The ITAM & CMDB + AI Forum 2026 This is an in-person event promoted by 4MATT, a ServiceNow Elite Partner in Brazil, that brings together clients, partners, and experts to discuss how IT Asset Management (ITAM), CMDB, and governance need to evolve in the face of the expansion of agency AI in companies. The second edition was held in [date/time]. August 11, 2026, in São Paulo, featuring presentations from Bradesco, ServiceNow, Rede Globo, Vale, Symbios, and 4MATT.
The event went beyond the traditional discussion of inventory, data quality, and operational efficiency. The debates showed that ITAM and CMDB are taking on a more strategic role: providing the necessary context for companies to control costs, assess risks, meet regulatory requirements, and scale the use of artificial intelligence more safely.
The August 11th program was held in two sessions. In the morning, the Forum hosted executives and professionals from the financial and insurance sectors, with discussions on technology procurement, security, risk, compliance, and operational resilience. In the afternoon, the agenda was expanded to include all industries, with presentations on agentic AI, Enterprise Asset Management (EAM), software asset management (SAM) and hardware asset management (HAM), CMDB evolution, and new artificial intelligence governance models.
Who presented at the ITAM & CMDB + AI Forum 2026?
The Forum featured seven presentations, combining real-world experiences from large Brazilian companies, platform insights, and perspectives on artificial intelligence governance.
| Speaker | Enterprise | Central theme |
|---|---|---|
| Hassã Orra and Reginaldo Mendes | Bradesco | Creation of the Technology Hiring Tribe and evolution of the process to reduce hiring lead time and expired contracts. |
| Aline Grotewold Bueno | ServiceNow | CMDB as a foundation for security, risk, and operational resilience, including the pillars of DORA (Digital Operational Resilience Act) and the prioritization of vulnerabilities considering their real impact on the business. |
| Thaina Maia | Globo Network | Using ServiceNow EAM to manage approximately 120,000 media assets and improve the operational processes associated with those assets. |
| CMDB Team | OK | A decade of evolution for CMDB, transitioning from manual inventory to a strategic database integrated with CSDM, business services, and new artificial intelligence initiatives. |
| Gustavo Zappi | 4MATT | The AI agent as a new class of enterprise asset, with ownership, cost, risk, dependencies, and lifecycle that need to be governed. |
| Ana Flavia Pimenta Braasch | Symbios | Governance of agency AI, differences between copilots and autonomous agents, Shadow AI, regulation and principles for the responsible adoption of artificial intelligence. |
| Marcelo Theophilo | 4MATT | Evolution of the technology and AI market, new cost and risk challenges, and a proposal for federated governance placing ITAM and CMDB at the center of the model. |
CMDB ceases to be an inventory and becomes a decision infrastructure.
The Vale case study concretely demonstrated the evolution of the CMDB's role. Over approximately a decade, the organization progressed from predominantly manual processes to a structure capable of relating configuration items, applications, services, and business context. This movement brings the CMDB closer to... Common Service Data Model (CSDM) and expands its use to processes that go far beyond the operational management of infrastructure.
Aline Grotewold Bueno's presentation from ServiceNow reinforced this perspective by relating CMDB, security, risk, and operational resilience. The better the context regarding assets, services, and their dependencies, the greater the organization's ability to understand the real impact of an incident or vulnerability—and this changes the very logic of prioritization.
Without context, an organization might try to fix thousands of vulnerabilities using only technical criteria. Instead, companies can use the context of... CMDB to identify which assets support critical services and which exposures effectively represent the greatest risk to the business, focusing efforts where the business risk is greatest. This relationship between active + configuration + service + risk significantly expands the strategic role of ITAM and CMDB.
The CMDB therefore goes beyond simply answering the question "what do we have?" and begins to help answer "what really matters to the business?".
Agency AI creates a new class of enterprise asset.
Another central theme of the Forum was the need to review the traditional concept of technology assets. Hardware, software, SaaS applications, and cloud resources already have relatively consolidated processes for identification, acquisition, control, use, and decommissioning. With the arrival of agentic AI, a new asset category emerges that is not yet covered by these processes.
The thesis presented by Gustavo Zappi, Head of AI at 4MATT, is that an AI agent possesses attributes equivalent to those of other technological assets managed by organizations—and that, therefore, it should enter the same governance cycle.
| Governance dimension | Traditional assets (hardware, software, SaaS, cloud) | AI Agent |
|---|---|---|
| Owner and purpose | Defined in the contract, cost center, and procurement process. | Often undefined, as the agent originates within a specific business area. |
| Cost | Licenses, users, contracted capacity | Tokens, API calls, processing, and volume of activities performed. |
| Access | System credentials and permissions | Credentials, permissions, tools, data, knowledge sources, and memory. |
| Dependencies | Infrastructure, applications and services | AI model, integrations, applications and business services |
| Controls | Usage and compliance policies | Guardrails and defined range level |
| Behavior | Executes deterministic instructions. | Interprets information, makes decisions, uses tools, and executes actions. |
| Life cycle | Acquisition, use, renewal and deactivation | Creating, reviewing, updating, and deactivating templates. |
The relevant difference is in the last line: An agent doesn't just run software. It can interpret information, make decisions, use tools, and perform actions within the business environment. It is this ability to act that increases the need for governance and distinguishes agentic AI from any previous asset.
“AI is becoming the new Microsoft Office. Just as an entire generation needed to learn Word, Excel, and PowerPoint to work productively, now professionals and companies will have to learn how to incorporate AI into their daily work. For software asset managers, there is an important advantage in this comparison: we already know the way. We need to find out where AI is being used, who is responsible for it, how much it costs, what risks it brings, and how to manage its lifecycle, just as we do with other technological assets.”
— Marcelo Theóphilo, 4MATT
The comparison reinforces one of the main points discussed at the Forum: although the technology is new, many of the fundamentals needed to govern it already exist. Inventory, ownership, costs, risks, contracts, and lifecycle remain essential disciplines—now applied to a new asset class.
From Shadow IT to Shadow AI
Ana Flavia Pimenta Braasch's presentation added another dimension to the debate: the speed at which artificial intelligence tools and agents can enter organizations without going through traditional governance models. The problem is similar to the phenomenon of Shadow IT and Shadow SaaS, but potentially more complex.
Node Shadow AI, Employees and business areas adopt models, co-pilots, or agents without Security, Architecture, ITAM, Purchasing, or Legal having adequate visibility into their use. When these agents are able to access corporate information or execute actions autonomously, the lack of visibility ceases to represent merely a cost or licensing issue.
It also involves issues such as:
- access to sensitive data;
- intellectual property;
- privacy;
- automated decisions;
- responsibility;
- operational risk;
- compliance;
- security.
In this scenario, discover What agents exist, who is responsible for them, and what resources can they access? becomes a new dimension of IT asset management, with direct implications for the areas of Security and software asset management (SAM).
ITAM will now also control the cost of agency AI.
Artificial intelligence adds another financial challenge. In traditional software, a large part of the costs can be associated with contracts, licenses, users, or contracted capacity. In generative and agentic AI, a significant portion of consumption varies according to tokens, API calls, processing, models used, and the volume of activities performed by the agents.
This brings agentic AI closer to the discussions that FinOps brought to the cloud: consumption can grow rapidly if there are no mechanisms for visibility, ownership, and control. During the Forum, Marcelo Theóphilo presented this scenario as a natural extension of ITAM's responsibility.
If an asset exists that is capable of continuously consuming financial resources, it needs to have at least Owner, purpose, cost, risk, and life cycle. defined. However, the management of this set cannot depend exclusively on a single area.
Agency AI governance needs to be federated.
The closing of the Forum solidified this concept through a proposal of federated governance of artificial intelligence. Instead of creating a central area responsible for all AI-related decisions, the model distributes responsibilities among different corporate functions.
| Area | Responsibility in the governance of agency AI |
|---|---|
| Business | It defines the agent's objective and is responsible for the expected outcome. |
| ITAM and CMDB | They manage inventory, ownership, relationships, costs, and lifecycle. |
| Security | Assesses access, exposure, identity, and risks. |
| Architecture | Defines technical standards, models, integrations, and permitted technologies. |
| Purchasing and Legal | They deal with contracts, suppliers, intellectual property, and regulatory aspects. |
This design allows for the creation of controls without transforming governance into an obstacle to innovation. The goal is not to prevent the use of artificial intelligence, but to allow it to be expanded with... traceability, accountability and trust.
Case studies demonstrate the practical application of these concepts.
The case studies presented during the Forum demonstrated that this transformation is already happening in complex business environments.
The Globo Network He presented his journey managing approximately 120,000 media assets using ServiceNow EAM, structuring processes and increasing visibility over assets that are directly involved in content production operations.
The Bradesco The study demonstrated the creation of a Technology Procurement Tribe to transform a critical acquisition and contract management process, reducing lead times and increasing control over expired contracts.
The OK, in turn, presented a long-term vision of CMDB, demonstrating how a discipline that is initially operational can evolve into becoming part of the organization's service architecture and data strategy.
In the projects presented by Globo and Bradesco, 4MATT participated as an implementation partner, connecting architecture, platform, and process transformation. The company is... ServiceNow Elite Partner in Brazil, has more than 80 certified specialists and received the ServiceNow Technology Excellence Partner Award 2024–2025.
The new role of ITAM and CMDB in the age of agency AI.
Historically, many organizations primarily associated ITAM with inventory, contracts, and licensing, while CMDB was often treated as an operational ITSM need. The expansion of cloud, SaaS, security, and now agency AI is broadening this responsibility.
ITAM will now deal with not only what the company owns, but also:
- how much does it cost;
- who is responsible;
- What risk does it represent?;
- how it is being used;
- when it should be removed from the environment.
The CMDB adds the context:
- Where is it?;
- what it relates to;
- Which service does it support?;
- What dependencies does it have?;
- What would be the impact of a failure?.
Together, ITAM and CMDB create a layer of business context that becomes even more relevant in AI-driven environments.
What can companies do now?
For organizations already experimenting with AI copilots and agents, the discussion doesn't need to begin with a large governance structure. A first step could be to identify:
- Which AI agents and solutions are already being used?;
- who is responsible for each initiative;
- What data and systems do these solutions access?;
- Which models and suppliers are involved?;
- What costs are associated with its operation?;
- what actions can they perform;
- What risks do they represent for business services?;
- What is the process for its review or deactivation?.
This initial inventory allows us to transform an abstract discussion about agency AI governance into an operational process, executed on the same database that underpins it. the ServiceNow platform, ITAM and CMDB.
ITAM + CMDB + AI: context before automation
The main conclusion of the ITAM & CMDB + AI 2026 Forum is that a company's ability to use artificial intelligence at scale increasingly depends on the quality of the context available to those systems. Automation based on inconsistent data only executes bad decisions more quickly.
Agent AI makes this issue even more relevant because agents can increasingly interpret information and execute actions within business processes. Therefore, ITAM and CMDB take on a strategic position in AI architecture.
ITAM provides control.
CMDB provides context.
Governance provides trust.
AI transforms this set of elements into a scalable solution.
Frequently Asked Questions about the ITAM & CMDB + AI 2026 Forum
What is the ITAM & CMDB + AI Forum?
The ITAM & CMDB + AI Forum is an in-person event promoted by 4MATT that brings together clients, experts, and partners to discuss IT Asset Management, CMDB, governance, security, and artificial intelligence. In 2026, the event reached its second edition.
When and where was the ITAM & CMDB + AI 2026 Forum held?
The second edition of the ITAM & CMDB + AI Forum was held on August 11, 2026, in person in São Paulo (SP), in two sessions: the morning dedicated to the financial and insurance sectors, focusing on compliance and operational resilience, and the afternoon open to all industries.
Which companies participated in the presentations?
The program included representatives from Bradesco, ServiceNow, Rede Globo, Vale, Symbios and 4MATT, in seven presentations that combined real-world customer case studies and discussions on technology, risk, and governance.
What is agentive AI?
Agent AI is the category of artificial intelligence in which the software not only generates content or answers questions, but also interprets information, makes decisions, uses tools, and executes actions within an environment with some degree of autonomy. It is this ability to act that differentiates an agent from a co-pilot.
Why can AI agents be considered IT assets?
Because they possess characteristics that need to be managed throughout their lifecycle, such as ownership, purpose, cost, technology used, access, dependencies, and risk. Unlike traditional assets, however, agents can also interpret information, make decisions, and execute actions.
What is the role of the CMDB in AI governance?
The CMDB provides context about applications, infrastructure, services, and dependencies used by AI solutions and agents. This relationship helps to understand impact, criticality, and risk, as well as supporting security and governance processes.
What is ITAM's role in managing artificial intelligence?
ITAM expands its processes to include AI agents, models, and services in the technology inventory, associating ownership, cost, suppliers, contracts, usage, risk, and lifecycle with each initiative.
How to control the cost of agency AI?
Control begins by assigning ownership and purpose to each agent and by measuring actual consumption, which in agentic AI varies according to tokens, API calls, processing, and volume of activities performed. It's the same logic that FinOps applied to the cloud, now under the responsibility of ITAM.
What is Shadow AI?
Shadow AI is the use of artificial intelligence tools, models, or agents without adequate visibility or governance from the areas responsible for technology, security, architecture, procurement, or compliance.
What does federated AI governance mean?
It's a model in which different areas share responsibilities. Business is responsible for purpose and results; ITAM and CMDB maintain inventory and context; Security handles risks and access; Architecture defines standards; and Procurement and Legal control contractual and regulatory aspects.
Why do ITAM and CMDB become more important with agency AI?
Because agents need context to operate and controls to be used safely. ITAM provides visibility and governance over assets, while CMDB relates these assets to the business systems, applications, and services they may impact.