Second annual State of Infrastructure Automation report finds only 19% of organizations have built the governance foundations needed for AI readiness, even as 89% plan to adopt agentic AI for infrastructure

REDWOOD CITY, Calif., June 24, 2026 /PRNewswire/ — Spacelift, the company behind the infrastructure orchestration platform built for the AI-accelerated software era, today released the findings of its 2026 State of Infrastructure Automation report. The second annual survey of 406 IT decision-makers and platform engineering leaders reveals that AI-accelerated development is outpacing infrastructure teams’ ability to govern it, creating a widening “AI-infrastructure gap” that is already producing security misconfigurations, compliance violations and unplanned incidents at scale.

The research, conducted by Panterra Group among North American infrastructure decision-makers, introduces the AI Maturity Index (AIMI), which segments organizations into four categories based on their AI readiness:

Pioneer (19%)Outpacing (25%)Fragmented (32%)Exposed (24%)

The index evaluates behavior across five dimensions:

AI integration depthGovernance maturityInfrastructure automation maturityRisk exposurePlatform readiness

This year’s report finds that most organizations don’t yet have the AI governance frameworks required for today’s AI-driven infrastructure workflows.

“The findings are unambiguous: organizations are using AI to generate infrastructure code at a rate their governance frameworks were never designed to handle,” said Paweł Hytry, co-founder and CEO of Spacelift. “Last year we identified a gap between perceived automation maturity and actual execution. This year, the gap has moved to governance. Teams are confident they’re governing AI well, but the incident data tells a very different story.”

According to Hytry, the governance gap is compounded by a measurement gap: Most organizations are only tracking pre-AI metrics (team productivity, deployment frequency, security incidents, etc.) while few are also collecting the AI-specific signals that would reveal whether governance is actually working. “Only 15% track the volume of AI-generated IaC moving through their pipelines, and just 20% track error rates of AI-generated changes. If organizations are not measuring AI-specific outputs, they are operating in the dark,” added Hytry.

The full report includes five recommendations for closing this gap, from prioritizing IaC coverage to building agentic governance frameworks before the first autonomous workflow goes live.

Key Findings

The AI-Infrastructure Gap Is Already Measurable

Sixty-seven percent (67%) of respondents say development is ahead of infrastructure in AI adoption, and 86% say AI has increased demands on infrastructure teams. The downstream effects are compounding: 40% report security vulnerabilities appearing faster, 40% say governance is getting harder, 37% cite higher change volume, 35% report increased pipeline strain, and 35% see growing infrastructure drift.

A Governance Paradox Is Masking Systemic Risk

86% of infrastructure leaders say they are confident in their organization’s ability to govern AI, but only 30% have a formal AI governance policy in place. Among Exposed organizations, the disparity is stark: 70% express confidence in their governance capabilities, yet just 4% have a formal policy. By contrast, 71% of Pioneer organizations actively enforce a formal governance policy, and 24% report having no outstanding AI governance concerns because their controls make the risks manageable.

Vibe Coding Has Penetrated Infrastructure and Policy Layers

The use of AI to generate code without thorough review is nearly identical across developer code (79%), infrastructure as code/HCL (78%), and policy as code (78%). One-third (33%) of infrastructure teams say they would apply AI-generated HCL directly to production without any review, and an additional 43% would do so with only minimal review. Pioneer organizations vibe-code IaC at a higher rate than Exposed ones (86% versus 69%), but they do it inside governed pipelines with automated validation and policy enforcement.

“Last year, organizations overestimated their automation maturity. This year, they’re overestimating their governance readiness,” said John Garrett, managing director at Panterra Research. “The organizations that stand out are not the ones using AI the most aggressively. They are the ones that built governance frameworks before AI dramatically increased the speed and complexity of infrastructure demands on platform teams. That’s the pattern every infrastructure leader should be studying.”

Webinar

On July 16, Spacelift will host a webinar to explore the survey findings and their implications. Guest participant Faisal Afzal, CNCF and Platform Engineering ambassador and Principal at AHEAD, will speak on platform engineering’s role in closing the compliance gap. Register through this link. 

“Platform engineering teams are the ones best equipped to bring compliance and safety to infrastructure that AI now generates on its own,” said Afzal. “The survey shows organizations plunging into agentic AI well ahead of establishing the governance to handle it. The most confident teams often have the least in place. Platform engineering closes that gap before it shows up in production.”

Methodology

The 2026 State of Infrastructure Automation report is based on a survey conducted by Panterra Group in April 2026 among 406 IT decision-makers and platform engineering leaders with responsibility for infrastructure decisions. All respondents were based in North America and employed at organizations with 250 or more employees. Respondents were screened for their knowledge of infrastructure as code and their attentiveness to survey questions. The full report, including the AI Maturity Index self-assessment, is available at spacelift.io/infrastructure-automation-survey-2026.

About Spacelift

Spacelift is the infrastructure orchestration platform that manages your entire IaC lifecycle, from provisioning and configuration to governance. It integrates with Terraform, OpenTofu, CloudFormation, Pulumi, and Ansible in a single governed workflow so you deliver secure, compliant infrastructure at scale. Developer self-service, Golden Paths with guardrails, an OPA policy engine, and drift detection accelerate developer velocity while maintaining control. Spacelift Intelligence adds AI-powered provisioning and diagnostics across traditional and AI-driven workflows. See how Duolingo, Figma, Moody’s, Checkout.com, 1Password, Redfin, and others trust Spacelift to manage their infrastructure at spacelift.io/customers. Learn more about the Spacelift platform and how it can help you overcome your infrastructure challenges at Spacelift.io. Sign up for a demo, or test the platform yourself with a free trial.

Media Contact:
Cristin Connelly
Cathey Communications for Spacelift
cristin@cathey.co

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SOURCE Spacelift

Flybuy’s real-time location intelligence combined with Eagle Eye’s personalized loyalty and offer technology to help restaurants and retailers deliver seamless omnichannel experiences.

WASHINGTON, June 24, 2026 /PRNewswire-PRWeb/ — Flybuy, the industry-leading AI-powered location engine that powers over 40,000 restaurants, retailers, and grocers worldwide, announced a strategic partnership with Eagle Eye, a leading SaaS and AI technology company that enables retail, travel, and hospitality brands to earn the loyalty of their end customers through real-time, omnichannel, and personalized consumer marketing.

Together, Flybuy and Eagle Eye will deliver a combined solution that bridges the gap between customer engagement and operational execution, enabling brands to create more personalized, timely, and frictionless experiences from order to fulfillment.

By combining Flybuy’s advanced location-based technology and real-time order readiness intelligence with Eagle Eye’s best-in-class loyalty, promotions, and AI personalization capabilities, restaurant and retail brands can better understand customer behavior, streamline operations, and increase customer satisfaction and retention.

“Flybuy is focused on helping brands create exceptional customer experiences using AI-powered location technology,” said Marc Wallace, CEO and Co-Founder of Flybuy. “Partnering with Eagle Eye allows us to extend that value even further by connecting fulfillment moments with personalized engagement opportunities that drive loyalty and repeat business.”

Consumers increasingly expect convenience, personalization, and speed across every touchpoint. Through this partnership, brands can now trigger personalized offers, loyalty rewards, and engagement opportunities based on real-world customer behaviors and location events.

“Our partnership with Flybuy represents a meaningful step forward in helping retailers create truly connected customer journeys,” said Jeff Baskin, CRO at Eagle Eye. “Personalizing the omni-channel experience with ‘marketing in the moment’ provides relevancy to the customer, increased sales and incremental revenue from CPGs. Together, we’re enabling brands to deliver more relevant, seamless experiences in a personalized manner.”

Flybuy’s technology powers millions of customer interactions annually through solutions including pickup, order readiness notifications, dine-in service optimization, and guest arrival tracking. Integrated with Eagle Eye’s loyalty and promotional ecosystem, brands can now create a more connected and intelligent customer experience from purchase through fulfillment.

Key benefits of the partnership include:

Real-time personalization tied to customer arrival and fulfillment momentsEnhanced loyalty and rewards experiences across digital and physical touchpointsImproved operational efficiency for pickup, delivery, and dine-in ordersIncreased customer satisfaction through more seamless, connected experiencesActionable customer insights powered by combined behavioral and location data

As consumer expectations continue to evolve, Flybuy and Eagle Eye are committed to helping brands deliver smarter, more responsive customer experiences that build long-term loyalty and drive measurable business results.

About Flybuy

Flybuy is the leading omnichannel location platform leveraging AI-powered technology to optimize speed of service across pickup, delivery, and drive-thru. In an era where every second matters, especially for order-ahead and off-premise fulfillment, Flybuy reduces wait times and ensures fast, accurate, and seamless handoffs—boosting both operational efficiency and guest satisfaction. Through its integrated Marketing Suite, Flybuy also enables brands to deliver hyper-targeted, moment-based messages during key stages of the customer journey—helping to drive engagement, increase check size, and support broader loyalty initiatives. Tailored for restaurants, grocery, and retail, Flybuy’s AI-driven location engine is transforming how brands manage off-premise transactions and drive customer lifetime value.

About Eagle Eye

Eagle Eye is a leading SaaS and AI technology company enabling retail, travel, and hospitality brands to earn the loyalty of their end customers by powering their real-time, omnichannel and personalized consumer marketing activities at scale. Eagle Eye AIR is the company’s cloud-based platform that delivers loyalty, promotions, subscriptions, gamification, and personalized offers for leading global brands.

Media Contact

Rebecca McFarland, Flybuy, 1 2026819434, rebecca@flybuy.com, www.flybuy.com

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SOURCE Flybuy

NEWARK, N.J., June 24, 2026 /PRNewswire/ — Runpod, the AI Developer Cloud, today announced a $100 million growth investment led by Summit Partners. The round comes on the heels of strong momentum for Runpod, which is now valued at $1.0 billion. The company has more than one million developers building on the platform. The new capital will fund continued investment in the full lifecycle AI development platform those developers depend on to take AI from first experiment to production.

Runpod is the AI developer cloud, offering AI developers a single destination to build. While much of the market has converged on hosted inference, developers use Runpod to experiment, train, fine-tune, run inference, and scale multi-node runs, all from one platform, with a library of models and templates ready from day one. With self-serve access, transparent per-second pricing and no commitment minimums, most developers are running their first workload within an hour of sign-up.

“The market spent the last two years narrowing to inference, but builders need more than that,” said Zhen Lu, CEO of Runpod. “They need one place to take an idea from first experiment to production traffic, without stitching together multiple tools or waiting on a procurement cycle. That is precisely the cloud we are building. This funding lets us build it faster, to serve the next million developers and more.”

The company’s growth underscores both the depth of developer demand and Runpod’s ability to meet the needs of that community. Runpod’s Serverless platform has processed more than 20 billion inference requests to date. Developers stay because the platform earns it. The median time from sign-up to a first running workload is under an hour, more than 90 percent of deployments succeed on the first try, and 85 percent of developers who deploy come back to build more.

Runpod’s customers range from independent AI researchers to teams building and serving frontier models. Deep Cogito built its Cogito v1 family of open models entirely on Runpod. “We trained Cogito v1, a family of models that outperforms size equivalent models from LLaMA and DeepSeek, in 75 days with a small team, entirely on Runpod,” said Drishan Arora, Co-Founder and CEO at Deep Cogito. “The ability to iterate fast on world-class GPU infrastructure without building our own cluster is a genuine competitive advantage.”

The platform continues to gain traction across the open-source community. “It’s easy to see why Runpod has resonated so strongly with the broader machine learning community,” said Julien Chaumond, Cofounder and CTO at Hugging Face. “Accessible, flexible compute is core to how we think about democratizing AI, and Runpod is one of the few companies that understands that.”

With this funding, Runpod will invest in the platform and developer experience, expand the team across engineering and developer relations, and broaden global access for developers wherever they build.

“Developers building with AI today need infrastructure that can keep pace with how fast the technology is moving and the flexibility to go from early experiment to production without switching platforms,” said Michael Medici, a Managing Director at Summit Partners who will join the Runpod Board of Directors. “Runpod has built a platform designed to meet these needs, and in our view, the company’s growth trajectory reflects the team’s strong execution against that vision. We believe Runpod is positioned to become a defining infrastructure platform for the next generation of AI developers, and we look forward to supporting Zhen and the team as they continue to scale.”

 J.P. Morgan Securities LLC acted as Sole Placement Agent to Runpod in connection with the financing. Cooley LLP acted as external legal counsel to Runpod, and Kirkland & Ellis LLP acted as external legal counsel to Summit Partners.

To learn more, visit runpod.io.

About Runpod
Runpod is the AI Developer Cloud. More than one million developers use Runpod to build, train, fine-tune, deploy, and scale AI on one platform, with self-serve access, transparent per-second pricing, and no commit minimums. Learn more at runpod.io.

About Summit Partners
Summit Partners is a leading growth-focused investment firm. Summit invests across growth sectors of the economy and, since the firm’s founding in 1984, has invested in more than 550 companies in technology, healthcare and other growth industries. Summit maintains offices in North America and Europe and seeks to invest in category-leading, profitable growth companies worldwide. For more information, please visit www.summitpartners.com or follow Summit Partners on LinkedIn.

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SOURCE Runpod