Deloitte Survey: Despite Growing Investment, Data and Risk Hinder Generative AI Scaling

Key takeaways

• Generative AI (GenAI) adoption has reached a critical phase, with two-thirds of respondents (67%) reporting their organization is increasing its investment in GenAI due to strong value to date.
• Despite increasing expectations for transformational impact, data, scaling and risk challenges are limiting options and tempering leadership enthusiasm.
• Demonstrating the value of GenAI deployments to the C-suite will be critical for continued investment as a majority (54%) of organizations are seeking efficiency and productivity improvements, yet only 38% are tracking changes in employee productivity.

Why this matters
The Deloitte AI Institute™ today unveiled the third quarterly edition of its State of Generative AI in the Enterprise report, revealing the current landscape of GenAI adoption and deployment and how organizations are overcoming barriers to create value at scale. “The State of Generative AI in the Enterprise: Now decides Next,” is based on a survey of 2,770 director- to C-suite-level respondents across 14 countries. While respondents have a range of self-reported levels of Generative AI expertise, all are experienced with AI and are piloting or implementing Generative AI in their organizations.

Also Read: AiThority Interview with Dounia Senawi, Chief Commercial Officer, Deloitte Consulting LLP

Key quotes
“As promising experiments and use cases begin to pay off, it’s clear that 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. Our Q3 survey has revealed that now more than ever, change management and deep organizational integration are critical to overcoming barriers, unlocking value and building for the future of GenAI.”  
— Jim Rowan, Applied AI leader and principal, Deloitte Consulting LLP

“We are seeing continued enthusiasm for GenAI across organizations, 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 GenAI 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. The diversity of these value sources underscores the immense potential and versatility of this transformative technology.”
— Costi Perricos, Generative AI leader, Deloitte Global

Excitement is being tempered by reality — and value-led use cases will lead to successful scaling

Survey respondents say that while their senior executives and board members are still intrigued by GenAI, there are signs of enthusiasm beginning to wane as the “new technology” shine wears off. Interest remains “high” or “very high” among most senior executives (63%) and boards (53%); however, those numbers have declined since the Q1 2024 survey, dropping 11 percentage points and eight percentage points respectively. While selecting and quickly scaling the GenAI projects with the most potential to create value is the goal, many GenAI efforts are still at the pilot or proof-of-concept stage, with a large majority of respondents (68%) saying their organization has moved 30% or fewer of their GenAI experiments fully into production.

Also Read: AiThority Interview with Seema Verma, EVP and GM, Oracle Health and Life Sciences

Executives are zeroed in on data lifecycle management as a foundation for GenAI deployments

Data is taking center stage for AI-savvy leaders, with 75% of organizations increasing their technology investments around data management due to GenAI. However, as enterprises look to scale, unforeseen roadblocks were exposed— with data-related issues causing 55% of surveyed organizations to avoid certain GenAI use cases. Solving for data deficiencies has emerged as a crucial step in addressing the GenAI-specific demands of data architectures. To modernize their data-related capabilities, organizations are enhancing data security (54%); improving data quality practices (48%); and updating data governance frameworks and/or developing new data policies (45%).

Struggles with trust and a shifting regulatory landscape are causing many to walk a tightrope — minimizing risk without being too risk-averse

Although respondents recognized that managing GenAI risk is critical, three of the top four reported barriers to successful GenAI deployment are risk-related, including worries about regulatory compliance (36%); difficulty managing risks (30%); and lack of a governance model (29%). Likely driving these concerns are risks specific to GenAI, like model bias, hallucinations, novel privacy concerns, trust, and protecting new attack surfaces. To help build trust and ensure responsible use, organizations are working to build new guardrails and oversight capabilities. The top actions organizations are taking include establishing a governance framework for using GenAI tools and applications (51%); monitoring regulatory requirements and ensuring compliance (49%); and conducting internal audits/testing on GenAI tools and applications (43%).

Amid continued experimentation there is a growing need to demonstrate the value of GenAI initiatives

While surveyed organizations are beginning to scale past proof-of-concept, 41% have struggled to define and measure the exact impacts of their GenAI efforts and only 16% have produced regular reports for the CFO about the value being created with GenAI. As applications and use cases mature, leaders will be less inclined to invest based solely on lofty visions and the fear of missing out — making measurement a critical factor in maintaining interest and support from the C-suite and boardroom. To demonstrate value, organizations are using specific KPIs for evaluating GenAI performance (48%); building a framework for evaluating GenAI investments (38%); and tracking changes in employee productivity (38%).

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