To understand where you're going, it's helpful to consider where you've been. Artificial intelligence (AI) is the transformative technology of our era and the next step in the evolution of cognition. Realizing the potential, organizations are in the thick of adoption and innovation. It is in the boardrooms, back offices, manufacturing plants, brick-and-mortar stores, and across the marketplace that a big part of the AI story is unfolding. The reflections and views of business leaders are revealing.
Since 2017, the Deloitte AI Institute has conducted surveys with almost 3,000 executives annually to understand their organizations' AI journeys. The results, offered in the annual State of AI in the Enterprise reports, chronicle the views and lessons learned from organizations using AI, from the most boldly innovative to the new and cautious entrants.
Looking across several years of business user impressions reveals the trajectory of our story with AI and illuminates where we may be heading next. Let's look at multiyear trends on the topics of AI's transformative potential, the investments and changes it requires, and the risks and complexity that result.
Turning the page on the next chapter
Today, investment continues with as much vigor as years prior, and the challenges in accessing talent, technology, transformed processes, and risk mitigation persist. Ongoing market surveys reveal that while companies are not shying away from AI investment, ROI is lagging. Whereas five years ago many business leaders felt certain that AI transformation would be as rapid as it is powerful, today, there is a more sober appreciation that simply accessing the technology is not enough. The alignment of people, processes, and technologies involved in AI deployment requires a methodical and inspiring approach to adoption.
We are at an inflection point with AI, shifting from the age of adoption into the age of value. The technology is mature, businesses have made years of investments and learned hard lessons, and now comes the creative, studious work of pursuing the greatest potential value AI has to offer. This can mean focusing on use cases that can fuel and fund other transformations, targeting investment in leadership positions, and fully implementing MLOps processes across the enterprise.
Each business will find its own mix of strategies and tactics that enable the greatest value AI has to offer. There are sure to be discoveries, as well as setbacks, but our story with AI is far from over.
Few organizations are completely AI-fueled today, but a significant and growing percentage are displaying the behaviors that will get them there. What can we learn from the practices of leading-edge organizations?
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