Moving from potential to performance
<b>New Q3 insights:</b> Explore the latest findings from the Deloitte AI Institute’s survey series tracking Generative AI adoption, successes, and challenges throughout 2024.
The State of Generative AI in the Enterprise
Quarter 3 report: May – June 2024
Unpacking GenAI adoption
Investment is increasing, but the clock is ticking to scale and create value. The Q3 edition of The State of Generative AI in the Enterprise series, Moving from potential to performance, reveals how organizations are navigating challenges and measuring value. Two critical areas of focus are data foundations and governance, risk, and compliance.
View Q3 report
Quarter 2: Jan. – Feb. 2024
Scaling for tangible results
It’s time to go from pilots and proofs of concept to large-scale deployment. The second report in our The State of Generative AI in the Enterprise series, Getting real about Generative AI, explores how organizations are getting down to the work of turning potential into reality.
View Q2 report
Quarter 1: Oct. – Dec. 2023
Now decides next
In our Q1 report, we found that expectations of GenAI remain high, but many leaders are feeling pressure to quickly realize value while managing risks. The greatest areas of concern include governance, talent, and the potential for economic inequality.
View Q1 report
Insights from the leading edge
of GenAI adoption
The defining time for GenAI is now. How we train, apply, govern and work with GenAI will determine its impact. The State of Generative AI in the Enterprise is a survey series tracking trends in use cases, sentiment, adoption, and challenges throughout 2024. Explore findings from the past three quarters now—and stay tuned for what’s next.
Subscribe for updatesDiscovering new benefits
Two-thirds of organizations are increasing investments after seeing strong value to date. A large percentage (42%) report efficiency, productivity, and cost reduction as their single, most important benefit achieved. However, most respondents (58%) reported a range of other benefits—highlighting the versatility of GenAI in the enterprise.
Measuring results
While 41% of organizations struggle to define and measure impact, others are building evaluation frameworks. Developing specific, standardized ways of assessing and communicating value—especially given the diversity of new benefits observed—is essential for progress.
Identifying opportunity
Most organizations aren’t getting a high percentage of experiments off the ground, stalling at pilot or proof of concept. These are the top areas where organizations are scaling GenAI in the enterprise.
Facilitating GenAI adoption
In addition to investing in data management, organizations that report feeling prepared for GenAI adoption are supporting scale through training, talent, and cloud investments.
Struggling with data
Over half of organizations reported they are avoiding certain GenAI use cases because of data-related issues such as data quality and accuracy, intellectual property, and usage rights. Some can’t even get started due to data deficiencies. These are their top concerns.
Modernizing data foundations
Organizations are taking action—75% have increased investments in data life cycle management, turning their data foundations into springboards for scaling GenAI successfully. Here's what else they're doing.
Navigating obstacles
The biggest barriers to GenAI adoption revolve around compliance, risk, and governance. Leaders report feeling ill-prepared on governance and risk as they work to address evolving challenges across accuracy, privacy, and security.
Mitigating risks
Organizations are increasingly basing decisions on risk, selecting effectively managing risks as the second-most reported way to drive the most value for GenAI initiatives. From a regulation standpoint, top preparatory actions include forecasting, monitoring, and working with external partners.
Push your way past proof-of-concept.
Learn how organizations are scaling Generative AI in our Q3 report.
View Q3 report
Looking ahead for Generative AI adoption
Our research reveals five next steps to help organizations set a course for scaling GenAI in the enterprise.
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Reinvest cost and capacity savings in other areas where organizations are seeing GenAI-driven value, such as improving innovation, products and services, customer relationships, and revenue growth.
Strong processes like governance, data management, and workforce development will speed the creation of new use cases as industries move to more differentiating custom domain and small language models.
Success requires high-quality, ethically sound data. Prioritize internal and external data management, improve foundational practices like security and labeling, and strengthen your data ecosystem.
Executives must stay engaged as cross-functional teams lead risk mitigation. One executive should oversee risk and define an approach to using more sensitive data in pursuit of more valuable use cases.
Qualitative metrics may suffice at proof-of-concept, but you need quantitative metrics to tangibly measure and communicate value once you scale. Expect oversight and cost pressures to increase over time.
Generative AI insights and solutions from across Deloitte
About this report
Now decides next: The state of generative AI in the enterprise is a quarterly report series by the Deloitte AI Institute exploring how actions taken now will guide Gen AI adoption and impact.
Methodology
To help leaders in business, technology and the public sector track the rapid pace of generative AI change and adoption within the enterprise, Deloitte is conducting a series of quarterly pulse surveys. The first wave of our survey was fielded to more than 2,800 Director to C-suite level respondents across six industries and 16 countries between October 12 and December 5, 2023.
See previous waves of this series in our archive.
View archiveLooking for Generative AI insight tailored to your business? Let's talk.
Source: Deloitte’s State of Generative AI in the Enterprise Q3 report
