As enterprises integrate AI to enhance customer experience and optimize business processes, AI is increasingly integrated into their operating models, creating the necessity to effectively design, deploy and support the underlying infrastructure for the sleek operation of AI-powered mission-critical applications.
IBM Technology Lifecycle Support (TLS) provides a broad range of integrated data center services and support designed to assist speed up our clients' transformation to hybrid cloud and AI. IBM TLS provides support services for IBM infrastructure products and products from leading third-party systems, in addition to support services for software and enterprise networking.
Our AI-powered technology foundation enables us to supply support when issues arise and help firms proactively and preventively avoid them. This enables us to assist our customers maintain and deliver high levels of availability and resilience.
Our path to integrating AI into support
To meet the dimensions, complexity and criticality of the infrastructure supported by IBM TLS, we’re early adopters of AI and automation technology. From rule-based systems to advanced machine learning models to generative AI, we repeatedly adopt latest technologies to deliver cutting-edge support at scale and across a broad product portfolio.
We leverage the innovation of IBM software and infrastructure products and collaborate with IBM Research®. As Client Zero for watsonx™ use cases, IBM also uses AI support to enhance the shopper and worker experience.
IT support offers enormous potential for leveraging AI in all its many facets, making it a key area for innovation. The next generation of support will increasingly leverage AI to deliver value to customers, engineers, and the partner ecosystem.
Our solutions are designed to assist our clients achieve greater value by way of reliability, availability and resilience of the systems they implement from IBM and our partners. This will help create value for his or her internal IT staff and, in turn, for his or her customers.
Managers expect ends in customer support – and we deliver
AI-based assistants help our support engineers gain deeper and proactive insights, find actionable and personalized problem solutions, and automate repetitive processes and tasks. The IBM Institute for Business Value (IBV) surveyed nearly 1,500 customer support managers, directors, and executives from organizations in 34 countries and all major industries which were using conversational AI for a minimum of 12 months.
According to the IBV report “Customer Service and the Benefit of Generative AI,” nearly two-thirds of business leaders surveyed expect generative AI to extend customer satisfaction, and greater than half expect increased human worker satisfaction, revenue growth, and customer loyalty.
IBM TLS provides our clients with tools and offerings with integrated AI to assist them achieve their IT goals and gain deeper insights into their environments (including proactive views).
For example, our Insights into support The offering enables customers to achieve deeper insights into their assets, infrastructure security risks and case evaluation. Our broad portfolio of services covers all the product lifecycle. It includes design, construct, deploy, support, upgrade and decommissioning of mission-critical core systems and latest systems for AI. They require extensive expertise in computing, networking, storage, performance and scaling.
By leveraging AI and automation capabilities, we will deliver support services across multiple channels, including chat, email, and phone. This enables our support agents to supply more informed assistance and improve the general customer experience.
Deepen support services with Watsonx and a data-driven approach
By leveraging the IBM Watsonx data, AI and governance product portfolio, TLS is creating latest progressive offerings that help our clients optimize their infrastructure investments. In addition, we enable operations for our many hundreds of clients with an insightful, personalized and proactive support experience and access feedback from our implementation on the functionality of IBM software and infrastructure products.
We have taken a data-driven approach to measure the improvements in our support and delivery processes caused by AI. We collect business and technical metrics to derive key performance indicators (KPIs) that drive a continuous improvement methodology. These KPIs include improvements in our customer Net Promoter Score (NPS), the effectiveness of our self-service virtual assistants, and the variety of issues proactively identified and resolved. In addition, we have now collected metrics for the time taken to resolve customer incidents and related process inefficiencies.
Overcoming challenges to fulfill customer expectations
IBM TLS supports our clients in several ways. We provide integrated product support for the information center across IBM infrastructure and choose partner products that integrate AI for self-service and provisioning. We also provide AI-powered insights into supported assets, risks, and cases. We help our clients speed up the delivery of AI solutions to their stakeholders with offerings and services designed for infrastructure assessment, provisioning, and decommissioning.
Based on our experience and expertise in coping with customers, these are the highest customer priorities in product support:
- Responsive customer experience. Enable available personalized self-service access, deep insights, and proactive automated alerts that make our customers' SREs simpler.
- High quality service and support. Leverage insights from multiple cases with personalized context to assist our support engineers deliver improved service quality and maximize the supply of your systems.
- Efficient service and support. Continuously evaluate and improve the efficiency of our back-end processes to speed up responses and eliminate bottlenecks.
AI and automation (in all forms, including the most recent generative models based on the IBM Watsonx platform) are critical to delivering these capabilities. However, implementing AI presents several challenges, including
- Manage the complexity that comes from the variety of infrastructures, product versions, and implementation-specific customizations and integrations.
- Access to data sources taking into consideration multilingualism, data protection and compliance points.
- Consider the human factor when coping with mission-critical systems with low failure tolerance and the potential for giant financial and regulatory impact.
IBM TLS is currently working closely with IBM CIO, Software and Research Teams addressing these challenges. We are implementing novel and scalable approaches to vectorizing, rating, and summarizing extensive product documentation. Our goal is to put the inspiration for implementing Retrieval Augmented Generation (RAG) approaches to support our customers through self-service channels and enable our engineers to reply to cases based on similar historical cases.
We also implement unified test frameworks, effectiveness and accuracy metrics for the underlying models, and customer, engineering, and LLM-based feedback loops for continuous improvement. We have adopted a platform approach that leverages common code across multiple projects, together with in-source and open-source usage and contributions.
At IBM TLS, our goal is to leverage insights from across IBM and support other customer-facing teams to supply best practices and implementation insights to clients on their AI journey.
Watch the webinar “IBM TLS + AI – Introducing the subsequent generation of support.”
Optimize your IT infrastructure with TLS
