ROI of AI case studies
- 78% of organizations will use AI in at least one business function this year.
- Only 25% deliver the expected ROI (Return on Investment). Moreover, only 16% scale throughout a business enterprise
Peter Drucker’s statement, “If you can’t measure it, you can’t manage it,” is a powerful and frequently cited principle in business management. Maybe that’s because Peter also said, “What gets measured, gets improved.”
75% of businesses won’t see a return with AI. So your business isn’t one of them. Here are case studies of successful ones. Moreover, the case studies show that measuring results is why they can manage and sustain success.
ROI of AI case studies – AstraZeneca, American Express, and Bank of America
- ASTRAZENICA: Knew early stages of drug discovery—especially identifying new targets—are typically slow and resource-intensive. This led to deploying an AI agent that rapidly identified potential treatments for chronic kidney disease. This resulted in: 1) Time required for discovery reduced by 70%, and 2) fast-tracking of drugs for clinical development.
- AMERICAN EXPRESS: Was struggling to keep up with the sheer volume of customer inquiries and transactions. By implementing an AI-powered chatbot, Amex was able to automate a significant portion of its customer service interactions, resulting in a 25% reduction in customer service costs. Moreover, the chatbot’s 24/7 availability enabled the company to respond to customer queries more quickly, leading to a 10% increase in customer satisfaction.
- BANK OF AMERICA: With millions of customers, manually managing support requests and transaction processing was unsustainable. Erica, a virtual AI assistant, was launched to handle financial queries, detect fraud, and execute transactions via voice and text interfaces. She achieved: 1) Over 1 billion interactions completed and 2) a 17% decrease in call center load.
ROI of AI case studies – General Mills, H&M, Mass General, and PayPal
- GENERAL MILLS: The food industry giant reduced transportation costs and boosted customer service levels by using AI in its logistics planning, CFO Kofi Bruce said. AI models assess more than 5,000 daily shipments from plants to warehouses, leading to more than $20 million in savings since the 2024 fiscal year. General Mills predicts real-time performance data in manufacturing will produce more than $50 million in waste reduction this year.
- H&M: Faced high cart abandonment rates and slow customer response times, leading to lost sales opportunities. The company implemented an AI agent capable of offering personalized product recommendations, addressing frequently asked questions, and guiding customers through purchasing. The results were: 1) 70% of customer queries resolved autonomously, 2) 25% increase in conversion rates during chatbot interactions, and 3) 3× faster response and resolution time.
- MASS GENERAL: Physicians were overwhelmed by clinical documentation, reducing the time for direct patient care. The healthcare system deployed an AI agent that automates note-taking and updates to electronic health records (EHRs). The results included a 60% reduction in time spent on clinical documentation and increased physician-patient face time.
- PAYPAL: PayPal faced significant challenges in maintaining robust cybersecurity and fraud prevention measures while handling massive transaction volumes and sensitive financial data. The company aimed to leverage AI to adapt quickly to changing fraud patterns and protect customers more effectively. Creating rapidly adaptable deep learning models that can be trained and deployed within 2–3 weeks. Utilizing their vast data resources (over 200 petabytes of payment data) to power AI models. For Q2 2023, PayPal reported $7.3 billion in revenue, up 7% year-over-year. The company achieved an 11% reduction in losses through improved risk management.
ROI of AI case studies – Siemens, Unilever, and Walmart
- SIEMENS: Due to inefficient production planning and scheduling, Siemens faced challenges in its manufacturing process. By leveraging AI-powered automation, Siemens optimized its production planning and scheduling, resulting in a 15% reduction in production time and a 12% decrease in production costs. Additionally, the AI system enabled Siemens to identify and mitigate potential bottlenecks, leading to a 99.5% on-time delivery rate.
- UNILEVER: Was seeking to improve the efficiency of its supply chain operations. By implementing an AI-powered automation solution, Unilever could predict and prevent stockouts, reducing inventory costs by 10%. The AI system also enabled the company to optimize its logistics and transportation operations, resulting in a 7% reduction in transportation costs.
- WALMART struggled with overstocking, stockouts, and the inefficiency of manual inventory audits. So, they deployed a store-floor robot powered by AI agents to monitor shelf inventory and trigger restocking decisions. There was: 1) a 35% reduction in excess inventory and 2) a 15% improvement in inventory accuracy.
Do these case studies convince you that any AI initiative you’re doing or considering is worth measuring to manage?
