The Deloitte AI Institute™ unveiled the third quarterly edition of its State of Generative AI in the Enterprise report, revealing the current landscape of Gen AI adoption and deployment and how organisations are overcoming barriers to create value at scale.

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 organisations.

Key takeaways:
•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 their organisation 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 organisations are seeking efficiency and productivity improvements, yet only 38% are tracking changes in employee productivity.

Deloitte’s Lead Advisory Partner in Jersey, Adam Cichocki, said: “Our latest 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. Innovation was a topic that Simeon Moss and Emma Shirreffs presented on at the recent IoD Jersey’s ‘AI Powered Productivity, Strategising for Success’ event sponsored by Deloitte, citing it as one of the main catalysts for business growth in the world of Generative AI. The latest survey results show that there is immense potential and versatility of this transformative technology.”

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

Data is taking center stage for AI-savvy leaders, with 75% of organisations increasing their technology investments around data management due to Gen AI. However, as enterprises look to scale, unforeseen roadblocks were exposed— with data-related issues causing 55% of surveyed organisations 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, organisations 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 — minimising risk 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%). Likely driving these concerns are risks specific to Gen AI, like model bias, hallucinations, novel privacy concerns, trust, and protecting new attack surfaces. To help build trust and ensure responsible use, organisations are working to build new guardrails and oversight capabilities. The top actions organisations 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%).

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

While surveyed organisations are beginning to scale past proof-of-concept, 41% have struggled to define and measure the exact impacts of their Gen AI efforts and only 16% have produced regular reports for the CFO about the value being created with Gen AI. 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, organisations are using specific KPIs for evaluating Gen AI performance (48%); building a framework for evaluating Gen AI investments (38%); and tracking changes in employee productivity (38%).

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 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 organisation has moved 30% or fewer of their Gen AI experiments fully into production.

Deloitte are committed to supporting organisations on their AI journeys. We have a wealth of resources available, including Board engagement, AI Labs, and scalable delivery capability from proof of concept to digital transformation.

To find out more, contact one of our experts – Adam Cichocki, Simeon Moss, Emma Shirreffs or email: UKIandG@deloitte.co.uk

ENDS

Notes to editors:

About “The State of Generative AI in the Enterprise” research.

This is the third in a series of quarterly surveys intended to track the adoption of Gen AI in the enterprise. This research builds from Deloitte’s previous “State of AI in the Enterprise” report which has been running for six years. This wave of the survey, conducted between May and June 2024, connected with 2,770 AI-savvy business and technology leaders directly involved in piloting or implementing Generative AI at major organisations across 14 countries and six industries: consumer; energy, resources, and industrials; financial services; life sciences and health care; technology, media and telecom; and government and public services.

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