Read more: Visit website The generative AI party is still raging. This zeitgeist has rocked the business world daily in a million ways, and the ground is still shifting. Now, four months into 2024, we're starting to see businesses, particularly those with rarified pragmatic brands, starting to demand evidence of value, of the path to the true ROI derived from AI. As pragmatic voices for value rise, how do thoughtful business leaders respond?
Our survey found that generative AI is already impacting the achievement of organizational goals at 80% of organizations. What led the way, as the #2 and #3 use cases, were analytics—both the creation of and the synthesis of new insights for the organization. These use cases trailed only content generation in terms of embrace.
What makes analytics and generative AI such a potent combination? To explore that, let's get started by diving into what key challenges generative AI solves for, how it works, where it can be applied to maximize the value of data and analytics, and why generative AI requires governance for success.
Companies have long recognized the benefits of using data and analytics to improve revenue performance, manage costs, and mitigate risks. Yet achieving data-driven decision-making at scale often becomes a slow, painful, and ineffective exercise, due to three key challenges.
First, there aren't enough experts in data science, AI, and analytics to deliver the breadth of insights needed across all aspects of business.
Second, enterprises are often hampered by legacy and siloed systems that make it impossible to know where data lives, how to access it, and how to work with it.
Third, even as we struggle with the first two challenges, data continues to grow in complexity and volume, making it much more difficult to use. Combined with a lack of robust governance policies, enterprises are then faced with poor data quality that can't be trusted for decisions.
Generative AI presents two massive opportunities to tackle these challenges by improving the usability and efficacy of enterprise analytics tools.
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