Written by IBM's conversational AI experts, this report demonstrates the market opportunity for conversational AI and outlines the use cases that will enhance your customer service and drive value across your organization.
Gaining full visibility into network traffic in complex environments requires integrating network packet analysis and system events. Learn more!
Read this Digital Dialogue to learn about new evaluation tools that promote employee retention by utilizing Self Development Objectives, and focusing on the employee as a person rather than their role in the firm.
The maturity of AI and machine learning (ML) use has reached a point where businesses of all sizes are using the technology as key strategic technology enablers. As an analytic and data science professional, you’re in control. You can empower people in centers of excellence (COE) and line of business (LOB) to C-level executives with scalable insights with trust and transparency. Data science competency is critical for your business to increase predictability, optimize operations and govern use of AI.
ESG recently completed testing of IBM Watson Studio and Watson Machine Learning, which are designed to enable organizations to accelerate the value they can extract from AI more easily. Testing examined how IBM Watson Studio and Watson Machine Learning collect data, organize an analytics foundation, and analyze insights at scale—with a focus on the ease of operationalizing AI and data science to improve trust, simplify compliance, and speed monetization.
Onboarding quality customer data across all sources is essential to improve the customer experience and meet compliance while cutting costs. Melissa’s AI-enabled active data quality solutions ensure your rising data volumes comply with business rules and are analytics ready.
The ability to integrate APIs from multiple sources is critical to success. New approaches to enterprise integration, backed by flexible, cloud-ready technologies, are necessary. Agile integration, an architectural approach, combines agile methods and practices with technologies for the purpose of rapidly integrating applications and data.
For the majority of organizations, digital business means pivoting to a culture of organizational agility, where the rapid pace of demand can only be satisfied by faster and more flexible development and delivery models. As most organizations do not have the luxury of completely rebuilding their technology foundation or immediately adopting new practices and mindsets, they are embracing gradual yet fundamental shifts in culture, processes, and technology to support greater velocity and agility. Learn 8 steps to guide your journey to cloud-native application development, including Red Hat® customer success stories.
Mayo Clinic started working with IBM Watson for Clinical Trial Matching in 2014. Over time, a team of Mayo experts determined optimal workflows and enhanced patient awareness about clinical trials. The system was implemented with a team of clinical research coordinators in the ambulatory practice for breast cancer.
Read this article to learn how Watson for Clinical Trial Matching has enabled Mayo to improve both enrollment metrics for breast cancer clinical trials as well as operational efficiency in its practice.
While cancer research is crucial to help the growing number of patients suffering from the disease, it is difficult to find enough patients that meet the criteria of clinical trials. Using spreadsheets to determine who would benefit from a new treatment can be slow and error prone.
Read this paper to find out how IBM Watson for Clinical Trials Matching is making a major difference.
Read this paper to learn how oncologists using IBM® Watson® for Genomics can quickly view insights from genomic data analysis which can be used to help them create personalized treatment plans for patients.
New trust and transparency capabilities from IBM represent the cornerstone of how we’re helping businesses build, run and manage AI models and applications across their organizations.