Deloitte AI Institute on Generative AI: 75% Boost in Data Investment as Adoption Hits Key Challenges

The Deloitte AI Institute recently released its third quarterly “State of Generative AI in the Enterprise” report, highlighting the current trends in Generative AI (GenAI) adoption and the challenges organizations face in scaling its deployment.

The report, titled “The State of Generative AI in the Enterprise: Now Decides Next,” draws from a survey of 2,770 senior leaders, ranging from directors to C-suite executives across 14 countries. Despite varying levels of GenAI expertise, all respondents have hands-on experience with AI and are actively piloting or implementing GenAI within their organizations.

Jim Rowan, the Applied AI leader at Deloitte Consulting LLP, indicated that the survey reflects a critical juncture for GenAI. While initial experiments and use cases have started to deliver results, organizations now face significant challenges, including data quality issues, high investment costs, difficulties in effective measurement, and the complexities of an evolving regulatory environment. Rowan emphasized that as these obstacles emerge, effective change management and deep organizational integration are becoming increasingly essential for unlocking GenAI’s full potential.

The survey findings reveal that although senior executives and board members remain interested in GenAI, their enthusiasm is waning as the initial excitement fades. Interest among senior executives remains high (63%) and boards (53%), but these figures have declined since the first quarter of 2024, dropping by 11 and 8 percentage points, respectively. Many organizations are still in the early stages of GenAI implementation, with the majority (68%) reporting that only 30% or fewer of their GenAI projects have moved beyond the pilot phase.

Data management has become a critical focus, with 75% of organizations increasing their technology investments in this area due to GenAI. However, as companies attempt to scale their GenAI initiatives, data-related challenges have emerged, with 55% of respondents indicating they have avoided certain GenAI use cases due to data deficiencies. To address these challenges, organizations are enhancing data security (54%), improving data quality (48%), and updating governance frameworks or creating new data policies (45%).

Risk management has also surfaced as a major concern, with three of the top four barriers to GenAI deployment being risk-related. These include regulatory compliance concerns (36%), difficulties in managing risks (30%), and the absence of a governance model (29%). These concerns are driven by GenAI-specific risks such as model bias, hallucinations, privacy issues, trust, and the protection of new attack surfaces. To mitigate these risks, organizations are establishing governance frameworks (51%), monitoring regulatory requirements (49%), and conducting internal audits of GenAI tools (43%).

While many organizations are progressing beyond the proof-of-concept stages, 41% are struggling to quantify the impact of their GenAI efforts, and only 16% regularly report the value generated to their CFOs. As GenAI use cases mature, leaders are increasingly focusing on concrete results rather than investing based on fear of missing out. To demonstrate value, organizations are implementing specific KPIs for GenAI performance (48%), building frameworks to evaluate GenAI investments (38%), and tracking changes in employee productivity (38%).

This report is the third in a series of quarterly surveys tracking GenAI adoption in the enterprise. It builds on Deloitte’s longstanding “State of AI in the Enterprise” research, which has been ongoing for six years. The latest survey, conducted between May and June 2024, includes insights from business and technology leaders in six industries across 14 countries: consumer, energy, resources, and industrials; financial services; life sciences and healthcare; technology, media, and telecommunications; and government and public services.

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