2024 year-end Generative AI report
Explore the complete findings—including Q4 results—from the Deloitte AI Institute’s survey series tracking Generative AI investments, successes, and challenges throughout 2024.
The State of Generative AI in the Enterprise
Generating a new future
The Q4 conclusion of our 2024 The State of Generative AI in the Enterprise series reveals that no matter how quickly GenAI advances, organizational change only happens so fast. ROI with AI is encouraging, regulation and risk loom large, and agentic AI is on the rise—but businesses are setting their own pace on the path to value.
View Q4 reportUnpacking GenAI adoption
Investment is increasing, but the clock is ticking to create value. The Q3 edition of The State of Generative AI in the Enterprise, Moving from potential to performance, reveals how organizations are navigating challenges and measuring value, focusing on two areas critical to scaling: data and governance, risk and compliance.
View Q3 reportScaling for tangible results
It’s time to go from pilots and proofs of concept to large-scale deployment. The Q2 report of our The State of Generative AI in the Enterprise series, Getting real about Generative AI, explores how organizations are getting down to the work of turning potential into reality.
View Q2 reportNow decides next
In our Q1 report, we found that expectations of Generative AI remain high, but many leaders are feeling pressure to quickly realize value while managing risks. The greatest areas of concern include governance, talent, and potential for economic inequality.
View Q1 reportLooking back at 2024
As a whole, our <i>Now decides next</i> series illustrates how Generative AI attitudes and innovation have evolved throughout the year. As with previous transformational technologies, the initial excitement and hype has gradually given way to a mindset of positive pragmatism.
From the speed of technology to the speed of organizations
There is a speed limit. GenAI is advancing at incredible speed, but most organizations are setting their own pace to achieving ROI with AI.
From specialized talent barriers to regulation and risk
Barriers are evolving. The uneven pace of change has put a spotlight on regulation and risk, which have emerged as the top barrier to development and deployment—increasing 10 percentage points from Q1 to Q4.
From experimentation to scaling top use cases
IT is the function with the most advanced initiatives, followed by operations, marketing, customer service and cybersecurity.
From technology catch-up to competitive differentiation
The focus is on core business value. A strategic shift is emerging as organizations focus their deepest deployments on areas critical to industry success.
From cheerleaders to champions
C-suite leaders (CxOs) express a rosier view of Generative AI investments—and how easy it is to address barriers. It’s critical that they direct that enthusiasm to removing barriers to scaling.
From Generative AI to agentic AI
Agentic AI is here. Agentic AI is gaining interest as a breakthrough innovation that could unlock the full potential of GenAI, but it’s not a silver bullet and all the broad challenges facing GenAI still apply.
Explore insights from our Generative AI report
In the final installment of the 2024 series, we asked leaders across a variety of industries several overarching questions about Generative AI investment, scaling, and value realization.
What is the state of GenAI experimentation?
Excitement remains high but has evolved into a feeling of positive pragmatism. More organizations are dedicating a greater portion of their budgets to GenAI than earlier in the year, but they're focusing their efforts and taking their time: Most are pursuing 20 or fewer experiments or proofs of concept (POCs) and over two-thirds said that 30% or fewer of their experiments will be fully scaled in the next three to six months.
% of experiments/POCs fully scaled in three to six months
Are some use cases showing more promise?
The most advanced initiatives target IT (28%), operations (11%), marketing (10%), and customer service (8%)—but this spread varies by industry in a way that suggests a shift toward competitive differentiation: Beyond IT, organizations overwhelmingly focus their deepest deployments on functions uniquely critical to success in their industries.
Top functions of most-advanced (scaled) GenAI initiatives
Real-world results: Learn how a global consumer company is increasing productivity and sales while reducing media costs through GenAI. View case study
Are advanced GenAI initiatives meeting expectations?
Almost all organizations report measurable ROI with GenAI in their most advanced initiatives, and 20% report ROI in excess of 30%. The vast majority (74%) say their most advanced initiative is meeting or exceeding ROI expectations. Cybersecurity initiatives are far more likely to exceed expectations, with 44% delivering ROI above expectations.
% of leaders reporting on ROI expectations
Real-world results: Learn how a bank is using GenAI to triage millions of cybersecurity alerts into fewer than 10 real threats per day. View case study
How long will it take to resolve challenges?
Organizations have learned that Generative AI scaling and value creation is hard work. The majority acknowledge they need at least a year to resolve ROI and adoption challenges such as governance, training, talent, trust, and data issues—and they’re willing to put in the time.
55-70%
need 12+ months to resolve adoption challenges
70%
need 12+ months to resolve ROI challenges
76%
say they'll wait at least 12 months or more before reducing investment if value targets weren't being met
Real-world results: Learn how a tech company is developing GenAI tools to accelerate sales with an eye toward commercialization in the future. View case study
Which technology advances could drive the future?
Among emerging GenAI-related innovations, the three capturing the most attention relate to agentic AI. In fact, more than one in four leaders (26%) say their organizations are already exploring it to a large or very large extent. The vision is for agentic AI to execute tasks reliably by processing multimodal data and coordinating with other AI agents—all while remembering what they’ve done in the past and learning from experience.
Interest in future GenAI-related developments
Case Studies
To build on our quantitative findings, <i>Generating a new future</i> features several case studies sourced directly from leaders on the front lines of GenAI scaling. These examples show how organizations are using GenAI to create value and drive competitive differentiation by applying it to industry- and business-specific challenges.
Looking ahead: AI scaling and agentic AI
We began our exploration of <i>Now decides next</i> in Q1 of 2024, during a frenzied time of Generative AI adoption when decisions in the moment were directly impacting the ability to succeed in the future. <b>Now, <i>you</i> decide what’s next.</b> Every organization is setting its own course to AI scaling, but our research reveals five broad next steps.
C-Suite
C-suite leaders should think about how to redefine their roles around GenAI and lead their organizations forward, ensuring alignment between technical and business executives, managing realistic expectations about timing for success, and showing patience and commitment in the face of uncertainty.
ROI
In our case studies, we found that focusing on a small number of high-impact use cases in proven areas can accelerate ROI with AI, as can layering GenAI on top of existing processes and centralized governance to promote adoption and scalability. Move beyond isolated initiatives and integrate GenAI into increasingly sophisticated and interconnected processes.
Workforce
Workers need more GenAI access and experience—sooner rather than later: Several case studies revealed that resistance to adopting GenAI solutions slowed project timelines. Usually, the resistance stemmed from unfamiliarity with the technologies or from skill and technical gaps.
Agentic AI
Take early steps to help test and build the data management, cybersecurity, and governance capabilities necessary for safe agentic AI applications. Begin by assessing which tasks and workflows are well suited for agentic AI. Map out potential risks and create mitigation plans. Start with low-risk use cases that use noncritical data—with human oversight as a backup.
Managing Uncertainty
While GenAI’s present is filled with great promise, uncertainty hinders progress. Organizations should consider boosting efforts in the areas of foresight, market sensing and scenario planning to help leaders model plausible futures, identify potential blind spots in their strategies, and make more informed decisions.
Generative AI insights and solutions from across Deloitte
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About this series
<em>The State of Generative AI in the Enterprise</em> is a research series by the <a href='https://www2.deloitte.com/us/en/pages/deloitte-analytics/articles/advancing-human-ai-collaboration.html'>Deloitte AI Institute™</a> exploring trends, practices, and challenges in scaling Generative AI.
Methodology
To help leaders in business, technology and the public sector track the rapid pace of generative AI change and adoption within the enterprise, Deloitte is conducting a series of quarterly pulse surveys. The first wave of our survey was fielded to more than 2,800 Director to C-suite level respondents across six industries and 16 countries between October 12 and December 5, 2023.
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Source: Deloitte’s State of Generative AI in the Enterprise Q4 report
