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- Generative AI Adoption and Productivity Improvements: The adoption of generative AI capabilities within ServiceNow’s platform is highlighted as a key driver for increasing productivity. This includes automating tasks and processes that traditionally required manual intervention, thereby significantly enhancing operational efficiency for ServiceNow’s customers.
- Developer Productivity with Text to Code: ServiceNow’s developers leveraging text to code capabilities to generate high-quality code by simply describing the type of code they want. This innovation has reportedly increased developer innovation speed by 52%, showcasing a substantial productivity boost within the software development process.
- Field Service Management Efficiency: Now Assist for field service management is mentioned as a tool that reduces cost and increases revenue by helping technicians complete jobs in a single visit. This includes identifying necessary equipment and providing repair recommendations quickly, which enhances the productivity of field service operations.
- Automated Document Generation in Clinical Trials: The use of generative AI to automate document generation in compliance with regulatory protocols for clinical trials is discussed as a potential for drastically reducing cycle times and improving the efficiency of clinical trial processes.
- Sales and Marketing Efficiency: The increase in sales and marketing efficiency is touched upon, with specific mention of ServiceNow’s ability to scale and leverage its sales force more effectively, implying that the company is achieving more with a proportionally smaller increase in headcount.
- Public Sector AI Adoption: While it’s early days, the adoption of generative AI within the public sector is anticipated to follow, suggesting that productivity gains seen in other industries could also benefit government agencies as they begin to integrate these technologies.
- Back Office Functions Automation: The automation of back-office functions using ServiceNow’s own platform is highlighted, demonstrating internal productivity gains by automating processes that traditionally required significant manual effort.