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What is the role of AI in revenue growth management? Infosys Knowledge Institute explains. Read here: infy.com/3TmBdbw. Using a data-driven model powered by AI can help companies arrive at well-considered pricing and price pack architecture decisions, and drive sustainable and profitable revenue growth. #revenuegrowthmanagement #dataandAI #RGM #predictiveanalytics Priyanka Haldipur Rahul Ubgade Infosys Consumer, Retail & Logistics

The role of AI in revenue growth management, as explained by the Infosys Knowledge Institute, is significant. By utilizing a data-driven model powered by AI, companies can make informed pricing and price pack architecture decisions. This approach helps drive sustainable and profitable revenue growth. The use of predictive analytics in revenue growth management is particularly highlighted, showcasing its potential to optimize strategies and outcomes in the consumer, retail, and logistics sectors. To learn more, check out the article at : infy.com/3TmBdbw. #revenuegrowthmanagement #dataandAI #RGM #predictiveanalytics

“Data democratisation empowers employees to access and utilise data without needing technical expertise or support, improving both data literacy and the ability to solve problems independently among the workforces,” states Rajan Padmanabhan of Infosys, in this article: bit.ly/4fhgRIB. Read on as he delves into how #DataDemocratisation is transforming business operations, fostering innovation, and enabling enterprises to leverage #AI at scale.

Sunil Senan of Infosys shares his expertise! Learn how AI-first business models go beyond hype to create measurable value for all stakeholders. Read more: https://bit.ly/3WpmcY1 #InfosysTopaz #BeingAIfirst #generativeAI

Hexaware helped a global #CRO tackle performance complexities and manual dependencies by migrating to #Databricks and automating #data processes. This transformation led to significant effort savings, accelerated analysis, and empowered end-users. Read how our innovative approach modernized their data infrastructure and enabled cutting-edge #AI and #ML development. https://bit.ly/4cgNsNB #clinicalresearch #casestudy

The tide is turning to take the #manufacturing industry up an innovative notch with more data, more #AI, and more modernized technical processes to keep operations relevant to the rising workforce generation. 🏭 To prepare your #Salesforce org for the future, you must first clean up and address the past. A full industry-specific org optimization takes care of both past oversights and paves the way forward for new innovations not yet leveraged. In this article, we’ll examine the three main trends pushing business leaders in manufacturing to conduct comprehensive Salesforce org optimizations in their businesses. Read more here: https://lnkd.in/gJuBC4ym Simplus Infosys Alyssa Suchy Amit Kapur Simplus ANZ (an Infosys company) Sunil Malik Steve Seo Surbhi Sharma Lakshmi Kannan Suyash Awasthi Kevin Willemse Grant Moore Pete Lenskold

Sunil Senan of Infosys shares his expertise! Learn how AI-first business models go beyond hype to create measurable value for all stakeholders. Read more: https://bit.ly/3WpmcY1 #InfosysTopaz #BeingAIfirst #generativeAI

At the Q3 Cognizant CMT Chief Data Officer Forum, top Communications, Media & Entertainment, Hi Tech, and Platforms & SaaS data leaders tackled AI’s most pressing challenges, from planning scalable budgets to addressing skills gaps. Discussions highlighted how businesses are shifting toward platform-centric AI investments that focus on long-term outcomes, including efficiency, customer experience, and revenue growth. However, defining the ROI of generative AI projects—particularly in automating tasks like RFPs—remains a hurdle. Key takeaways: • Strategic AI budgeting: Moving beyond project-specific estimates toward platform-wide scalability. • Outcome-based metrics: Tailoring KPIs, such as “Time to Decision,” to align AI use cases with business goals. • Upskilling and governance: Investing in training and governance structures to address rapid demand and reduce inefficiencies. • Data’s evolving role: Reinventing data platforms to support scalable, AI-driven solutions while balancing build vs. buy decisions for tools. Cognizant fosters these valuable conversations to empower businesses navigating AI’s potential and challenges. Explore the full insights here: https://bit.ly/3Zg5yLH #GenerativeAI #DigitalTransformation #DataLeadership #BeCognizant #Innovation

At the Q3 Cognizant CMT Chief Data Officer Forum, top Communications, Media & Entertainment, Hi Tech, and Platforms & SaaS data leaders tackled AI’s most pressing challenges, from planning scalable budgets to addressing skills gaps. Discussions highlighted how businesses are shifting toward platform-centric AI investments that focus on long-term outcomes, including efficiency, customer experience, and revenue growth. However, defining the ROI of generative AI projects—particularly in automating tasks like RFPs—remains a hurdle. Key takeaways: • Strategic AI budgeting: Moving beyond project-specific estimates toward platform-wide scalability. • Outcome-based metrics: Tailoring KPIs, such as “Time to Decision,” to align AI use cases with business goals. • Upskilling and governance: Investing in training and governance structures to address rapid demand and reduce inefficiencies. • Data’s evolving role: Reinventing data platforms to support scalable, AI-driven solutions while balancing build vs. buy decisions for tools. Cognizant fosters these valuable conversations to empower businesses navigating AI’s potential and challenges. Explore the full insights here: https://bit.ly/3Zg5yLH #GenerativeAI #DigitalTransformation #DataLeadership #BeCognizant #Innovation

At the Q3 Cognizant CMT Chief Data Officer Forum, top Communications, Media & Entertainment, Hi Tech, and Platforms & SaaS data leaders tackled AI’s most pressing challenges, from planning scalable budgets to addressing skills gaps. Discussions highlighted how businesses are shifting toward platform-centric AI investments that focus on long-term outcomes, including efficiency, customer experience, and revenue growth. However, defining the ROI of generative AI projects—particularly in automating tasks like RFPs—remains a hurdle. Key takeaways: • Strategic AI budgeting: Moving beyond project-specific estimates toward platform-wide scalability. • Outcome-based metrics: Tailoring KPIs, such as “Time to Decision,” to align AI use cases with business goals. • Upskilling and governance: Investing in training and governance structures to address rapid demand and reduce inefficiencies. • Data’s evolving role: Reinventing data platforms to support scalable, AI-driven solutions while balancing build vs. buy decisions for tools. Cognizant fosters these valuable conversations to empower businesses navigating AI’s potential and challenges. Explore the full insights here: https://bit.ly/3Zg5yLH #GenerativeAI #DigitalTransformation #DataLeadership #BeCognizant #Innovation