The Deloitte AI Institute has published the third quarterly edition of its State of Generative AI in the Enterprise report, revealing the current landscape of Gen AI adoption and deployment.
The report 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 Gen AI expertise, all are experienced with AI and are piloting or implementing Gen AI in their organizations.
Key findings from the survey include:
- Despite increasing expectations for transformational impact, data, scaling, and risk challenges are limiting options and tempering leadership enthusiasm.
- Generative AI (Gen AI) adoption has reached a critical phase, with two-thirds of respondents (67%) reporting that their organization is increasing its investment in Gen AI due to strong value to date.
- Demonstrating the value of Gen AI 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.
Data is a key focus for AI-savvy leaders, with 75% of organizations increasing their technology investments around data management due to Gen AI. However, as enterprises look to scale, unforeseen roadblocks have been exposed — with data-related issues causing 55% of surveyed organizations to avoid certain Gen AI use cases. Solving for data deficiencies has emerged as a crucial step in addressing the Gen AI-specific demands of data architectures. To modernise 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 says the report. This involves minimising risks without being too risk-averse.
Although respondents recognised that managing Gen AI risk is critical, three of the top four reported barriers to successful Gen AI deployment are risk-related, including worries about regulatory compliance (36%); difficulty managing risks (30%); and lack of a governance model (29%). Driving these concerns are likely to be risks specific to Gen AI, such as 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 Gen AI tools and applications (51%); monitoring regulatory requirements and ensuring compliance (49%); and conducting internal audits/testing on Gen AI tools and applications (43%).
Survey respondents say that while their senior executives and board members are still intrigued by Gen AI, 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 Gen AI projects with the most potential to create value is the goal, many Gen AI 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 Gen AI experiments fully into production.
