many of these companies are also using AI to improve their payment processes for their clients and customers. These types of applications are usually layered into an existing payments technology stack, which could include straight-through processing (STP) or robotic process automation (RPA).
Chatbots are one of the most talked-about uses of natural language processing (NLP) software in business. Some of the most common application areas for chatbots include customer service, healthcare, and financial advisory.
Robotic Process Automation (RPA) is a rule-based software solution that automates repetitive tasks without any self-learning capabilities. It is not inherently artificial intelligence. RPA vendors now offer AI-tools as add-ons to their automation platforms. This includes RPA applications in banking where some form of AI, such as computer vision or natural language processing, is a part of the automation workflow.
The insurance industry is responsible for a multitude of sensitive financial data concerning both its customer base and staff. Any breach to an insurance company's CRM or other claims database could compromise the personal data of multiple people at once, which puts the company at risk as well.