Top Generative AI Use Cases at IBM

According to Armand Ruiz, IBM has completed 1,000+ Generative AI projects in 2023. 

Top use cases include:

▪️ Customer-facing functions and experiences

- Customer service: Empower customers to find solutions with easy, compelling experiences. Automate answers with 95% accuracy

- Marketing: Increase personalization, and improve efficiency across the content supply chain. Reduce content creation costs by up to 40%

- Content creation: ex. enhance digital sports viewing with auto-generative spoken AI commentary. Scale live viewing experiences cost-effectively

- Knowledge worker: Enable higher value work, improve decision making, increase productivity. Reduce 90% of text reading and analysis work

▪️ HR, Finance, and Supply-Chain Functions

- HR automation: Reduce manual work and automate recruiting sourcing and nurturing job candidates. Reduce employee mobility processing time by 50%

- Supply chain: Automate source-to-pay processes, reduce resource needs, and improve cycle times. Reduce cost per invoice by up to 50%

- Planning and analysis: Make smarter decisions, and focus on higher-value tasks with automated workflows and AI. Process planning data up to 80% faster

- Regulatory compliance: Support compliance based on requirements/risks, and proactively respond to regulatory changes. Reduce time spent responding to issues

▪️ IT Development and Operations

- App modernization, migration: Generate code, and tune code generation response in real time. Deliver faster development output

- IT automation: Identify deployment issues, avoid incidents, and optimize application demand to supply. Reduce mean time to repair (MTTR) by 50%

- AIOps: Assure continuous, cost-effective performance and connectivity across applications. Reduce application support tickets by 70%

- Data platform engineering: Redesign the approach for data integration using generative AI. Reduce data integration time by 30%

▪️ Core Business Operations

- Threat management: Reduce incident response times from hours to minutes or seconds. Contain potential threats 8x faster

- Asset management: Optimize critical asset performance and operations while delivering sustainable outcomes. Reduce unplanned downtime by 43%

- Product development: ex. expedite drug discovery by inferring structure with AI from simple molecular representations. Faster and less expensive drug discovery

- Environmental intelligence: Provide intelligence to proactively plan and manage the impact of severe weather and climate. Increase manufacturing output by 25%