TRENDING simulate scenarios , enhancing their ability to anticipate and plan for market changes with significant accuracy . According to the report , the implementation of GenAI for analytics has already placed over a third ( 37 %) of early adopters far ahead of their competitors .
The Path to GenAI Success in Analytics
The success of GenAI implementation hinges on key factors : evolving skill sets , fostering strong collaboration between business and data teams , and selecting the right tools to support business strategy .
To achieve this , organizations must establish clear and consistent communication between their business and data teams – ensuring alignment on a common execution strategy .
The majority of early adopters ( 75 %) report strong partnerships and a centralized strategy , putting them in an advantageous position . In contrast , less than half ( 47 %) of planners – companies that haven ’ t yet adopted GenAI but expect to do so – have achieved similar alignment , underscoring the competitive edge that early adopters gain through prioritizing collaboration across the organization .
Both early adopters and planners recognize the importance of key technical skills for creating or customizing generative AI solutions – with data modeling cited as the most critical ( 49 %) by all respondents .
However , a notable difference emerges in their prioritization of natural language processing ( NLP ): many ( 41 %) of the early adopters view NLP as a top priority , compared to just a limited share ( 28 %) of planners . This divergence suggests that early adopters , having already deployed the technology , understand NLP ’ s potential to accelerate data-driven decisionmaking , positioning them to better attract and develop talent for effective use of GenAI .
The findings of the report also highlight the value of choosing the right tools and collaborating with external experts to enhance business outcomes .
Over half ( 52 %) of successful early adopters are leveraging third-party GenAI tools for analytics , compared with a smaller share ( 32 %) of planners . By relying on strategic partnerships and external expertise , early adopters are optimizing their resources , while minimizing the time and effort required from their internal teams as they scale their deployments .
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