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The State of Generative AI in the Enterprise

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.

Download the Q4 Report

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.

Explore the quarterly series

Explore findings from the past quarters now—and stay tuned for what’s next

Quarter 4: July - Sept. 2024

See how far organizations came in 2024 and where things are headed in 2025.

Quarter 3: May-June. 2024

The Q3 edition of the series - 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

Quarter 2: Jan-Feb. 2024

It’s time to go from pilots and proofs of concept to large-scale deployment. The Q2 report in the series, Getting Real About Generative AI, explores how organizations are getting down to the work of turning potential into reality.

Quarter 1: Oct-Dec. 2023

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

Looking back at 2024

As a whole, our now decides next 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.

Setting pace to achieve RoI

There is a speed limit. GenAI is advancing at incredible speed, but most organizations are setting their own pace to achieving ROI with AI.

Spotlight on 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.

Scaling top use cases

IT is the function with the most advanced initiatives, followed by operations, marketing, customer service and cybersecurity.

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.

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.

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?

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.

Are some use cases showing more promise?

Are advanced GenAI initiatives meeting expectations?

How long will it take to resolve challenges?

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.

Future forward with GenAI | Optimize for Organizational Value

Costi Perricos, Generative AI Business Leader at Deloitte Global, and Clare Harding, Chief Innovation Officer at Deloitte Global talk about the recently released fourth wave of Deloitte's State of GenAI in the Enterprise quarterly survey, delving into key insights and strategies organizations can use to address barriers to scaling GenAI.

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Looking ahead: AI scaling and agentic AI

We began our exploration of now decides next 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. Now, you decide what’s next. 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.