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As enterprises rapidly pivot to incorporate Generative AI (Gen AI) into their operations, they face significant knowledge gaps regarding its integration and application in specific business contexts.
Vijay will guide attendees through the nuances of integrating Gen AI in business, outlining an essential blueprint for developing Gen AI talent that aligns with business functions.
His discussion will also focus on the current trends and burgeoning opportunities in Gen AI. Vijay will also highlight the emerging skills and roles essential in the Gen AI arena, addressing how this technology is influencing various business sectors, including HR. His insights aim to provide a deeper, more nuanced understanding of Gen AI’s transformative role in shaping the future of business.
People Analytics / HR Data Science continues to be an evolving space within the HR function across companies. Most companies have only recently kicked off their People Analytics journey wherein they are trying to get better at descriptive analytics around core foundational HR reporting using various technology tools and platforms.
A very small proportion of companies have a People Analytics arm ready and mature enough to explore & experiment innovative predictive and prescriptive analytics solutions leveraging AI and Gen AI capabilities.
This presentation will look to provide a personal perspective from the speaker on things to likely keep in mind as you ideate, conceptualize, plan, socialize, build, test and scale Gen AI led solutions across HR use cases.
Language Translation capabilities are a fundamental requirement for global companies. For Pfizer, translation requirements range from colleague, patient, and government communications and documents to drug details and packaging.
While Gen AI cannot take the place of costly and time-consuming human review in many highly regulated areas, it can expedite the process and save money for many general corporate users.
This presentation will showcase how we have explored the use of Gen AI in Language Translation through the evaluation of Gen AI against traditional machine translation models, while placing emphasis on preserving the translation memory of company specific acronyms and terminology.
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