Businesses of all sizes around the world are trying to understand generative AI and figure out where it can add value. The good news: Most organizations actually make it work.

According to a new report today from Deloittethe majority of businesses are actually meeting or exceeding their own expectations for return on investment (ROI) from gen AI. The “State of Generative AI Q4” report, based on a survey of 2,773 leaders in 14 countries, highlights the progress and challenges organizations face in their gene AI journeys.

The report shows a significant improvement from first version was released a year ago, where business leaders expressed many concerns. There is also positive progress over the third quarter reportwhich shows that most organizations avoid some gen AI use cases because of data issues.

Despite the longer time to value, nearly three-quarters (74%) of respondents reported that their most advanced gen AI initiatives met or exceeded ROI expectations. Cybersecurity and IT functions lead in terms of ROI and successful scaling.

Key findings include:

• Organizations need at least 12 months to resolve major adoption challenges
• IT, cybersecurity, operations, marketing and customer service showed the strongest adoption and results
• Regulatory compliance has emerged as a major barrier to gen AI deployment
• 78% of respondents expect to increase their overall AI spending in the next financial year

Jim Rowan, head of AI at Deloitte, told VentureBeat that the biggest gains businesses are reporting from using AI are efficiency and cost savings.

“We take time out of everyday tasks and activities and make individuals more efficient,” Rowan said.

The challenge of gen AI moving at the speed of business

Business technology is by definition about stability and stability. These are supposed to be the things that businesses run. For many types of technology, business adoption can take years because organizations must first validate use cases and ROI potential.

While the rapid development of gen AI capabilities has captured the public’s imagination, businesses often move at a much slower pace when it comes to adoption. This disconnect between the rapid pace of AI innovation and the more deliberate nature of enterprise technology rollouts presents a significant challenge.

“Businesses move at the speed of business,” Rowan said. “That plays into a couple of different areas within the report, in terms of scaling questions, risks and regulatory challenges facing organizations across the board.”

This difference in speed is further complicated by the fact that many enterprises still face challenges in the foundation of technology, such as data management and platform modernization. Rowan noted that underlying issues need to be addressed before businesses can fully utilize the potential of generative AI.

Instead of rushing to deploy the latest gen AI tools, Rowan emphasizes the importance of a more measured, strategic approach that focuses on building the necessary infrastructure and cultural readiness. By taking the time to properly integrate gen AI into existing operations and workflows, businesses can ensure that the technology delivers tangible, lasting value, rather than serving as a passing novelty. This patient, deliberate approach, while likely to be slow in the short term, may ultimately prove more effective in driving lasting change.

Where business AI is delivering the greatest ROI today

One of the main areas where businesses are seeing tangible value from AI is in the software development cycle.

According to the report, AI is helping to drive efficiency gains throughout the entire process – from requirements gathering to testing and deployment.

“We see this a ton in the software development life cycle,” Rowan said. “This is why IT is a big, big proponent of this.”

Besides software development, businesses are tapping AI to improve their customer service and contact center operations. By automating certain tasks and interactions, companies can improve efficiency and responsiveness. “The other big use case is around contact centers, customer service, some kind of engagement from both,” Rowan said. “So those are the biggest areas where we’re seeing the biggest efficiency gains.”

How businesses are measuring the impact of gen AI

As businesses seek to quantify the impact of their AI investments, Rowan emphasizes the importance of looking at both quantitative and qualitative metrics.

While cost savings and efficiency improvements are important, companies must also track the number of new ideas and use cases generated, as well as the impact on employee skills and culture.

In quantitative categories Rowan cites some key metrics:

• Measuring efficiency through cost savings
• Additional income generation
• Increased efficiency per full-time equivalent employee (FTE) in certain activities.

On the qualitative side, Rowan focuses on metrics around employee development, continuous learning and the overall transformation of business processes.

“How is the skill development of your employees? How can you use this opportunity to really change the culture of learning and development? ” he said.

Benefit from the promise of agent AI

Perhaps the biggest area of ​​innovation for businesses to consider in 2025 is agent AI.

The report shows that 52% of organizations are pursuing AI agents, with 45% specifically exploring multi-agent systems. Rowan expressed optimism about the potential of agent AI, but noted that it will take time for businesses to fully adopt and integrate this technology. He explained that businesses are likely to start with simpler, more focused agent applications before expanding their use.

Rowan says agent AI has the potential to fundamentally change business processes and drive significant ROI, but only if approached strategically. With the initial rollouts of gen AI, enterprises are often focused on proof of concept (PoC) deployments. A different approach is needed for agent AI. Instead of looking at individual use cases, businesses are better served looking at the broader process chain. He explained that the real value of agent AI will come from rethinking the entire business process to be AI-driven, rather than just implementing individual use cases.

“To do the agent, you have to think about how you’re going to rebuild the processes with the idea that it’s all going to be AI-driven, not human-driven,” he said.

Overcoming adoption challenges

Despite the clear benefits, businesses continue to face many barriers to scaling their AI deployments.

One of the key obstacles, according to Deloitte, is the limited access and use of AI tools within the workforce. According to the report, less than 40% of the workforce in most organizations have access to gen AI tools.

This lack of widespread adoption points to the need for a cultural shift, where employees are not only given the tools, but understand the value and importance of incorporating AI into their daily workflows. .

“If you’re not using AI once a day for your day-to-day, whether it’s a corporate tool you’re given or a consumer-based tool, I think you’re missing out,” Rowan said.