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GenAl: Powering Enterprise Transformation Through Trust

DataQuest

|

May 2024

Enterprises are rapidly moving beyond GenAI experimentation and seeking to scale its implementation for real business impact. This requires a data-driven shift in how work is done to unlock GenAI's full potential.

- Prabhu Ram

GenAl: Powering Enterprise Transformation Through Trust

Over the past year, Generative Artificial Intelligence (GenAI) adoption in the enterprise focus has moved from experimentation to achieving significant and scalable and GenAI implementation. Enterprises are eager to embrace GenAI, spearhead innovation, and unlock opportunities at scale. While launching GenAI pilots is straightforward, scaling them to deliver substantial value remains a daunting challenge. This necessitates a fundamental shift in how work is actually done. This data-driven and customer-centric approach is precisely where GenAI shines.

Our ongoing research at CyberMedia Research (CMR) highlights the significant potential of GenAI in enabling enterprises with the development of customer-centric products (60%), data-driven decision-making (59%), and enhanced customer experience (47%). These findings paint a compelling picture on how GenAI can steer a data-driven and customer-centric enterprise-wide transformation.

As an analyst, I believe GenAI presents a unique opportunity for enterprises to unlock a new era of productivity, personalized customer service, and sustainable growth. However, GenAI represents a paradigm shift for enterprises and is fraught with both potentially tremendous gains as well as significant risks.

My conversations with enterprise leaders, in Asia and beyond, reveal a shared belief: one of the most transformative applications of GenAI lies in delivering transformative customer experiences leveraging AI bots. Large Language Models (LLMs) possess the ability to handle complex inquiries, delivering swift and natural-sounding responses that mimic human interaction.

SO, HOW CAN ENTERPRISES EMBARK ON THEIR GENAI JOURNEY?

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