ServiceNow positions itself as the control layer for enterprise AI execution Emilia David January 21, 2026 Credit: VentureBeat, generated with MidJourney ServiceNow announced a multi-year partnership with OpenAI to bring GPT-5.2 into its AI Control Tower and Xanadu platform, reinforcing ServiceNow’s strategy to focus on enterprise workflows, guardrails, and orchestration rather than building frontier models itself. For enterprise buyers, the deal underscores a broader shift: general-purpose models are becoming interchangeable, while the platforms that control how they’re deployed and governed are where differentiation now lives. 0:01 / 14:09 ServiceNow lets enterprises develop agents and applications, plug them into existing workflows, and manage orchestration and monitoring through its unified AI Control Tower. The partnership does not mean ServiceNow will no longer use other models to power its services, said John Aisien, senior vice president of product management at ServiceNow. "We will remain an open platform. There are things we will partner on with each of the model providers, depending on their expertise. Still, ServiceNow will continue to support a hybrid, multi-model AI strategy where customers can bring any model to our AI platform,” Aisien said in an email to VentureBeat. “Instead of exclusivity, we give enterprise customers maximum flexibility by combining powerful general-purpose models with our own LLMs built for ServiceNow workflows.” What the OpenAI partnership unlocks for ServiceNow customers ServiceNow customers get: Voice-first agents: Speech-to-speech and voice-to-text support Enterprise knowledge access: Q&A grounded in enterprise data, with improved search and discovery Operational automation: Incident summarization and resolution support ServiceNow said it plans to work directly with OpenAI to build “real-time speech-to-speech AI agents that can listen, reason and respond naturally without text intermediation.” The company is also interested in tapping OpenAI’s computer use models to automate actions across enterprise tools such as email and chat. The enterprise playbook The partnership reinforces ServiceNow’s positioning as a control layer for enterprise AI, separating general-purpose models from the services that govern how they’re deployed, monitored, and secured. Rather than owning the models, ServiceNow is emphasizing orchestration and guardrails — the layers enterprises increasingly need to scale AI safely. Some companies that work with enterprises see the partnership as a positive. Tom Bachant, co-founder and CEO of AI workflow and support platform Unthread, said this could further reduce integration friction. “Deeply integrated systems often lower the barrier to entry and simplify initial deployment," he told VentureBeat in an email. "However, as organizations scale AI across core business systems, flexibility becomes more important than standardization. Enterprises ultimately need the ability to adapt performance benchmarks, pricing models, and internal risk postures; none of which remain static over time.” As enterprise AI adoption accelerates, partnerships like this suggest the real battleground is shifting away from the models themselves and toward the platforms that control how those models are used in production. Subscribe to get latest news! Deep insights for enterprise AI, data, and security leaders VB Daily AI Weekly AGI Weekly Security Weekly Data Infrastructure Weekly VB Events All of them By submitting your email, you agree to our Terms and Privacy Notice. Get updates You're in! Our latest news will be hitting your inbox soon. Image credit: VentureBeat with ChatGPT MIT’s new ‘recursive’ framework lets LLMs process 10 million tokens without context rot Rather than expanding context windows or summarizing old information, the MIT team reframes long-context reasoning as a systems problem. By letting models treat prompts as something they can inspect with code, recursive language models allow LLMs to reason over millions of tokens without retraining. This offers enterprises a practical path to long-horizon tasks like codebase analysis, legal review, and multi-step reasoning that routinely break today’s models. Ben Dickson January 20, 2026 CleoP made with Midjourney Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) Every year, NeurIPS produces hundreds of impressive papers, and a handful that subtly reset how practitioners think about scaling, evaluation and system design. In 2025, the most consequential works weren't about a single breakthrough model. Instead, they challenged fundamental assumptions that academicians and corporations have quietly relied on: Bigger models mean better reasoning, RL creates new capabilities, attention is “solved” and generative models inevitably memorize. Maitreyi Chatterjee,Devansh Agarwal January 17, 2026 Credit: VentureBeat made with Google Gemini 3 Pro Image / Nano Banana Pro Claude Code just got updated with one of the most-requested user features Anthropic's open source standard, the Model Context Protocol (MCP), released in late 2024, allows users to connect AI models and the agents atop them to external tools in a structured, reliable format. It is the engine behind Anthropic's hit AI agentic programming harness, Claude Code, allowing it to access numerous functions like web browsing and file creation immediately when asked. Carl Franzen January 15, 2026 Credit: VentureBeat, generated with MidJourney Why MongoDB thinks better retrieval — not bigger models — is the key to trustworthy enterprise AI As agentic and RAG systems move into production, retrieval quality is emerging as a quiet failure point — one that can undermine accuracy, cost, and user trust even when models themselves perform well. Emilia David January 15, 2026 CleoP created with Midjourney AI agents can talk — orchestration is what makes them work together Rather than asking how AI agents can work for them, a key question in enterprise is now: Are agents playing well together? Taryn Plumb January 14, 2026 CleoP made with Midjourney Why Egnyte keeps hiring junior engineers despite the rise of AI coding tools The approach challenges a dominant 2025 narrative that automation will replace developers, showing instead how enterprises are using AI to scale engineering capacity while keeping humans firmly in the loop. Taryn Plumb January 13, 2026 Credit: VentureBeat made with Seedream v4.5 on fal.ai This new, dead simple prompt technique boosts accuracy on LLMs by up to 76% on non-reasoning tasks In the chaotic world of Large Language Model (LLM) optimization, engineers have spent the last few years developing increasingly esoteric rituals to get better answers. Carl Franzen January 13, 2026 CleoP made with Midjourney Why your LLM bill is exploding — and how semantic caching can cut it by 73% Our LLM API bill was growing 30% month-over-month. Traffic was increasing, but not that fast. When I analyzed our query logs, I found the real problem: Users ask the same questions in different ways. Sreenivasa Reddy Hulebeedu Reddy January 12, 2026 Credit: VentureBeat, generated with MidJourney Orchestral replaces LangChain’s complexity with reproducible, provider-agnostic LLM orchestration A new framework from researchers Alexander and Jacob Roman rejects the complexity of current AI tools, offering a synchronous, type-safe alternative designed for reproducibility and cost-conscious science. Emilia David January 9, 2026 Partner Content How KPMG is redefining the future of SAP consulting on a global scale Presented by SAP VB Staff January 9, 2026 Credit: VentureBeat made with Google Gemini 3 Pro Image / Nano Banana Pro Claude Code 2.1.0 arrives with smoother workflows and smarter agents Anthropic has released Claude Code v2.1.0, a notable update to its "vibe coding" development environment for autonomously building software, spinning up AI agents, and completing a wide range of computer tasks, according to Head of Claude Code Boris Cherny in a post on X last night. Carl Franzen January 8, 2026 Credit: VentureBeat, generated with MidJourney Nvidia’s Cosmos Reason 2 aims to bring reasoning VLMs into the physical world Nvidia CEO Jensen Huang said last year that we are now entering the age of physical AI. While the company continues to offer LLMs for software use cases, Nvidia is increasingly positioning itself as a provider of AI models for fully AI-powered systems — including agentic AI in the physical world. Emilia David January 5, 2026
==============
ServiceNow укрепляет позицию как контрольный слой для enterprise AI, заключая партнерство с OpenAI для внедрения GPT-5.2 в платформы AI Control Tower и Xanadu. Это позволяет компаниям создавать агентов и приложения, интегрировать их в существующие рабочие процессы и управлять их оркестрацией и мониторингом, обеспечивая безопасность и масштабируемость. Ключевым моментом является фокус на контроле над развертыванием и управлением, а не на разработке собственных моделей. Партнерство с OpenAI открывает возможности для создания голосовых агентов, автоматизации задач в корпоративных инструментах и интеграции с существующими моделями. ServiceNow делает ставку на гибкость и возможность использования различных моделей, а не на эксклюзивность.