ServiceNow hits $1 billion in AWS Marketplace transactions as enterprises rapidly adopt AI at scale

Key Terms

ai control tower technical

An AI control tower is a centralized system that monitors, coordinates and governs an organization’s AI tools and data flows, like an air-traffic controller for machine intelligence. It helps ensure models behave as expected, stay compliant with rules, and are updated or shut down if they misfire—matters for investors because it reduces operational risk, regulatory exposure and unexpected costs while protecting a company’s ability to scale AI-driven products and services.

amazon bedrock agentcore technical

A managed cloud service that provides tools and infrastructure to build, run and coordinate AI “agents” — software that can carry out tasks, answer queries and connect different systems. Think of it as a ready-made toolbox plus a conductor that helps businesses deploy smart assistants without building everything from scratch; investors watch it because wide adoption can drive sales, lower customers’ development costs, and strengthen a provider’s competitive position in the fast-growing AI market.

configuration management database (cmdb) technical

A configuration management database (CMDB) is a centralized digital inventory that records an organization’s IT components — like servers, software, network devices — and how they connect and depend on each other. For investors, a CMDB matters because it gives management a clear map for preventing outages, estimating remediation costs, guiding cybersecurity and compliance efforts, and supporting smoother integration or scaling, much like a detailed maintenance log and wiring diagram for a complex building.

model context protocol (mcp) technical

The Model Context Protocol (MCP) is a system that helps financial models understand and share information about market conditions and data. It’s like a common language that ensures different tools and models work together smoothly, making predictions and decisions more accurate and consistent.

aiops technical

AIOps (Artificial Intelligence for IT Operations) uses machine learning and data analysis to monitor, detect, and resolve problems in an organization’s technology systems automatically. It matters to investors because it can cut downtime and operating costs, speed up fixes, and make digital products more reliable—similar to an autopilot that notices and corrects issues before they disrupt service, which can protect revenue and reduce operational risk.

site reliability engineering technical

Site reliability engineering is a discipline that designs, tests and runs systems so a company’s websites and online services stay up, fast and secure—think of it as building maintenance for digital products, preventing and fixing outages before customers notice. Investors care because reliable systems protect revenue, customer trust and regulatory compliance, reduce the chance of costly interruptions, and make operational costs and risk more predictable.

telco customer 360 technical

A telco customer 360 is a single, unified profile that brings together a telecom subscriber’s billing records, usage patterns, device data, support history, and demographic or third-party information so a company can see the whole relationship at a glance. For investors, it matters because a clear, up-to-date customer view helps the carrier reduce churn, sell the right add-ons, cut service costs and better predict future revenue—like turning scattered puzzle pieces into one complete picture of value.

ServiceNow AI Control Tower and Amazon Bedrock AgentCore give mutual customers a unified governance architecture for the enterprise

New AI agent integrations across security, IT operations, and telecommunications detect, act, and resolve issues with humans in the loop

Developers can build and deploy AI agents on the ServiceNow AI Platform directly from Kiro, the AWS agentic IDE

LAS VEGAS--(BUSINESS WIRE)-- Knowledge 2026 — May 6, 2026 — ServiceNow (NYSE: NOW), the AI control tower for business reinvention, and Amazon Web Services (AWS) today announced a platform expansion as companies rapidly deploy and scale agentic AI across the enterprise, which follows a significant milestone of ServiceNow AWS Marketplace transactions surpassing $1 billion. The expansion introduces a governance architecture for mutual customers built on ServiceNow AI Control Tower and Amazon Bedrock AgentCore; new AI agent integrations for enterprise security, IT operations, and telecommunications that detect, act, and resolve issues; and a native developer integration that lets teams build and deploy ServiceNow applications directly from Kiro, the AWS agentic integrated development environment (IDE), so that developers can move from idea to impact faster.

ServiceNow’s $1 billion milestone reflects something larger than a commercial threshold. Enterprises are consolidating their AI infrastructure around platforms they trust, and increasingly, that means combining cloud and foundation model services with orchestration, governance, and workflow execution. ServiceNow’s platform expansion with AWS is a direct response to that demand: customers who have already committed to both platforms now have a single, connected architecture to deploy and scale AI. The AI workloads they've already built and deployed on AWS can now be governed, audited, and wired into the ServiceNow workflows that run their business, without rebuilding anything from scratch.

“The enterprises leading in AI are deploying it, at scale, across their most critical operations on a trusted governance architecture. ServiceNow and AWS are meeting that moment together,” said Jon Sigler, executive vice president and general manager, AI Platform at ServiceNow. “ServiceNow's orchestration and governance capabilities combined with AWS's cloud and model infrastructure is the architecture that makes that possible, and the $1 billion in AWS Marketplace transactions shows that the market agrees.”

“Organizations aren't experimenting with AI anymore, they're operationalizing it,” said Chris Grusz, managing director of technology partnerships at AWS. “ServiceNow and AWS are delivering the architecture to make that real: unified governance, trusted infrastructure, and developer tools that take AI from idea to impact. With more than $1 billion in AWS Marketplace transactions, the momentum is clear. Now we're making it easier than ever to deploy, govern, and scale AI agents across the enterprise.”

AI Control Tower and Amazon Bedrock AgentCore: where enterprise AI gets built and governed

Enterprises scaling agentic AI face a common problem: agents built on different models, governed by different teams, with no unified view of what they are doing or whether they are working. ServiceNow AI Control Tower and Amazon Bedrock AgentCore address this together. Amazon Bedrock AgentCore provides the flexible foundation to build agents on the models and infrastructure customers trust, while ServiceNow AI Control Tower delivers the unified control plane to help govern how those agents operate across the business. Leading enterprises are building toward this architecture now.

“At TEKsystems Global Services, we don't just implement AI transformation for our customers, we live it,” said Matt Payne, senior vice president and head of TEKsystems Global Services. “ServiceNow's AI Control Tower gives us enterprise-wide governance to deploy and manage AI agents with confidence, across our own operations and the complex client environments we support. Combined with Amazon Bedrock AgentCore, it's a single place to govern, manage, and orchestrate every AI agent, model, and workflow, whether built in ServiceNow or AWS. That hands-on experience is our edge. We know what it takes to move AI from pilot to production at enterprise scale because we're doing it ourselves.”

ServiceNow AI Specialists and AWS AI agents tackle critical enterprise workflows

Across security, IT operations, and telecommunications, manual triage and system handoffs compound risk and delay outcomes. ServiceNow AI specialists working alongside AWS AI agents handle these workflows end to end, with humans in the loop to guide important decisions.

• Security use case: The moment a configuration change is detected in the Configuration Management Database (CMDB), ServiceNow Vulnerability Resolution AI Specialist calls the AWS Security Agent via the Model Context Protocol (MCP) to run an on-demand penetration test against the affected application. ServiceNow then layers on identity blast radius from Veza and device exposure from Armis, producing a complete risk picture. It then determines the fix and presents it for a single human approval. Remediation executes on two parallel tracks: patch deployed, privileges reduced. A final call to the AWS Security Agent will confirm that the fix is clean.
• IT operations use case: An anomaly detected by Amazon CloudWatch is routed to ServiceNow, where the ServiceNow AIOps AI Specialist and Site Reliability Engineering AI Specialist collaborate with the AWS DevOps Agent to correlate events, enrich signals with business context, and validate and execute remediation with human approval. Post-remediation, alerts are confirmed cleared, often proactively without a formal incident ever being raised.
• Telecommunications use case: A ServiceNow and AWS AI-orchestrated telecommunications customer care solution leverages the combined strengths of Amazon Connect for interactions, AWS for infrastructure intelligence, and ServiceNow Telecommunications Service Management for orchestration. When a customer contacts support, a transcript streams into the ServiceNow Telco Customer 360-powered agent workspace in real time via Amazon Connect. A ServiceNow AI specialist queries RADCOM, a cloud-native network intelligence provider running on AWS, for a scored assessment of voice, video, and streaming quality via Agent-to-Agent (A2A), and simultaneously queries ARIA for billing history and lifetime value. Based on findings and knowledge base rules, the AI specialist recommends a resolution, routes important decisions for human approval, triggers field dispatch if required, and closes the case with a full audit trail.

Build and deploy ServiceNow AI Agents directly from Kiro

ServiceNow is bringing the ServiceNow SDK with Build Agent skills natively into Kiro, giving developers the ability to build and deploy ServiceNow applications, including AI agents, directly from the AWS IDE. With a single-click install from the Kiro Power Marketplace, developers can scaffold applications, configure workflows, and create AI agents through prompt engineering without ever leaving their IDE. Because everything runs natively on the ServiceNow AI Platform, developers get enterprise governance and security without any additional configuration.

Availability

• ServiceNow AI Control Tower with Amazon Bedrock AgentCore is available now in AWS Marketplace.
• The ServiceNow Vulnerability Resolution AI Specialist, AIOps AI Specialist, and Site Reliability Engineering AI Specialist integrations with AWS AI agents is expected to be available later this year, with launch details to follow.
• The AI specialist workflow for telecommunications is available now. ServiceNow Telecommunications Service Management is a generally available product and now includes ServiceNow Telco Customer 360 as part of the Australia Platform release.
• The ServiceNow SDK for Kiro is available now through the Kiro Power Marketplace.
• Learn more about how ServiceNow is expanding its Autonomous Workforce of AI Specialists to major business functions at Knowledge 2026 here, and how it’s introducing new AI Control Tower capabilities to further discover, observe, govern, secure, and measure AI deployed across the enterprise here.

About ServiceNow

ServiceNow (NYSE: NOW) is the AI control tower for business reinvention. The ServiceNow AI Platform integrates with any cloud, any model, and any data source to orchestrate how work flows across the enterprise. By unifying legacy systems, departmental tools, cloud applications, and AI agents, ServiceNow provides a single pane of glass that connects intelligence to execution across every corner of business. With more than 100 billion workflows running on the platform each year, ServiceNow helps organizations turn fragmented operations into coordinated, autonomous workflows that deliver measurable results. Learn how ServiceNow puts AI to work for people at www.servicenow.com.

Forward-looking statements

This press release contains “forward-looking statements” about the expectations, beliefs, plans, and intentions relating to ServiceNow and AWS innovations. Such statements include statements regarding future product capabilities and offerings and expected benefits to ServiceNow. Forward-looking statements are subject to known and unknown risks and uncertainties and are based on potentially inaccurate assumptions that could cause actual results to differ materially from those expected or implied by the forward-looking statements. If any such risks or uncertainties materialize or if any of the assumptions prove incorrect, ServiceNow’s results could differ materially from the results expressed or implied by the forward-looking statements made. ServiceNow undertakes no obligation, and does not intend to update the forward-looking statements. Factors that may cause actual results to differ materially from those in any forward-looking statements include: (i) delays and unexpected difficulties and expenses in executing the product capabilities and offerings, (ii) changes in the regulatory landscape related to AI and (iii) uncertainty as to whether sales will justify the investments in the product capabilities and offerings. Further information on factors that could affect ServiceNow’s financial and other results is included in the filings ServiceNow makes with the Securities and Exchange Commission from time to time.

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Source: ServiceNow