From AI Adoption to Automation: The FOX Sports Approach
September 30, 2026

FOX Sports: From AI Experiments to Enterprise AI Operations

When FOX Sports prepared for the expanded FIFA World Cup, the challenge was not simply broadcasting more matches.

The tournament included 48 teams, 104 matches, 16 host cities, and generated more than 11,500 hours of recordings, 23,000 files, and 85,000 subclips. Production teams needed to find specific moments, interviews, and highlights within seconds while delivering content to audiences across multiple platforms in near real time. To support that scale, FOX Sports embedded AI deeply into its production operations, using Gemini-powered search, automated tagging, intelligent content discovery, and agentic workflows that helped teams locate and use content faster than ever before.

The technology challenge was not simply deploying AI. It was making AI useful across a large, distributed workforce.

As FOX Sports explained, the goal was to help more than 1,200 team members quickly find the information they needed while maintaining the reliability expected from one of the world's largest sporting events. Their approach demonstrates something many organizations are now discovering: successful AI adoption requires more than access to powerful models. It requires visibility, governance, and a clear understanding of where AI can create value. 

Before organizations deploy Gemini, AI agents, or enterprise automation initiatives, they first need to understand how AI is already being used and which workflows are ready for deeper automation.

The Real Challenge Is Not Deploying AI

Most organizations already have AI inside their environment. Employees use browser-based AI assistants. Teams experiment with AI productivity tools. Developers install AI coding assistants. Departments adopt workflow automation platforms. Business users increasingly rely on AI features embedded inside applications they use every day.

The challenge is that many organizations cannot see the complete picture. AI adoption often happens faster than governance.

Different teams introduce different tools. Some applications are approved. Others are not. Some employees interact directly with AI platforms, while others use AI through existing productivity tools without realizing it. Before organizations can build enterprise-scale AI experiences like those seen at FOX Sports, they need visibility into what is already happening across their environment.

Understanding AI Usage Before Scaling AI Adoption

The FOX Sports deployment succeeded because the organization understood how AI would support real business workflows.

The objective was not AI for the sake of AI. The objective was helping teams discover content faster, automate repetitive tasks, and support production decisions in real time. AI became valuable because it was connected to meaningful work. 

Organizations pursuing similar outcomes need the same level of understanding. The AI Insights capability within the Google Endpoints Readiness Tool helps organizations gain visibility into AI activity across their environment. It provides insight into installed AI applications, browser-accessed AI tools, local LLMs, workflow automation platforms and browser-integrated AI experiences.

This creates a more complete picture of AI adoption across the enterprise. Instead of relying on assumptions, IT teams can understand which AI technologies are being used, where they are being used and whether they align with organizational policies.

Visibility Is the First Step Toward AI Governance

As AI adoption grows, governance becomes increasingly important. Organizations need to understand not only which AI tools exist within the environment but also whether those tools should be approved for business use.

This challenge becomes more significant as employees adopt AI-powered applications independently. Browser extensions, local AI models, AI workflow platforms, and embedded assistants can all introduce governance and security considerations if they operate outside organizational oversight.

AI Insights helps organizations move beyond simple discovery. By identifying sanctioned and unsanctioned AI technologies across devices and browsers, organizations gain a clearer understanding of where governance policies may need to be strengthened. This allows teams to build AI strategies based on visibility rather than assumptions. For many organizations, this becomes an essential foundation before broader AI initiatives begin.

Why Agentic Workflows Matter More Than Individual AI Tools

One of the most interesting aspects of the FOX Sports story is that the value did not come from a single AI application. The value came from workflows. AI-powered search helped teams find content faster. Automated tagging accelerated asset management. AI-assisted content discovery reduced manual effort. Different capabilities worked together to support larger business processes.

This reflects a broader shift happening across enterprises. Organizations are moving beyond isolated AI tools and toward agentic workflows that span multiple systems, applications, and business processes. At the same time, Gemini Enterprise is making AI agents more persistent. Long-running agents can maintain context, support multi-step tasks, and participate in workflows that continue across hours or even days.

That creates an important question.

Which workflows are actually ready for that level of automation?

Workflow Readiness Should Come Before Workflow Automation

Not every business process should become an AI-driven workflow.

Some processes are highly repetitive and structured. Others depend heavily on human judgment. Some workflows are excellent candidates for automation, while others require more review before AI can be introduced effectively.

This is where Agentic Workflows within the Google Endpoints Readiness Tool provides value. Rather than starting with automation ideas and searching for a use case, organizations can begin by understanding how work currently happens. Teams gain visibility into workflow patterns and can identify processes that may be suitable for future AI-driven automation initiatives.

This creates a more practical path toward agent adoption. Instead of automating based on enthusiasm, organizations can prioritize workflows that already demonstrate strong readiness characteristics.

From AI Visibility to AI Readiness

The FOX Sports story highlights a reality many organizations are now facing. AI is no longer a future initiative. It is already becoming part of how people work. The organizations that succeed will not necessarily be those with the most AI tools. They will be the organizations that understand how AI is being used, where governance is required, and which workflows are genuinely ready for automation.

The Google Endpoints Readiness Tool helps organizations build that understanding.

Through AI Insights, organizations gain visibility into AI adoption across devices, browsers, applications, local models, and workflow platforms. Through Agentic Workflows, they can evaluate workflow readiness before expanding into deeper Gemini-powered automation. Because successful AI adoption does not begin with deploying another AI tool. It begins with understanding the environment where AI will operate. FAQs

1. What can organizations learn from FOX Sports’ AI approach?

FOX Sports shows how AI can support real business workflows through content discovery, automation, and intelligent search at scale.

2. Why is AI usage visibility important?

AI usage visibility helps organizations understand which AI tools, applications, models, and workflow platforms are being used across their environment.

3. How does AI Insights support AI governance?

AI Insights identifies AI technologies across devices and browsers and helps distinguish sanctioned and unsanctioned usage for better governance.

4. What are agentic workflows?

Agentic workflows use AI agents to support multi-step tasks and business processes, often across multiple applications or systems.

5. Why should organizations assess workflow readiness before automation?

Assessing workflow readiness helps organizations identify processes that are suitable for AI automation before investing in more complex agentic workflows.

Senuri Senevirathna

Google Endpoints Readiness Tool

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September 28, 2026

What Roche Shows About Turning CEP Readiness Into Action

Organizations invest heavily in security technologies, yet many still struggle with a fundamental challenge: turning security strategy into operational reality.

A useful example comes from Roche, one of the world's largest healthcare and pharmaceutical companies. As its workforce increasingly relied on browser-based applications and cloud services, the organization needed deeper visibility into browser activity and stronger controls over how sensitive information moved across the web. Traditional security approaches could protect devices and networks, but they often lacked visibility into what was happening inside the browser itself.

The challenge Roche faced is not unique. Many organizations exploring Chrome Enterprise Premium (CEP) have similar goals. They want better browser security, stronger access controls, richer telemetry, and improved visibility into user activity. However, achieving those outcomes requires more than purchasing licenses. It requires a deployment strategy that moves from readiness assessment to implementation efficiently and at scale.

The Security Visibility Challenge

For Roche, browser security was becoming increasingly important because employees were accessing thousands of web-based applications daily. The security team needed a better understanding of how users interacted with corporate data, what actions were taking place within the browser, and where potential risks existed.

After implementing Chrome Enterprise capabilities, Roche gained centralized visibility into browser activity and security events. According to Google's documented customer story, the organization was able to identify suspicious behavior and respond rapidly to potential threats. In one case, Roche detected and stopped an attempt to exfiltrate a large amount of corporate information within hours of enabling the solution.

That outcome highlights an important reality.

Organizations cannot benefit from browser-native security telemetry if their browsers are not properly enrolled, managed, and configured. Security visibility starts long before the first alert appears in a dashboard.It starts with deployment readiness.

The Hidden Work Behind a CEP Deployment

When organizations decide to adopt Chrome Enterprise Premium, the technical objective often seems straightforward.

  1. Enable browser management.

  2. Enroll devices.

  3. Configure reporting.

  4. Activate security capabilities.

  5. Begin monitoring.

In practice, the process is usually more complex. Administrators must determine which devices require enrollment, identify deployment blockers, generate enrollment configurations, configure deployment settings, publish instructions and verify that enrollment has been completed successfully.

These tasks often span multiple tools and administrative workflows.The result is a gap between knowing what needs to happen and actually executing it. Many organizations can identify readiness issues. Fewer can move from readiness findings to deployment actions quickly and consistently.

Learning From the Roche Journey

If Roche were beginning its Chrome Enterprise Premium journey today, the first requirement would not be threat detection.It would be understanding deployment readiness.Before browser telemetry can reach security teams, organizations need answers to critical questions.

Are browsers enrolled?

Are management policies configured?

Are reporting capabilities enabled?

Are target devices ready for deployment?

Are organizational units correctly structured?

Without clear answers, deployment projects can slow down before security outcomes are ever realized.This is where the Google Endpoints Readiness Tool helps organizations establish a foundation for Chrome Enterprise Premium adoption.

The platform enables IT teams to assess their current environment, identify readiness gaps, and understand what must be addressed before deployment begins. Rather than relying on assumptions, organizations gain data-driven visibility into their readiness posture.That visibility creates a more structured path toward deployment.

From Readiness Findings to Deployment Execution

Historically, readiness assessments and deployment activities have often existed in separate workflows.An assessment identifies what needs attention. Administrators then switch tools to perform the required deployment tasks.The process works, but it creates additional operational overhead.

The latest deployment capabilities within the Google Endpoints Readiness Tool help reduce that gap.

Organizations can move from readiness insights directly into deployment workflows from the same platform. Instead of treating assessment and deployment as disconnected activities, teams can manage both stages within a more unified experience. For organizations pursuing outcomes similar to Roche's, this creates a practical advantage.The faster teams can move from identifying readiness gaps to enrolling and configuring browsers, the sooner they can begin realizing the security benefits that Chrome Enterprise Premium provides.

Simplifying Deployment with AI-Assisted Workflows

Large-scale deployments often involve repetitive administrative tasks.

  • Enrollment information must be located.

  • Configuration details must be reviewed.

  • Deployment settings must be verified.

  • Instructions must be published.

  • Progress must be monitored.

The Google Endpoints Readiness Tool introduces AI-assisted workflows designed to simplify these operational activities. Through AI-powered interactions, administrators can retrieve deployment-related information, review readiness insights, and support deployment actions through natural language experience.

The objective is not to remove administrative control.Enterprise deployments require governance, approval processes, and accountability.Instead, AI-assisted workflows help reduce manual effort while keeping administrators in control of deployment decisions.For IT teams managing large environments, this can significantly improve operational efficiency while maintaining deployment oversight.

Why Deployment Speed Matters for Security Outcomes

The Roche story demonstrates the value of browser visibility.

Once browser telemetry became available, security teams gained the insight needed to investigate suspicious activity and respond quickly. The ability to detect and stop a significant data exfiltration attempt illustrates how browser-level visibility can strengthen an organization's overall security posture.

However, that visibility depended on successful deployment.

  • Browsers needed to be managed.

  • Reporting needed to be enabled.

  • Security capabilities needed to be configured.

Only then could telemetry flow into security operations.This is why readiness and deployment are closely connected.Organizations often focus on the destination, whether that is stronger security, better governance, improved access controls, or richer browser telemetry.

But achieving those outcomes requires an efficient path from assessment to implementation.The Google Endpoints Readiness Tool helps create that path.By combining readiness assessment, deployment workflows, deployment visibility, and AI-assisted execution, organizations can reduce the operational friction that often slows Chrome Enterprise Premium initiatives. 

Turning Readiness Into Results

The Roche case demonstrates what becomes possible when organizations gain meaningful visibility into browser activity. Better insights lead to faster investigations, stronger governance, and improved security outcomes.

But those benefits do not begin with security alerts.Organizations first need to understand their environment, identify deployment requirements, and successfully enroll and manage their browser fleet.

The Google Endpoints Readiness Tool helps support that journey by connecting readiness insights with deployment execution. From identifying gaps to initiating deployment actions and monitoring progress, the platform provides a more direct route from assessment to implementation.Because for organizations pursuing Chrome Enterprise Premium, readiness is not the final destination.It is the starting point.

FAQs

1. What is Chrome Enterprise Premium (CEP)?

Chrome Enterprise Premium is Google's enterprise browser security and management solution, providing capabilities for secure access, browser management, and visibility into browser activity.

2. Why is deployment readiness important for CEP?

Deployment readiness helps organizations identify enrollment, configuration, policy, and device-related gaps before implementing CEP at scale.

3. How does the Google Endpoints Readiness Tool support CEP deployment?

It helps IT teams assess readiness gaps and connect those findings with deployment workflows, making it easier to move from assessment to implementation.

4. How can AI-assisted workflows simplify CEP deployment?

AI-assisted workflows can help administrators retrieve deployment information, review readiness findings, and support deployment actions through natural-language interactions.

5. What can organizations gain from successful CEP deployment?

Successful deployment can provide stronger browser visibility, security controls, reporting, and telemetry that help security teams monitor and respond to potential risks.

Google Workspace Migration: Identify User Dependencies Early
September 24, 2026

Before You Move to Google Workspace, Know What Your Users Depend On

A Google Workspace migration is more than moving email, calendars, and files. The bigger challenge is understanding how employees work today and which applications, spreadsheets, browser extensions, and workflows they depend on every day. When those dependencies are discovered late, migration teams may need to change rollout plans, investigate applications, or prepare specific user groups at the last minute. That is why understanding the existing endpoint environment should be part of Workspace migration planning from the beginning.

The Google Endpoints Readiness Tool helps IT teams build that visibility across their environment. By examining application and usage information across users and devices, teams can identify areas that may require additional assessment before migration. This makes it possible to plan around actual usage rather than assuming every employee has the same requirements. For large organizations, that difference can significantly influence how migration waves are structured.

What Happens When Business Dependencies Are Hidden?

Real migration projects show why application and workflow discovery matters. For example, Veolia Australia and New Zealand assessed applications as part of its Google Workspace transformation, including server-based business applications, applications developed by users, and applications installed on user devices. The user-developed applications included macros embedded in products or databases, and the project involved assessing, redesigning and testing those applications.

This is a practical example of why an application inventory alone is not enough. A department may appear to use a standard spreadsheet or application, while behind it sits an automated workflow that supports reporting, calculations, approvals, or other business processes. If that dependency is not identified before migration, the technical team may only discover its importance when users are preparing to move. Readiness information gives migration teams an opportunity to investigate those dependencies while there is still time to plan.

Macro Usage Can Change the Migration Conversation

Spreadsheet macros are a particularly useful example because they can represent business logic hidden inside everyday documents. In one documented Google Workspace migration case, the migration team reviewed internal documents and found that no complex Excel macros were being used, which allowed the organization to move more easily toward Google Sheets. The case also recommended auditing spreadsheets beforehand because organizations with more complex macro dependencies may need a different migration approach.

For an IT team preparing a larger environment, the important question is therefore not simply whether spreadsheets exist. The question is where macro-related dependencies exist and which users or business functions rely on them. Those findings can then lead to a closer review of the affected workflows and help determine whether they can transition directly, require modification, or need additional planning. Identifying the dependency early is valuable because it gives the business more time to decide what should happen next.

A Finance Team and an Operations Team May Need Different Plans

Consider a company preparing to migrate 2,000 employees to Google Workspace. Most users may primarily work with email, documents, meetings, and browser-based applications, while a smaller finance group may depend on complex spreadsheet workflows. Another operations team may rely on a specialized desktop application, and a sales team may depend on particular browser extensions.

A single migration plan could easily overlook those differences.

With endpoint and application readiness information, IT teams can investigate:

  • Application usage across users and devices

  • Macro-usage presence that may require further review

  • Browser and extension usage supporting daily workflows

  • Department-specific applications that may need compatibility assessment

  • Users and devices associated with particular dependencies

This allows migration teams to organize preparation around real usage patterns. Instead of treating the entire organization as one migration group, teams can identify where additional assessment is needed before each migration phase.

Prepare the Environment Before You Move the Users

Google Workspace migrations can involve thousands of users, multiple departments, and very different business workflows. Google documents phased migration as a way to manage users and data according to factors such as organization size, complexity, and migration requirements. Real customer examples also demonstrate the scale of these projects, including Turner Industries' migration of 4,800 employees, where comprehensive planning and change management were used to support the transition.

The Google Endpoints Readiness Tool adds another layer of visibility before those migration waves begin. By understanding application usage, macro-related dependencies, browser activity, and user or device context, IT teams can identify where additional preparation may be required. That means migration planning can be based on the environment employees actually use rather than assumptions about how they work.

Before you move users to Google Workspace, understand what they depend on today.

FAQ

Why should macro usage be checked before a Workspace migration?

Macros can contain business logic that supports important workflows, reporting, and automation. Identifying macro-related dependencies early gives IT teams time to investigate those workflows and determine the appropriate migration approach. Through the assessment, users can see whether macros have been used or not.

Does every user need the same migration plan?

No. Different departments can have very different application and workflow dependencies. Readiness information can help teams identify those differences and use them when organizing migration phases.

What should teams assess besides email and files?

Application usage, macro-related workflows, browser activity, extensions, and department-specific applications can all provide useful context. These areas can reveal dependencies that may not be visible from a basic data migration inventory.

Discover AI Usage Across Your Organization
September 22, 2026

Shadow AI Is Becoming a Visibility Challenge for Enterprises

Shadow AI Is Becoming a Visibility Challenge for Enterprises

AI adoption is expanding rapidly across organizations, but IT teams may not always have a complete view of where AI is being used. Employees can access public AI tools, browser-based applications, local AI models, and automation platforms outside traditional software procurement processes.

Larridin’s September 2026 analysis highlights this growing visibility challenge, citing Writer’s 2026 enterprise AI adoption research, which found that 35% of employees had entered proprietary information into public AI tools. The same research found that 67% of executives believed their organization had experienced a data leak or security breach because of an employee using an unapproved AI tool.

The Challenge of Building an AI Inventory

Traditional software inventories are built around applications that IT teams install, manage or approve. AI usage can be much broader because employees can access tools directly through browsers or adopt new AI services without going through established procurement processes. This makes it difficult to understand which AI applications are being used, how they are being accessed, and whether they are sanctioned by the organization. Larridin also reports that enterprise monitoring can uncover three to five times more AI usage than organizations initially expect.

An accurate inventory is an important starting point for AI governance. Before an organization can review how an AI application is being used, assess its relevance to internal policies, or determine whether additional controls are required, it needs visibility into what is actually present across the environment. This becomes increasingly important as AI usage expands beyond traditional installed applications. A broader view needs to include both managed and browser-accessed AI activity.

AI Usage Extends Beyond Installed Applications

AI applications are no longer limited to software installed directly on employee devices. Employees can interact with AI through websites, browser-based applications, automation platforms and locally running language models. These different access methods can create separate areas of AI activity that are difficult to understand through conventional application inventories alone. Identifying these sources provides a more complete view of how AI is being used across an organization.

Google Endpoints Readiness Tool’s AI Insights section provides visibility into AI usage across the organization to support AI governance and decision-making. It brings together information about installed AI applications, web-accessed AI, local AI models, and workflow automation platforms. Organizations can also view direct and indirect AI usage and understand the governance status associated with identified AI applications. This gives IT teams a centralized view of AI activity instead of relying only on known or manually reported applications.

From Organization-Level Visibility to Device-Level Details

Understanding the overall AI footprint is only the first step. IT teams may also need to determine where specific AI activity is occurring and what applications or platforms are involved on individual devices. Google Endpoints Readiness Tool allows administrators to drill down from organization-level AI insights into device-level details, providing additional context around the AI activity detected on each device. This helps connect broad AI usage patterns with the specific devices and applications behind them.

Device-level insights can include installed AI applications, web-based AI applications, local AI models, and agentic automation platforms. Administrators can also review information such as AI categories, usage types, governance status, and application usage details. This level of visibility can help teams identify where AI is being used and understand the different ways employees interact with AI tools. It also provides a more practical starting point for reviewing individual areas that require attention.

Supporting AI Governance with Sanctioning

Visibility becomes more useful when organizations can apply their own governance context to the AI activity they discover. Google Endpoints Readiness Tool’s Report Generator includes AI Sanctioning, where administrators can review discovered AI applications, workflow platforms, local LLMs, and browser-integrated AI. These items can be classified as Sanctioned or Unsanctioned, helping organizations distinguish tools that have been approved from those that may require further review. Administrators can also configure whether identified AI activity is considered direct or indirect where applicable.

This classification does not determine whether an AI application should ultimately be allowed or restricted. Instead, it gives organizations a structured way to understand their AI footprint and identify applications that may need additional assessment. Combined with device-level visibility, sanctioning helps connect AI discovery with the organization’s own governance approach. The result is a more contextual view of AI activity across the environment.

Turning AI Visibility Into Readiness Insights

AI adoption will continue to introduce new applications, workflows, and ways of working. As this happens, relying only on manually maintained software inventories can make it harder to understand the actual AI landscape within an organization. Continuous visibility can help IT teams identify AI activity across different access methods and understand where additional governance review may be needed.

AI Insights in Google Endpoints Readiness Tool brings this visibility into a broader readiness assessment, helping organizations understand AI activity across their environment. From installed applications and browser-accessed AI to local models, workflow platforms, and governance classifications, Google Endpoints Readiness Tool provides the insights needed to build a clearer picture of AI usage. Explore AI Usage Insights with Google Endpoints Readiness Tool. Visit Google Endpoints Readiness Tool

Frequently Asked Questions

What is Shadow AI?

Shadow AI refers to AI tools or services used within an organization without going through established IT approval or governance processes.

Why is AI visibility important?

Visibility helps organizations understand which AI tools are being used, how they are accessed, and where additional governance or review may be required.

What does Google Endpoints Readiness Tool AI Insights identify?

Google Endpoints Readiness Tool AI Insights provides visibility into installed AI applications, web-accessed AI, local AI models, workflow platforms, and AI usage and governance information.

Can Google Endpoints Readiness Tool show AI usage at the device level?

Yes. Google Endpoints Readiness Tool allows administrators to drill down into individual devices to review detected AI applications, web-based AI, local models, and automation platforms.

Can administrators classify AI applications?

Yes. Google Endpoints Readiness Tool’s Report Generator provides AI Sanctioning options that allow administrators to classify identified AI applications and related AI technologies as Sanctioned or Unsanctioned.

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