Deloitte: Enterprises Face Gen AI Scaling Challenges
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.
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%).
In response, organisations are establishing governance frameworks for Gen AI tools and applications, monitoring regulatory requirements and conducting internal audits on Gen AI tools, aiming to mitigate risks and ensure responsible use of the technology.
Demonstrating value: A crucial challenge
As Gen AI initiatives mature, demonstrating value has become crucial. Forty-one percent of respondents struggle to define and measure the impacts of their Gen AI efforts, with only 16% producing regular CFO reports on Gen AI value creation. To address this, organisations are implementing specific KPIs for evaluating GenAI performance, building frameworks for evaluating Gen AI investments and tracking changes in employee productivity.
Despite these challenges, Gen AI benefits extend beyond efficiency gains. Costi Perricos, Generative AI leader at Deloitte Global, notes: “We are seeing continued enthusiasm for Gen AI across organisations, and leaders are deriving the most value from the technology by deeply embedding it into critical business functions and processes.
“Our research indicates that the top benefits of Gen AI are extending beyond improved efficiency, productivity and cost reduction, with more than half pointing to increased innovation, improved products and services, enhanced customer relationships and other types of value.”
Looking ahead, effective data management, risk mitigation and value demonstration will be crucial in determining the success of enterprise Gen AI initiatives. Jim Rowan concludes: “Our Q3 survey has revealed that now more than ever, change management and deep organisational integration are critical to overcoming barriers, unlocking value and building for the future of Gen AI.”
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