Legal Knowledge Management and the Rise of Artificial Intelligence
Robotic Refactoring the Workplace
Why Your Next Insurance Claims Processor Could be a Robot
Building an AI Based Machine Learning for Global Economics
The Forgotten Element in Your Big Data Strategy
HK Bain, CEO, Digitech Systems
WiFi Networks: Shifting from Providing a Service to Improving the...
Daniel J. Strojny, Interim Associate Director of Network and IT Operations, University of St. Thomas
Breaking the Stereotypes in the Development of AI
Yves Jacquier, Executive Director, Production Studio Services, Ubisoft
Operationalize Machine Learning
Zongjie Diao, Director of Product Strategy and Management, Data Center Compute Group, CISCO
Thank you for Subscribing to CIO Applications Weekly Brief
Leveraging AI for an Efficient Corporate Treasury
With AI into the play, data sets will guide the firms assisting them in streamlining their operations and supply chain processes.
FREMONT, CA: With each online interactions happening around the globe, data has grown exponentially in the past few years. According to the experts, the world will be generating more than 163 zettabytes (ZB) of data per year by 2025. With massive data sets at their disposal, the companies must be aware of the best practices required to understand and manage the sea of data. Utilization of the technologies such as artificial intelligence (AI) and internet of things (IoT) plays a significant role while leveraging the data sets.
Potential of Data
With a magnificent surge in online connectivity and digitization, a huge amount of data sets are available to be tapped. The data sets can help companies to realize better their customer needs helping them to optimize services by utilizing advanced analytics to spot future supply or tailoring products for customers. The data sets will also guide the firms while streamlining their operations and supply chain processes. Despite the advancements in data analytics, the true potential of data boom will be leveraged over the next ten years when the current technology will get more evolved and mature. However, even in the future, the efficient utilization of such data sets cannot be accomplished without throwing AI into the mix.
AI-enabled solutions are already contributing to the sectors across verticals. Its ability to digest massive data sets and providing critical insights which would have remained hidden if approached manually form the basis of its widespread adoption. Sophisticated AI models which use machine learning (ML) ranks high on the expert's list. ML algorithms provide users with prescriptive and predictive technology by leveraging concepts such as deep learning and neural networks in new applications like natural language processing or computer vision. Organizations such as banks are incorporating AI and ML to identify operational risks and counterparty credit risk. Such assessments will help the firms to move from a reactive approach towards a predictive approach concerning risk management.
Corporate Treasury and AI
The short-term impact of AI on corporate treasury can be less significant. However, with AI-enabled forecasts, businesses will save huge in the long run. Further AI’s self-learning capabilities will increase the quality of the forecast, thereby removing some of the costly manual processes. Primary applications include the use of ML in hedging strategies and optimizing cash management. It also has a crucial role in the case of machine-executable regulatory compliance. Further, AI-driven predictive analysis can also improve procurement processes for the treasurers, while also impacting sales forecasts and supply chain management activities.
Several corporate accept that AI will be a game-changer for their enterprises. AI’s ability to deconstruct massive volumes of data will enhance various operational activities enabling new sources of revenues to be exploited and cost synergies to be obtained. Though these technologies can simplify numerous business processes, human involvement in sectors such as query resolution and client engagement will still have a long road ahead. It means that service providers must maintain a balance if they wish to have a long term client relationship.