The ServiceNow AI Summit São Paulo 2026, held on August 5th and 6th at the Transamerica Expo Center, placed AI Control Tower, agency AI, governance, and data quality at the center of ServiceNow's strategy for enterprise artificial intelligence. 4MATT participated as a Gold sponsor and brought to the event its vision of AI readiness based on ITAM, CMDB, ITOM, and asset governance, in addition to presenting, with Globo, an Enterprise Asset Management (EAM) experience in a session reserved for invited executives.
What was the ServiceNow AI Summit São Paulo 2026?
The ServiceNow AI Summit São Paulo 2026 was ServiceNow's event dedicated to the practical application of artificial intelligence, data, and workflows in business operations. The Brazilian edition took place in two parts: the Learning Labs, on August 5th, with hands-on activities on the platform, and the AI Summit, on August 6th, with keynote speeches, technical sessions, customer case studies, and participation from the partner ecosystem.
The program demonstrated a significant evolution in ServiceNow's strategy. The discussion shifted from focusing solely on generative assistants to addressing how AI agents can operate within corporate processes with context, security, oversight, and governance.
For CIOs, technology leaders and those responsible for ITOM, ITAM, In the context of CMDB and digital transformation, the main message was clear: expanding the use of AI requires a reliable operational foundation.
What were the main themes of the ServiceNow AI Summit 2026?
The event's agenda demonstrated that the next stage of enterprise artificial intelligence involves more than just providing co-pilots or generative models. The focus has shifted to control, autonomous execution, security, governance, and the quality of the data necessary for agents to act directly on corporate processes.
| Theme | Implications for companies |
|---|---|
| AI Control Tower | Centralize visibility and governance over artificial intelligence agents, models, workflows, and initiatives. |
| agent AI | To enable agents to interpret context, make decisions within defined limits, and execute actions in business processes. |
| Autonomous IT | Expand operational automation to reduce repetitive tasks and accelerate problem identification and resolution. |
| AI Workforce Security | To control the identities, permissions, access, and actions performed by autonomous agents. |
| Governance of the agency enterprise | Scaling agents while maintaining accountability, traceability, supervision, and corporate controls. |
| Data ready for agents | To ensure that automated decisions use contextualized, up-to-date, and reliable information. |
Among the sessions on the agenda were content dedicated to AI Control Tower, Autonomous IT, AI workforce security, agent-ready data, and governance of increasingly AI-driven enterprise environments.
AI Control Tower gains ground in ServiceNow's strategy.
AI Control Tower is ServiceNow's approach to expanding visibility and governance over enterprise use of artificial intelligence. The goal is to enable companies to track AI initiatives, agents, models, and workflows within a common control framework.
This concept gains relevance as organizations move from query-driven generative AI to agents capable of performing activities within enterprise systems. The challenge shifts from simply creating an agent to including governance questions: what agents exist, what processes can they execute, what data can they query, what permissions do they have, and where should human oversight exist?.
In complex corporate environments, this layer of control is necessary to prevent AI initiatives from developing in a fragmented way across departments, suppliers, and platforms.
From generative AI to agentic AI
Generative AI initially gained scale through assistants capable of producing texts, summarizing information, answering questions, and supporting human activities. Agentive AI expands this model by enabling systems to interpret objectives, utilize context, perform tasks, and interact with corporate workflows.
This shift significantly increases the importance of governance. When AI only recommends an action, a person can still validate the decision before execution. When an agent starts executing the process, data quality, identity, authorization, operational context, and traceability become critical components of the architecture.
Therefore, the move towards an agentic enterprise does not eliminate traditional operational governance disciplines. In practice, it increases the reliance on mature processes, reliable data, and clearly defined responsibilities.
Enterprise AI in Brazil: Investment is advancing faster than governance.
The scenario discussed at the AI Summit aligns with the results of ServiceNow's 2026 Enterprise AI Maturity Index. The study assessed executives from different countries and sectors to understand how organizations are evolving from experimentation to the structured use of artificial intelligence.
In the Brazilian analysis released in 2026, the data shows a significant acceleration in investment, accompanied by challenges related to governance, transparency, and control.
| Indicator | Brazil in 2026 | Strategic reading |
|---|---|---|
| Growth in AI spending | 127% compared to the previous year | Investment is progressing rapidly, increasing the pressure to generate concrete results. |
| Organizations that are already actively using AI | 57% | Adoption is beginning to move beyond the purely experimental phase in a significant portion of companies. |
| Companies with structured risk testing, auditing, and assessment. | 13% | Governance is still advancing at a slower pace than technological adoption. |
| Executives who identify a lack of transparency in AI systems. | 61% | Explainability, control, and traceability are now part of the executive agenda. |
| Brazilian AI Maturity Index | 48 points | The result was below the global average of 51 points recorded in the study. |
The indicators help explain why governance, data, and control featured prominently in discussions at the ServiceNow AI Summit. The business challenge is not only to make artificial intelligence available, but to build an operational architecture capable of using it in a controlled, traceable, and scalable way.
The data is part of ServiceNow's Enterprise AI Maturity Index 2026 and was detailed in an analysis published by Data Center Dynamics Brazil.
ServiceNow expands its presence in Brazil.
The timing of the AI Summit also coincided with an expansion of ServiceNow's presence in the Brazilian market. In August 2026, the company announced its first dedicated operation in Brazil, in São Paulo, and initiatives focused on training professionals for artificial intelligence and platform technologies.
This move reinforces the importance of the Brazilian market within ServiceNow's regional strategy and reflects the increasing adoption of automation and artificial intelligence by large organizations.
In addition to commercial expansion, the strategy includes initiatives related to talent development, a relevant front given the need to combine knowledge in platform, data, processes, architecture, and AI to implement more autonomous business environments.
Data-ready for agents: why CMDB and ITAM are gaining importance.
One of the consequences of the evolution towards agentic AI is that data quality begins to have a direct impact on the quality of decisions and actions performed by agents.
An agent may correctly interpret a request and still perform an inappropriate action if they are working with incorrect relationships, non-existent assets, outdated assignees, or incomplete information.
It is at this point that CMDB, CSDM, ITAM, Discovery and data governance are now directly integrated into an AI-readiness strategy.
| Foundation | Role in enterprise AI |
|---|---|
| CMDB | Provides context about components, applications, services, and their relationships. |
| CSDM | It structures the data model that connects technological resources to services and to the business. |
| Discovery | It automates infrastructure identification and reduces reliance on manual inventories. |
| ITAM | It adds information about ownership, usage, contracts, costs, and the life cycle of assets. |
| ITOM | It connects events, operational context, and automation to the service infrastructure. |
| AI Governance | It defines controls over agents, access, decisions, risks, auditing, and supervision. |
4MATT's interpretation is that the evolution towards autonomous agents increases, rather than reduces, the importance of traditional operational governance disciplines. The greater the execution capabilities of artificial intelligence, the greater the trust that must be placed in the context used to decide and act.
4MATT at the ServiceNow AI Summit São Paulo 2026
4MATT participated in the ServiceNow AI Summit São Paulo 2026 as a Gold sponsor, with experts at the booth for technical discussions on artificial intelligence, ITAM, CMDB, ITOM, EAM, architecture, and the evolution of the ServiceNow platform.
Participation reinforced the company's positioning as ServiceNow Elite Partner in Brazil and recognized with the Technology Excellence Partner Award in 2024 and 2025. 4MATT brings together more than 180 certified specialists and more than 1,780 ServiceNow certifications.
During the event, the team presented a vision of AI readiness based on an architectural principle: enterprise artificial intelligence needs to operate on mature processes, reliable data, governed assets, and clear control mechanisms.
This approach connects AI to disciplines that are already part of business operations, such as ITAM, CMDB, ITOM, Discovery, CSDM, and enterprise asset management.
4MATT and Globo presented their EAM experience in a private session.
During the event, 4MATT and Globo held a private session for invited executives on the evolution of enterprise asset management using ServiceNow EAM (Enterprise Asset Management).
The session took place outside the public agenda of the AI Summit and discussed how a complex environment of physical assets can evolve in governance, traceability, and lifecycle control.
The context presented was PodParque, a suite of media solutions that brings together equipment used in Globo's production operations. In this environment, asset management needed to evolve from fragmented controls to structured processes capable of tracking acquisition, use, repair, warranties, and disposal.
Among the critical flows was the disposal process, which involves transportation, definition of responsibilities, and formal write-off of assets that have reached the end of their life cycle.
Another important process was the repair workflow, involving opening a service request, logistical analysis, technical identification of the problem, warranty verification, and interaction with manufacturers until resolution.
With the implementation of ServiceNow EAM, these processes began to operate in a structured and traceable way within the platform. The evolution of the work also opened up space for new areas related to SAM (Software Asset Management) and HAM (Hardware Asset Management), expanding the integration between physical and technological assets under a common governance model.
The EAM ServiceNow case study at Globo It provides more details about this journey.
“4MATT did more than they promised. They understood our environment and built something that truly works for us.” — Thaina Maia, Product Owner at Globo
Globo's public participation was different from the EAM session.
Globo also participated in the public agenda of the ServiceNow AI Summit São Paulo 2026 with content related to the evolution of conversational experience and the use of artificial intelligence on the ServiceNow platform.
This participation should be differentiated from the reserved EAM session promoted by 4MATT. Both sessions took place within the same event, but addressed distinct initiatives.
Why EAM matters for asset management maturity
EAM is the discipline of managing the lifecycle of physical and business assets, covering stages such as acquisition, operation, maintenance, repair, relocation, warranty, and disposal.
While the ITAM focuses on technological assets, including hardware and software, the EAM expands governance to physical and operational assets., such as production equipment, machinery and specialized infrastructure.
When EAM, HAM, SAM, ITAM, and CMDB share processes and context within the same platform, the organization reduces fragmentation between operational, financial, and technological data. This integration creates a more consistent foundation for automation, analytics, and artificial intelligence.
The objective is no longer simply to know where an asset is located. A mature operation needs to understand what it is, what process it is involved in, who is responsible for it, what state it is in, what its cost is, what services depend on it, and what action should be taken in the face of a change in context.
From workflow automation to agency-based enterprise
One of the main takeaways from the ServiceNow AI Summit São Paulo 2026 is that the next stage of business automation is not simply about adding artificial intelligence to existing processes.
Evolution involves enabling agents to interpret context, utilize corporate knowledge, make decisions within defined limits, and execute complete workflows with governance.
This shift alters the architectural requirements. In traditional automation, deterministic rules predetermine the path to be executed. In an agentive environment, some decisions may vary depending on data, context, and objectives.
Information quality, permissions, knowledge, CMDB relationships, identity management, and oversight mechanisms therefore have an even greater impact on operational results.
AI readiness begins before agent deployment.
AI readiness can be understood as an organization's ability to deploy artificial intelligence on a technological and operational foundation that is sufficiently mature to support automated decisions and actions.
In ServiceNow environments, this means evaluating not only which models or agents will be used, but also the quality of the CMDB, the CSDM model, asset discovery, ITAM data, the knowledge base, existing workflows, access governance, and the processes that will be executed.
Companies with inconsistent processes or unreliable information risk automating existing problems. AI can significantly increase execution speed, but this speed needs to be coupled with adequate controls and data.
What CIOs can take away from the ServiceNow AI Summit 2026
- Enterprise AI has entered a new phase: The focus is beginning to shift from content generation to agents capable of executing tasks.
- AI Control Tower puts governance at the heart of the strategy: Visibility into AI agents, models, and initiatives will be necessary to scale with control.
- Data becomes infrastructure for AI: Agents rely on reliable information to make decisions and take action.
- CMDB, CSDM, ITAM, and ITOM are now integrated into AI readiness: These disciplines provide operational context for automation and intelligence.
- Autonomy requires security: Identities, permissions, auditing, traceability, and oversight need to evolve along with the agents.
- Maturity should not be measured by the quantity of agents: The relevant indicator is the ability to produce operational results in a controlled and repeatable manner.
Asset governance as a foundation for artificial intelligence.
The ServiceNow AI Summit São Paulo 2026 demonstrated a clear evolution in the debate about enterprise artificial intelligence: the discussion is shifting from models and co-pilots to execution, agents, data, and governance.
In this scenario, the quality of the operational foundation becomes the determining factor in how far automation can safely advance.
The Globo case study presented by 4MATT illustrates this logic in asset management. Before seeking autonomy, it is necessary to structure processes, responsibilities, data, and traceability. From this foundation, automation and intelligence can be incorporated with greater context and control.
For ServiceNow environments, the path to artificial intelligence at scale tends to connect disciplines that have historically been treated separately: ITAM, EAM, CMDB, CSDM, ITOM, workflows, knowledge, security, and AI governance.
The expected outcome is not simply to increase the volume of automation. It is to build an operation capable of interpreting context, making decisions, and executing processes using reliable data and clearly defined responsibilities.
Frequently Asked Questions about the ServiceNow AI Summit São Paulo 2026
When did the ServiceNow AI Summit São Paulo 2026 take place? The Learning Labs took place on August 5, 2026, and the main AI Summit was held on August 6, 2026, at the Transamerica Expo Center in São Paulo.
What were the main themes of the ServiceNow AI Summit 2026? The program highlighted AI Control Tower, agent AI, Autonomous IT, AI enterprise governance, agent security, and the data quality necessary for executing intelligent workflows.
What is AI Control Tower in ServiceNow? AI Control Tower is ServiceNow's approach to extending visibility and governance over artificial intelligence agents, models, initiatives, and workflows used by the organization.
What does agentic AI mean? Agent AI describes systems capable of interpreting objectives, using context, and executing tasks or workflows with a certain level of autonomy, within policies and limits established by the organization.
What was 4MATT's participation in the AI Summit São Paulo 2026? 4MATT participated as a Gold sponsor, maintained experts at its booth during the event, and held a private session for executives with Globo on Enterprise Asset Management with ServiceNow.
What case study did 4MATT and Globo present? The private session addressed the evolution of Globo's physical asset management using ServiceNow EAM, including processes related to repair, warranties, relocation, traceability, and disposal.
Why are CMDB and ITAM important for AI? AI agents rely on reliable context to decide and execute actions. CMDB, CSDM, and ITAM help structure information about services, assets, relationships, ownership, usage, costs, and lifecycle.
What is AI-readiness in ServiceNow? AI readiness is the ability to prepare processes, data, architecture, knowledge, security, and governance so that automation and AI agents can operate in a controlled and reliable manner on the platform.
Is Brazil ready for enterprise AI? Data from ServiceNow's 2026 Enterprise AI Maturity Index indicates strong growth in investment and adoption in Brazil, but also reveals gaps in governance, transparency, testing, and risk assessment.
What does the AI Summit São Paulo 2026 leave for the market?
The ServiceNow AI Summit São Paulo 2026 reinforced that the business value of artificial intelligence does not depend solely on the capabilities of the models used. Processes, data, architecture, security, and governance determine the ability to transform intelligence into reliable operational execution.
For organizations using ServiceNow, the evolution to agentic AI increases the relevance of a mature platform, with a structured CMDB, consistent CSDM, governed assets, trusted knowledge, and workflows ready for automation.
4MATT's participation and the experience presented with Globo demonstrate how this principle can be applied to a concrete transformation front: first structuring the governance and traceability of assets in order to, from this base, expand automation, integration, and intelligence throughout the operation.
Data from the ServiceNow AI Summit São Paulo 2026
| Information | Detail |
|---|---|
| Event | ServiceNow AI Summit São Paulo 2026 |
| Learning Labs | August 5, 2026 |
| AI Summit | August 6, 2026 |
| Local | Transamerica Expo Center |
| City | São Paulo/SP |
| Organization | ServiceNow |
| 4MATT's participation | Gold Sponsor |
The official schedule and event information can be found at [website address]. ServiceNow AI Summit São Paulo 2026 website.