What Makes an Enterprise Truly Digital Native

Digital native enterprises are organizations founded in the digital era, leveraging technology as a core part of their business operations and culture. They rapidly adopt new digital tools, prioritize customer experience, and rely on data-driven decision-making. These enterprises drive innovation, agility, and competitiveness in a fast-evolving, technology-focused business environment.
What Makes an Enterprise Truly Digital Native
Written by Ryan Gibson

In the increasingly crowded landscape of cloud infrastructure, DigitalOcean Holdings Inc. is betting that artificial intelligence will become as embedded in software as “Intel Inside” was to a prior era of computing.

At the heart of the company’s ambitions is CEO Paddy Srinivasan, who sees a future where AI is integrated into every application—and where DigitalOcean, long synonymous with serving small and mid-sized businesses and developers, emerges as a viable alternative to hyperscalers like Amazon Web Services, Microsoft Azure, and Google Cloud Platform.

“We are entering an era of AI everywhere, much like it was ‘Intel Inside’ in the PC era,” Mr. Srinivasan said in a recent interview, referring to the company’s just-launched generation AI platform and surging demand from digital-native companies eager to embrace next-generation software. “AI is going to be inside every software application, and our customers are looking to companies and vendors like DigitalOcean to enable them to consume AI seamlessly into the fabric of their applications.”

AI as a Revenue Engine

DigitalOcean’s recent quarterly results underline its accelerating pivot to artificial intelligence. For the first quarter, the company reported 14% year-over-year revenue growth, with AI-related sales up 160% compared to a year prior. That growth rate—albeit off a relatively small base—reflects the appetite among its core base of smaller businesses and upstart tech firms for leveraging AI to differentiate their offerings and survive a more competitive digital economy. AI revenue is now in the “tens of millions of dollars,” Mr. Srinivasan noted, and the number of large customers spending over $100,000 has grown by 41%.

Not all news was bullish, however. DigitalOcean shares rebounded after initial declines, as the company’s earnings-per-share guidance for the current quarter fell below the midpoint of Wall Street expectations. Investors digested a volley of information: continued double-digit growth, robust AI milestones, and the company’s assertion that its just-launched generative AI platform could act as a future growth engine.

A particularly notable point is that DigitalOcean’s customer base is overwhelmingly international. “Two-thirds of our revenue comes from overseas,” said Mr. Srinivasan, who cited strong performance in both Europe and Asia—where the company derives nearly equal shares of its business.

A Strategic Maneuver in the GenAI Arms Race

The wave of excitement around AI infrastructure isn’t limited to industry giants with vast R&D budgets. DigitalOcean has doubled down on democratizing access to AI tools, particularly open-source models that have quickly evolved following the release of Meta’s Llama 3 and the proliferation of projects like DeepSeek (sometimes colloquially called “deep sea”).

“We host a lot of different AI models,” Srinivasan said, highlighting accelerating traction especially from open-source innovations. “Our open source models have seen a lot of traction, especially since Llama 3.2 came out.”

Through a private preview, over 5,000 customers have already tested DigitalOcean’s AI platform, deploying more than 8,000 AI agents, data that Mr. Srinivasan points to as evidence of pent-up demand among small digital-native enterprises—companies that were “born in” the cloud era and now see emerging AI tools as essential for staying competitive.

Navigating Macroeconomic Uncertainty

The economic backdrop for cloud companies remains uncertain. Inflation, fluctuating IT budgets, and global instability have forced many startups and small businesses—the very clientele DigitalOcean targets—to become more cautious. Analysts have noted that DigitalOcean, compared with the hyperscalers, tends to be more vulnerable to volatility among less capitalized, digital-native clients.

Yet DigitalOcean sees opportunity where others sense risk. The cloud and, increasingly, artificial intelligence are “a top line driver” for growth, Mr. Srinivasan argued, and even in a slower economy, customers must invest to stay afloat. “During these kinds of bumpy times, typically digital native enterprises use this as an opportunity to streamline their operations. But come out of this dislocation looking stronger with a set of products that are even more robust in terms of their ability to consume cutting edge technologies like AI, because otherwise they’re going to go out of business.”

Compared to AWS, Google, or Azure—each pouring billions into proprietary AI solutions and fighting for the most lucrative enterprise contracts—DigitalOcean is betting on democratization. Its pitch: to make AI tools, inference engines, and application integration affordable and accessible not just for the Fortune 500, but for the millions of businesses seeking an on-ramp to the AI revolution.

Is DigitalOcean Too Late to the AI Game?

Skeptics question whether the company, which launched its generative AI platform after larger rivals had grabbed mindshare, can catch up. But Srinivasan dismisses concern that DigitalOcean is arriving late: “We’re just getting started with GenAI. GenAI has two phases. One is you have to train the models and the other one is you have to use the models. And we are very, very early stage in terms of companies and their ability to consume and use AI in the real world. So I don’t think we are late at all. In fact, we’re super early and we have AI revenue in the tens of millions of dollars growing at 160% year over year.”

Market observers say the pace of AI adoption in the broader economy is still in its early innings, with vast swathes of applications—from e-commerce to productivity software to specialty SaaS—set to be reimagined through intelligent automation and embedded models. If that holds true, DigitalOcean’s position as a nimble, developer-friendly platform could allow it to win business from the next Stripe, Shopify, or Atlassian as those companies reinvent themselves with AI at their core.

The Stakes Ahead

As Srinivasan sees it, DigitalOcean’s opportunity—and risk—lies in serving the “digital native enterprises for whom technology and cloud is a top line driver.” The fate of the company will rest not just on its ability to scale infrastructure or launch new features, but on nurturing a vibrant community of customers and partners who consider AI, not merely as a tool, but as the essential substrate for a new era of software.

For now, DigitalOcean is wagering that the golden age of AI will be open, widely accessible, and—crucially—not the sole domain of tech’s biggest players. The company’s next act will be to convince a growing cohort of small businesses worldwide to build the future with them, one intelligent application at a time.

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