Digitalocean Report Finds Widening Gap Between Companies Adopting Agentic AI and Those Falling Behind
Biannual survey of cloud users points to accelerating adoption of agentic AI and inference, trends expected to shape budgets and infrastructure needs in 2026
DigitalOcean , the Inference Cloud for production AI, released its Currents report, finding that while businesses are increasingly leveraging AI for problem-solving and efficiency, fully autonomous agentic deployments remain early-stage, and AI spend has shifted from training to inference.
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DigitalOcean’s Currents report provides insight into how digital native enterprises are using artificial intelligence. Pulled from more than 1,100 responses from developers, CTOs, and founders via an online survey completed in November 2025 that was received by both DigitalOcean customers and non-customers, the survey findings include:
- Organizations have moved from AI exploration to implementation: The percent of companies actively implementing AI solutions, optimizing AI performance, or treating AI as a core component of their business strategy has grown to 52%, compared to 35% who said the same in 2024.
- AI spend has shifted from training to inference: Nearly half (44%) of organizations now allocate the majority (76-100%) of their AI budget to inferencing, rather than training, demonstrating that the next generation of AI businesses will be built on inference.
- Infrastructure as a strategy: Only 23% are using a single cloud provider that combines models, data, and infrastructure. For organizations using multiple tools, the top challenges are all related to complexity and cost. Most organizations (61%) are using multiple tools stitched together, or a hybrid of multiple tools alongside an integrated stack.
- Pricing (75%) and ease of use (61%) are important factors when selecting AI infrastructure. For organizations using multiple tools, the top challenges are all related to complexity and cost:
- “Separate tools or APIs needed” (50%)
- “Difficulty predicting and understanding costs” (49%)
- “Deployment or orchestration complexity” (48%)
- “Challenges managing security across tools” (34%)
- AI agents save time: The use of agents to achieve productivity gains is on the rise, with 53% of companies reporting success on time saved for employees. Furthermore 44% of respondents saw new business capabilities as a direct outcome from the use of AI agents.
- Human oversight is still needed: Only 10% reported that fully autonomous agents are in production, with 40% still using human review of agent outputs. Human-in-the-loop was the top guardrail that companies reported having in place.
- Looking ahead to 2026: Expect to see the expansion of AI agents in 2026, as 38% of respondents who haven’t yet explored agents report that they will start exploring or deploying agents at that time.
The latest data make it clear that for enterprises that have not started planning or experimenting with the use of agents, the time is now to create production workflows in place to keep pace with quickly accelerating trends.
According to DigitalOcean CEO Paddy Srinivasan, “AI-native businesses are being built on a foundation of inference and agentic AI, and those who are figuring out how to effectively integrate AI into their workflows are seeing real benefits. Respondents are in agreement that the real opportunity for AI lies in applications and agents, and modern businesses are in need of straightforward, comprehensive tools that pair traditional cloud services with AI infrastructure and platform tools.”
While the use of AI agents is on the rise, and half (50%) of respondents say they are experimenting with or deploying AI agents, the majority are still exploring or testing small pilots. In fact, only 10% see agents as core to their business strategy . But businesses that have implemented agents are starting to see real productivity gains, and 61% see applications and agents as the greatest long-term value in the AI stack.
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