Red Hat Summit 2026 is here in Atlanta, and the energy is incredible. Thousands of open source practitioners, enterprise architects, and AI engineers have gathered at the Georgia World Congress Center for what is shaping up to be one of the most AI-focused Summits yet.
Here is my on-the-ground experience from the event.
The Sponsor Ecosystem: Who Is Backing Open Source AI
The sponsor lineup tells you everything about where enterprise open source is heading. Every major infrastructure player is here, and they are all betting on AI.
Platinum Sponsors
The platinum tier reads like a who’s-who of AI infrastructure: AMD, AWS, Google Cloud, IBM, Intel, Microsoft, and Portworx by Pure Storage. Every single one of these companies is racing to provide the compute, storage, and cloud fabric that AI workloads demand.
What strikes me is the balance: chip makers (AMD, Intel), hyperscalers (AWS, Google Cloud, Microsoft), the parent company (IBM), and a storage specialist (Portworx). AI workloads need all of these layers working together, and Red Hat is positioned as the common denominator.
Gold Sponsors
The gold tier brings the infrastructure heavyweights: Cisco, Dell Technologies, F5, Hewlett Packard Enterprise, Lenovo, NetApp, NVIDIA, and Veeam. Notice NVIDIA here — the GPU company that is powering virtually every enterprise AI deployment. Their partnership with Red Hat on NVIDIA NIM and GPU Operator is a major theme at this Summit.
Deploy to the Feed
Red Hat knows how to build community engagement. The “Deploy to the Feed” campaign encourages attendees to share their Summit moments with #RHSummit — and the hallways are buzzing with content creators, engineers live-tweeting sessions, and booth selfies.
Product Spotlights in Sidney Marcus Auditorium
The product spotlights are happening in the Sidney Marcus Auditorium, and they cover the full Red Hat portfolio. The icons on the sign tell the story: OpenShift AI, Ansible Automation Platform, OpenShift, RHEL, and more.
What caught my eye is the LEGO set giveaway for completing session surveys. Smart move by Red Hat — gamifying feedback collection. (Red Hat, IBM, and government employees are excluded, naturally.)
These spotlights are a great way to get hands-on with the latest features without the full session commitment. I am particularly interested in the RHEL AI and InstructLab demos.
Turkish Airlines: 60+ AI Models at Scale
One of the standout customer stories at Summit is Turkish Airlines, which has scaled 60+ AI models across the business while literally flying to every corner of the world. The tagline — “Keep your options open” — perfectly captures the Red Hat value proposition: avoid vendor lock-in while running mission-critical AI at airline scale.
Think about what that means operationally: flight optimization, predictive maintenance, customer service, pricing, crew scheduling — all powered by AI models running on Red Hat infrastructure. This is exactly the kind of production AI at scale that enterprise organizations are striving for.
Late-Night Labs
The Late-Night Labs on Tuesday evening (6:00-8:30 PM ET, Building A, Level 3) combine hands-on learning with pizza and a fun atmosphere. It is the perfect way to get practical experience with Red Hat technologies in a relaxed setting. The neon pizza and VR headset graphics capture the vibe — technical depth meets after-hours fun.
Georgia Aquarium Closing Event
The closing event takes over the Georgia Aquarium — the largest aquarium in the Western Hemisphere. Wednesday, May 13, 7-10 PM ET. “Swim upstream with us” is a fitting metaphor for the open source community that has always gone against the proprietary current.
Partner Keynote: Relentless Prioritization, Momentum to Mastery
Andrew Brown, Red Hat’s SVP and Chief Revenue Officer, took the stage at the Partner Ecosystem Day to lay out the partner strategy for 2026. The three pillars he emphasized tell you exactly where Red Hat is focusing its go-to-market energy:
- Relentless prioritization — focusing partner efforts on the highest-impact opportunities
- Momentum to mastery — building deep technical expertise across the partner ecosystem
- Being unstoppable together — the collaborative flywheel between Red Hat, partners, and customers
The packed ballroom for the partner keynote shows how seriously the ecosystem takes this event. With the Innovation Awards, market data from Omdia, and the strategic roadmap from leadership — Partner Ecosystem Day sets the tone for the entire Summit.
Individual Award Highlights
Capgemini winning Hybrid Cloud Everywhere reflects the massive demand for consultancies that can bridge on-premises and multi-cloud Red Hat deployments at enterprise scale.
Logicalis as Container Champion Partner of the Year highlights the growing importance of OpenShift adoption across enterprise customers looking to modernize their application platforms.
AI Partner Opportunity: $59B to $267B by 2030
The growth trajectory is staggering. Omdia projects the AI partner opportunity will grow from $59B in 2025 to $267B by 2030 — a 35.3% CAGR. The year-by-year progression: $85B (2026) → $119B (2027) → $159B (2028) → $206B (2029) → $267B (2030).
For consultants and technology partners, this is the single largest growth opportunity in enterprise IT history. The implication is clear: if you are not building AI capabilities now, you are leaving exponential revenue on the table.
Agentic AI: 47% of Customers Need Partners
Perhaps the most telling slide for anyone in the consulting or advisory space: 47% of customers are partnering with specialized providers for agentic AI. Only 12% are developing AI agents in-house with internal teams. The breakdown (Canalys QuickPolls, 394 global partner respondents):
- 47% — Partnering with specialized providers, partners, and experts
- 24% — Adopting a hybrid approach (some build, some buy)
- 17% — Purchasing off-the-shelf AI agent solutions
- 12% — Developing AI agents in-house with internal teams
This confirms that agentic AI is too complex for most organizations to tackle alone. The demand for expert guidance on architecture, deployment, and scaling is only going to accelerate.
Omdia AI Maturity: 70% of PoCs Never Reach Production
The Omdia data on AI adoption maturity is sobering — and validates what many of us see in the field. Key findings from their AI Maturity Survey (N=448):
- 59% of organizations have dedicated AI budgets (40% over $500K)
- 29% average growth expected in AI budgets for 2026
- 70% say fewer than 20% of PoCs make it to production — the main blocker is integration and architectural complexity
- 32% prioritize use cases with the biggest impact on customer experience
- Only 28% of GenAI and 16% of Agentic AI deployments are scaling across multiple use cases
- 12% still have no AI strategy at all
The PoC-to-production gap is the elephant in the room. Organizations are spending heavily on AI experimentation, but the infrastructure and integration challenges are preventing most projects from reaching production. This is exactly where Red Hat’s platform approach — OpenShift AI, RHEL AI, Ansible — comes in.
AI Opportunities Across the Customer Journey
Omdia mapped out where AI creates partner opportunities across the entire customer lifecycle:
- Advise — Business transformation, executive planning, roadmap and use case development, tech advisory, assessment, change management
- Design — Architecture, sovereignty, data strategy, LLM advisory, configuration and customization
- Build — Co-innovation, customization, security/compliance, custom integrations, industry applications, white-label technology
- Procure — Implementation and integrations, data collection/cleansing/optimization, data management and orchestration
- Adopt — Analytics, business process, training
- Manage — Ongoing management, maintenance and improvements, assess and monitor
This framework is incredibly relevant for consultants and advisors. Every stage of the AI journey needs specialized expertise — and the partner ecosystem delivers 66.7% of all IT deals.
The 1K Global Partner Ecosystem
The Omdia Global Partner 1000 visualization is stunning — a galaxy of logos representing the world’s largest technology partners. The inner circle reads like a Fortune 500 of IT services: Accenture, Deloitte, TCS, PwC, Capgemini, IBM, NTT, Cognizant, Infosys, Leidos, HCLTech, Wipro, Booz Allen, Atos, DXC, SHI, Kyndryl, NEC, Fujitsu, EY, CGI, KPMG.
The data backs this up: 66.7% of the total addressable IT market flows through the channel, and 96% involves “partner assist” in some form.
The $6.1 Trillion IT Market: Omdia’s 2026 Breakdown
One of the most eye-opening presentations featured Omdia’s Total Addressable IT Market analysis for 2026 — a staggering $6.1 trillion worldwide B2B Tech and Telco market growing at 10.2%.
The breakdown reveals where the money is flowing:
- IT Services — $1,869B (the largest slice at 14.8% of the market)
- Software — $1,307B (+16.6% growth — the fastest-growing major segment)
- Cloud Application Software (SaaS) — $631B (embedded within software)
- Servers — $563B (driven by AI infrastructure demand)
- Cloud Infrastructure (Hyperscalers) — $493B
- Managed Services — $600B
- Components and Peripherals — $244B (+15.5% growth)
- Cybersecurity — $106B (+10.9% growth)
- On-Premises Application Software — $357B
- Telecom Services — $1,054B
The numbers that jump out: software at +16.6% growth and components/peripherals at +15.5% — both driven by AI. The server segment at $563B reflects the massive GPU infrastructure buildout happening across every industry. Cybersecurity at $106B with 10.9% growth confirms that security spending is keeping pace with the AI expansion.
For anyone in the Red Hat ecosystem, the takeaway is clear: the total addressable market for open source infrastructure, automation, and AI platforms is enormous and accelerating.
Red Hat Ecosystem Innovation Awards 2026
One of the highlights of Summit is the Red Hat Ecosystem Innovation Awards ceremony — recognizing partners who are pushing the boundaries of what open source can do in production.
The ceremony took place in a packed ballroom with dramatic purple and red lighting. The energy was electric as the winners were announced across six categories:
Global Winners
- AI Visionary Partner of the Year — Google Cloud
- Automation Accelerator Partner of the Year — One Technology
- Container Champion Partner of the Year — Logicalis
- Hybrid Cloud Everywhere Partner of the Year — Capgemini
- Platform Modernization Partner of the Year — Microsoft
- Virtualization Transformation Partner of the Year — Everpure
The categories tell the story of where enterprise IT is heading: AI, automation, containers, hybrid cloud, platform modernization, and VMware-to-OpenShift migration. Each winner represents a partner that shipped real production outcomes with Red Hat technology.
Everpure winning the Virtualization Transformation award is particularly notable — this is the category that captures the massive VMware-to-OpenShift migration wave sweeping through enterprise IT since the Broadcom acquisition.
Microsoft taking Platform Modernization underscores how far the Red Hat-Microsoft partnership has come. Azure Red Hat OpenShift (ARO) is now a first-class managed service, and the two companies are deeply aligned on enterprise Kubernetes.
Regional Honorable Mentions
The regional honorable mentions show the global reach of the Red Hat partner ecosystem:
- AI Visionary — Simudyne (EMEA), Dell Technologies (NA)
- Automation Accelerator — Conclusion Xforce (EMEA), RTM (LATAM), Pellera (NA)
- Container Champion — NxtGen (APAC), Vertis (LATAM), Everpure (NA)
- Hybrid Cloud Everywhere — NxtGen (APAC), Microsoft (NA)
- Platform Modernization — TCS (APAC), IPT (EMEA), Peraton (NA)
- Virtualization Transformation — (EMEA winner not visible), Arctiq (NA)
Lola AI Package Manager
One of the gems I found on the show floor: Lola, an AI package manager for skill modules. Built by the Red Hat Product Security team, Lola uses a marketplace concept — registries of skill modules that you can add, list, enable, and update from the CLI. The demo showed installing Lola via uv tool install lola-ai and adding the Red Hat Product Security marketplace with lola market add prodsec. Think of it as a pip for AI skills — modular, composable, and community-driven.
RISC-V Server Hardware at Red Hat
The Red Hat booth had actual RISC-V server hardware running — multiple RISC-V boards in a tower chassis with LF Energy “The Power of Together” branding. This is not a prototype anymore. Red Hat is actively building RHEL support for RISC-V, and seeing production-grade server hardware with RISC-V stickers alongside the traditional x86 and ARM ecosystem tells you where the industry is heading. Open source silicon running open source software.
Red Hat and AMD: Enterprise AI Stack
The AMD partnership slide tells the full story of Red Hat’s AI platform strategy. Three tiers of software stack — RHEL AI (single node), Red Hat OpenShift AI (Kubernetes-scale), and the full Red Hat AI platform — mapped against AMD’s hardware lineup: EPYC CPUs, Instinct MI350P and MI355X for inference, and the upcoming Helios (2026) MI450 x 72 rack for training. The message is clear: Red Hat is hardware-agnostic but AMD-optimized for enterprises that want an alternative to NVIDIA’s dominance.
InstructLab: SDG Hub and Training Hub
The InstructLab team presented two key components for community contribution: the SDG Hub (Synthetic Data Generation) and the Training Hub. Both repositories are open source and actively seeking contributors — the stage showed QR codes linking directly to the GitHub repos.
A powerful customer success story from a German public sector deployment (Atos and Red Hat partnership). The challenge: analyzing vast unstructured social media data for 14 distinct features with 100% valid JSON extraction and precise violence detection. The solution used a “Teacher-Student” methodology with SDG Hub — training Phi-4 Mini (1B), Qwen 2.5 (1.5B), and Qwen 2.5 (7B) models using SFT and Orthogonal Subspace Fine-Tuning (OSFT) via OpenShift AI. The results: Qwen 2.5 7B outperformed GPT-4.1 with a detailed prompt (30.8 vs 30.5 pts), and Phi-4 Mini 1B improved JSON validity from 1% to 99% after fine-tuning. The entire pipeline ran on just 3x NVIDIA L40 GPUs.
The Training Hub provides a unified API surface for modern LLM post-training. It supports supervised fine-tuning (SFT), LoRA/QLoRA parameter-efficient tuning, OSFT, and Lora-GRPO — all through the same Python API. Native integration with MLFlow for experiment tracking and the Kubeflow Training Operator for Kubernetes-scale training. Install it with pip install training-hub[lora,grpo].
The live coding demo walked through loading a HuggingFace dataset, generating 13,222 training examples via SDG, and running OSFT continual learning on the Qwen 2.5 1.5B Instruct model — all in a Jupyter notebook.
Real-time MLFlow experiment tracking showing model metrics for the osft-Qwen2.5-1.5B-Instruct-tablegpt training run: avg_loss_backward, avg_time_per_minibatch, and batch_num_loss_counted_tokens across 50 training steps.
The demo stage at Red Hat Summit — a purpose-built theater with headphone listening stations. The InstructLab demo covered an openly available DOTS notebook for continual learning, showing how off-the-shelf limitations can be overcome with targeted fine-tuning while preserving general capability.
Ansible Automation Orchestrator
The new Ansible Automation Orchestrator is a game-changer for enterprise security operations. The demo showed a complete vulnerability remediation workflow on a single canvas: alerts from multiple sources (IBM Instana, ServiceNOW, Splunk) trigger deterministic automation rulebooks, an AI agent analyzes and recommends actions, humans approve the remediation plan, and automated execution happens at scale. Five steps — from alert to remediation — with full end-to-end governance and trusted execution. This is what agentic AI looks like in production: connecting event detection, AI reasoning, and deterministic execution in a unified management plane.
What I Am Watching
Red Hat Summit 2026 has a clear theme: AI is no longer a future bet — it is a present-tense production reality. From Turkish Airlines running 60+ models to the platinum sponsor lineup of every major AI infrastructure provider, the message is unmistakable.
Key trends I am tracking:
- RHEL AI and InstructLab are becoming the enterprise on-ramp for fine-tuning open models
- OpenShift AI is the Kubernetes-native ML platform that ties everything together
- Ansible Automation Platform is evolving with AI-assisted playbook generation
- Edge AI deployment patterns are a recurring theme across sessions
- The open source AI movement is gaining enterprise credibility fast
I am also giving away copies of my book Practical RHEL AI at the Lawn Lounge — stop by if you are at Summit!
