Deloitte research reveals a complex landscape where increased investment in generative AI clashes with scaling challenges and waning executive enthusiasm
Capable of creating human-like text, images and code, generative AI (Gen AI) has sparked a global investment frenzy, with market researchers estimating that the technology could add trillions to the global economy in the coming decade.
However, as organisations pour resources into Gen AI initiatives, they face a complex web of technical and ethical regulatory challenges. Amidst this backdrop of opportunity and uncertainty, Deloitte’s latest quarterly report sheds light on the current state of Gen AI adoption in the enterprise, revealing both progress and persistent hurdles.
The survey, based on responses from 2,770 director to C-suite level executives across 14 countries, shows that while organisations are committing more resources to Gen AI, they are struggling with scaling and demonstrating value.
The report, The State of Generative AI in the Enterprise: Now Decides Next, finds that 67% of respondents are increasing their Gen AI investments due to perceived value. However, this commitment is offset by obstacles including data quality issues, investment costs and regulatory uncertainties.
Jim Rowan, Applied AI leader at Deloitte Consulting LLP, states: “We have arrived at a pivotal moment for Generative AI, balancing leaders’ high expectations with challenges such as data quality, investment costs, effective measurement and an evolving regulatory landscape.”
Waning executive enthusiasm for Gen AI
One of the most striking findings is the decline in enthusiasm among senior executives and board members. Interest remains ‘high’ or ‘very high’ among 63% of senior executives and 53% of board members, down 11 and 8 percentage points respectively since Q1 2024: likely reflecting a growing awareness of the complexities involved in scaling Gen AI initiatives.
We have arrived at a pivotal moment for Generative AI, balancing leaders’ high expectations with challenges such as data quality, investment costs, effective measurement and an evolving regulatory landscape.
Jim Rowan, Applied AI leader, Deloitte Consulting LLP
The transition from pilot to production also remains a significant hurdle. Sixty-eight percent of respondents’ organisations said they have moved 30% or fewer of their Gen AI experiments into full production, highlighting the difficulty of scaling GenAI beyond proof-of-concept stages.
Data management has emerged as a critical factor for successful Gen AI deployments. Seventy-five percent of organisations are increasing their technology investments in data management due to Gen AI, but data-related issues have caused 55% of surveyed organisations to avoid certain Gen AI use cases. To address these challenges, companies are focusing on enhancing data security (54%), improving data quality practices (48%) and updating data governance frameworks (45%).
The regulatory landscape presents additional complexity. Deloitte’s study found the top barriers to successful Gen AI deployment are risk-related, including concerns about regulatory compliance (36%), difficulty managing risks (30%) and lack of a governance model (29%).
