Becoming an AI-fueled organisation has been saved
Becoming an AI-fueled organisation
State of AI in the enterprise, 4th edition
Few organisations are completely AI-fueled today, but a significant and growing percentage are displaying the behaviours that will get them there. What can we learn from the practices of leading-edge organisations?
Our AI-fueled future: The pathway is clear
We’re rapidly approaching the day when AI is expected to independently and reliably illuminate creative and strategic opportunity, releasing us from the confines of our limited perspectives. As we advance further into that AI-fueled future, organisations that dedicate their imagination and energy to laying the foundations now could be rewarded manyfold.
Who is leading the AI marketing today?
AI-fueled organisations leverage data as an asset and scale human-centered AI across all core business processes. They use rapid, data-driven decision-making to enhance workforce and customer experiences. Our research uncovered four types of companies that are progressing toward this ideal.
Explore research findings
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794 executives | 28% total survey population
Transforming but not fully transformed, this group has identified and largely adopted leading practices associated with the strongest AI outcomes. They average 5.9 out of 10 possible full-scale deployments of different types of AI applications, and 6.8 out of 17 possible outcomes achieved to a high degree.
753 executives | 26% total survey population
Pathseekers have adopted capabilities and behaviours that are leading to success, but on fewer initiatives. In other words, they are making the right moves but have not scaled to the same degree as Transformers. They average 1.9 out of 10 possible full-scale deployments of different types of AI applications, and 6.2 out of 17 possible outcomes achieved to a high degree.
496 executives | 17% total survey population
A significant amount of development and deployment activity characterises this group; however, they haven’t adopted enough leading practices to help them effectively achieve more meaningful outcomes. They average 5.6 out of 10 possible full-scale deployments of different types of AI applications, and 1.4 out of 17 possible outcomes achieved to a high degree.
832 executives | 23% total survey population
Getting a late start in building AI capabilities seems to characterise this group; they are the least likely to demonstrate leading practice behaviours. They average 1.6 out of 10 possible full-scale deployments of different types of AI applications, and 1 out of 17 possible outcomes achieved to a high degree.
About the survey
We surveyed 2,875 executives from 11 top economies who have purview into AI strategies and investments within their organizations. We asked them about a wide variety of behaviors—from their overarching AI strategy and leadership, to their technology and data approaches, and how they’re helping their workforce operationalize AI. Then, to understand which behaviors lead to the greatest outcomes, we analyzed the survey responses based on how many types of AI applications a company has deployed full scale and the number of outcomes achieved to a high degree.