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How can a large organization apply generative AI to unlock business value? Discover how we help enterprises leverage generative AI through our real-world examples.

At Cognizant, we’re helping many of the world’s largest brands to transform, through consulting, modern engineering and a platform-based approach to generative AI at scale. Here are some compelling examples from both our and our partner Microsoft’s sphere:  

  • Faster releases with GitHub Copilot for multinational e-commerce platform. As this company, active on 100+ markets, analyzed the effort spent in development, automation testing and unit testing, it observed that 70 percent of its daily efforts were attributed to coding. The coding complexity heavily impacted the time-to-market. We helped roll out subscription-based GitHub Copilot to all teams involved in coding as an “AI pair programmer”. The tool provides code suggestions for any coding tasks, which, so far, has resulted in a 2x increase in productivity, a 50 percent reduction in rework efforts and a 15 percent effort savings through automated scripting.
  • Generative AI-powered insights for a Fortune 100 company. Our client’s existing data platform was unable to deliver the right level of business value, with GDPR and business rule processing requirements pushing investment demand for the current platform and leaving the client unable to implement any AI/ML solutions efficiently to bring in automation and reduce manual efforts. We implemented a fully automated solution on Microsoft Azure Cloud which accelerated the client’s digital transformation journey, was easily transcended to other customers, and greatly expanded the brand’s ability to launch AI/ML solutions and automation tooling. This resulted in an expected 50 percent year-on-year growth, a 20 percent increase in performance and $7.5M savings over the next five years.
  • Generative AI for regression testing for global insurance leader. Due to a large volume of manual test scripts, this Canada-based insurer saw a need for optimization, test efficiency and lower defect throughput to avoid the long test cycles. It also wanted the transform team to produce higher-value work. Generative AI in the software testing life cycle has led to efficient and effective testing processes with the potential to automate, improve test coverage and enhance the overall quality. Overall, the insurer expects a 40 percent saving in efforts, 35 percent optimized regression testing and 32 percent overall quality assurance cost savings through efficiencies.

Check out other generative AI cases here and learn more by visiting our Generative AI section and Rewire for AI

Mats Johard

Country Manager, Cognizant Sweden

Mats Johard

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