Microsoft is tightening the screws on Microsoft 365 Copilot at exactly the right moment: after the initial wave of enthusiasm, enterprises are now asking harder questions about what the assistant can see, what it can say, and how much telemetry they get back in return. The latest update adds Purview DLP controls, oversharing remediation, and new analytics that help admins see how Copilot is actually being used across the business, not just how it was marketed. In other words, Microsoft is treating Copilot less like a novelty feature and more like a governed enterprise workload, with controls to match.
Microsoft 365 Copilot started as a productivity story, but it has rapidly become a governance story too. The reason is simple: once an AI assistant can summarize mail, search internal content, draft responses, and work across repositories, it stops being a standalone app and becomes a high-speed interface to the organization’s permissions model. If those permissions are messy, the AI does not create the problem, but it makes the exposure easier to see and much harder to ignore. That is why Microsoft’s current messaging has shifted from pure innovation to controlled adoption.
This latest Copilot update fits into a broader Microsoft pattern that has emerged over the last several months: secure the identities, secure the data, then expose the usage. Microsoft has been pushing identity governance, shadow tenant controls, continuous access, and Purview-based data protection as the foundations for AI adoption. The company’s own framing makes clear that AI-era security is not just about blocking malicious prompts; it is about fixing the environment that the model inherits.
The Petri report shows this shift in practical terms. Microsoft is introducing Purview Data Loss Prevention support for Microsoft 365 Copilot, bulk remediation for overshared links, richer Copilot usage analytics, dashboard upgrades, and usage-based targeting for organizational messaging. Most of the features are already generally available for commercial customers, while some capabilities remain in public preview and are expected to widen soon. That combination matters because it suggests Microsoft is trying to move from policy theory to policy operations.
There is also a bigger market context here. Enterprise AI is no longer being judged only on quality of output; it is being judged on how well it behaves inside existing compliance frameworks. The more Copilot gets used for sensitive work, the more security leaders will demand visibility into prompts, access paths, sharing links, and downstream risk. Microsoft appears to understand that the next phase of Copilot adoption will be won or lost on trust, not just utility.
In that sense, this release is less about “new features” than about institutionalizing AI. The company is building the administrative scaffolding that enterprises need before they will let AI touch more critical data. That scaffolding includes policy controls, analytics, remediation workflows, and communication tools that can push guidance to the right users at the right time.
Microsoft’s approach acknowledges that reality. The company is effectively saying that data governance has to move upstream into the assistant experience, not just downstream into logs and incident response. That is an important distinction because it changes the security conversation from “What got leaked?” to “What should never have been surfaced in the first place?”
The same logic applies to web grounding. If Copilot can use the web to enrich answers, organizations need a way to stop sensitive internal data from being blended into external searches or responses. That is why DLP for AI is becoming a workflow control, not merely a classification feature.
The key point is that Microsoft is not asking admins to chase every single bad permission manually. Instead, it is giving them a way to remediate broadly and consistently. That is a pragmatic recognition that the problem is usually not one or two risky files; it is a permission culture that has drifted for years.
The significance here is subtle but real. Once analytics show who is using Copilot, how often, and for what kinds of tasks, organizations can start treating AI usage like any other enterprise system with measurable value and measurable risk. That is the sort of capability that helps security, compliance, and business teams stop arguing in the abstract and start looking at actual adoption patterns.
That is why Purview’s role matters so much. Microsoft is trying to secure the path to the data, not just the file object. That is a much more realistic model for AI-enabled work, where the risk is often not a direct file download but a synthesized answer, an exported summary, or a prompt that unlocks a sensitive context the user should not have assembled on their own.
This shift also changes how admins think about policy enforcement. Instead of relying on coarse directory permissions alone, they can use data-loss controls to shape the AI experience itself. That is more precise, but it also raises the bar for policy design.
But there is a broader operational implication too. Once Purview sits in the middle of AI workflows, policy teams will need to decide what kinds of content are safe for AI to summarize, what should trigger warnings, and what should be blocked outright. That means AI governance will increasingly depend on business context, not just data type.
In practice, that will force organizations to make some hard calls:
That balance is the whole game. Too little control, and Copilot becomes a liability. Too much friction, and users simply route around it. Microsoft’s challenge is to make governance feel like part of the experience rather than an obstacle to it.
That change has enormous consequences for enterprise administration. A stale sharing link that sat unnoticed for months can become a live risk the moment Copilot starts indexing the same repository. What used to be a low-priority housekeeping issue is now a governance liability.
This is also why Microsoft’s focus on bulk remediation is smart. Security teams do not have the luxury of touching every permission manually, especially in large tenants. They need scalable actions that can reduce the blast radius quickly, even if perfect cleanup has to happen later.
Bulk action changes the economics of response. Instead of triaging one suspicious asset at a time, admins can take wide corrective action based on policy. That is essential in environments where Copilot is amplifying hidden exposure across SharePoint, OneDrive, Teams, and connected services.
It also signals that Microsoft expects customers to use Copilot at serious scale. If the company believed adoption would stay limited to a few pilot groups, it would not need to emphasize remediation tooling so heavily. The existence of these controls is itself a clue about the size of the problem Microsoft anticipates.
That matters because many AI rollouts will fail not from lack of enthusiasm, but from uneven adoption. Some teams will embrace Copilot immediately, while others remain skeptical or heavily constrained by compliance requirements. Analytics help administrators understand that gap instead of guessing.
It also gives IT a better way to defend the investment. If the dashboard can show productivity gains, user satisfaction, and adoption trends, then Copilot moves from “new software” to “measurable platform initiative.” That is much easier to justify to executives.
That kind of insight can change training and policy design. If employees are using Copilot mostly for summarization but not for action, the organization can tailor guidance accordingly. If certain teams are using it heavily for sensitive operational work, that may trigger tighter controls or more targeted education.
The caveat, of course, is that analytics can become surveillance if mishandled. Enterprises will need to be careful not to turn productivity insight into a trust problem. Visibility is useful; creepiness is not.
That makes the feature more practical. Security teams can compare AI usage against incident data, DLP events, or identity risk metrics. Business leaders can compare adoption against department-level performance measures. The value is in correlation, not just collection.
This is especially important during the early phases of deployment, when users are still forming habits. A well-timed message can prevent a lot of unnecessary help-desk friction later. It can also reduce the impulse to bypass approved tools in favor of consumer AI.
The practical upside is obvious. Admins can send guidance to power users, cautionary notes to high-risk groups, and adoption tips to teams that are underusing the tool. That creates a more mature rollout than blanket broadcast emails ever could.
That sort of targeting is exactly how enterprise software should work in 2026. Blanket policy announcements rarely land well. Context-aware guidance is more likely to get read, understood, and acted on.
It also mirrors a broader trend in Microsoft’s AI strategy: use analytics to inform governance, and use governance to improve adoption. The company is trying to close the loop rather than leaving security and enablement as separate silos.
That means the best governance strategy is not only restrictive. It is also communicative. Microsoft appears to be acknowledging that, and that is a good sign for enterprises that want secure adoption rather than sterile compliance theater.
The important thing is that these are not abstract benefits. They address the exact barriers that have slowed Copilot rollouts in many organizations: fear of leakage, fear of poor permissions hygiene, and fear of deploying AI without a usable governance model. Microsoft is attacking all three.
That should help larger customers accelerate adoption, especially in regulated sectors. Finance, healthcare, legal, public sector, and highly matrixed global enterprises all tend to move slowly unless the control story is strong.
That invisibility is both a strength and a weakness. It makes the product feel seamless, but it can also hide the degree to which enterprise AI depends on a very sophisticated trust stack. The average user may think Copilot is “just there,” when in reality it is being continuously shaped by policy, telemetry, and remediation logic.
That gap between perception and infrastructure is where Microsoft has real leverage. If the company can keep the experience simple while making the backend much more governable, it can satisfy both the user and the CISO.
Microsoft’s advantage is that it already owns the productivity stack, the identity layer, and much of the data governance stack. That creates a built-in control plane that competitors have to assemble piece by piece. The market may still tolerate best-of-breed tools, but platform-native governance is a powerful selling point.
What to watch next:
Microsoft’s latest Copilot update is therefore best understood as a quiet but important maturation step. The company is not just making Copilot safer; it is making it administrable, auditable, and easier to justify in the enterprise. That is the real milestone, because at scale, the future of AI adoption will belong to the vendors that can prove their tools are not only smart, but governable.
Source: Petri IT Knowledgebase Microsoft 365 Copilot Gets Purview DLP Controls and New Analytics
Microsoft 365 Copilot started as a productivity story, but it has rapidly become a governance story too. The reason is simple: once an AI assistant can summarize mail, search internal content, draft responses, and work across repositories, it stops being a standalone app and becomes a high-speed interface to the organization’s permissions model. If those permissions are messy, the AI does not create the problem, but it makes the exposure easier to see and much harder to ignore. That is why Microsoft’s current messaging has shifted from pure innovation to controlled adoption.This latest Copilot update fits into a broader Microsoft pattern that has emerged over the last several months: secure the identities, secure the data, then expose the usage. Microsoft has been pushing identity governance, shadow tenant controls, continuous access, and Purview-based data protection as the foundations for AI adoption. The company’s own framing makes clear that AI-era security is not just about blocking malicious prompts; it is about fixing the environment that the model inherits.
The Petri report shows this shift in practical terms. Microsoft is introducing Purview Data Loss Prevention support for Microsoft 365 Copilot, bulk remediation for overshared links, richer Copilot usage analytics, dashboard upgrades, and usage-based targeting for organizational messaging. Most of the features are already generally available for commercial customers, while some capabilities remain in public preview and are expected to widen soon. That combination matters because it suggests Microsoft is trying to move from policy theory to policy operations.
There is also a bigger market context here. Enterprise AI is no longer being judged only on quality of output; it is being judged on how well it behaves inside existing compliance frameworks. The more Copilot gets used for sensitive work, the more security leaders will demand visibility into prompts, access paths, sharing links, and downstream risk. Microsoft appears to understand that the next phase of Copilot adoption will be won or lost on trust, not just utility.
In that sense, this release is less about “new features” than about institutionalizing AI. The company is building the administrative scaffolding that enterprises need before they will let AI touch more critical data. That scaffolding includes policy controls, analytics, remediation workflows, and communication tools that can push guidance to the right users at the right time.
What Microsoft Added
The headline addition is Purview DLP support for Microsoft 365 Copilot. According to the Petri summary, this is intended to prevent confidential data from being included in Copilot prompts and from being unintentionally exposed through AI-assisted web searches. That is a notable move because it brings DLP closer to the moment of use rather than relying only on storage or endpoint controls after the fact.DLP at the prompt layer
This is the most strategically important part of the update. Traditional DLP tools were built for email, documents, and endpoints, but Copilot changes the equation by letting users ask natural-language questions that may touch content from several systems at once. If a prompt can surface a sensitive file, a confidential message, or a stale permission path, the real risk is no longer the file itself; it is the interaction.Microsoft’s approach acknowledges that reality. The company is effectively saying that data governance has to move upstream into the assistant experience, not just downstream into logs and incident response. That is an important distinction because it changes the security conversation from “What got leaked?” to “What should never have been surfaced in the first place?”
The same logic applies to web grounding. If Copilot can use the web to enrich answers, organizations need a way to stop sensitive internal data from being blended into external searches or responses. That is why DLP for AI is becoming a workflow control, not merely a classification feature.
Oversharing remediation at scale
Microsoft is also adding bulk remediation tools so admins can fix or disable overshared links at scale. That matters because oversharing remains one of the most common and most embarrassing enterprise data hygiene problems, especially in Microsoft 365 environments where sharing links can outlive the project, the team, or even the employee who created them. A Copilot rollout can make those latent problems visible very quickly.The key point is that Microsoft is not asking admins to chase every single bad permission manually. Instead, it is giving them a way to remediate broadly and consistently. That is a pragmatic recognition that the problem is usually not one or two risky files; it is a permission culture that has drifted for years.
Analytics becomes part of governance
The new analytics story is equally important. Microsoft says administrators can get better visibility into adoption, usage patterns, and security risks across Copilot-enabled apps. The article also notes that the Copilot Dashboard now includes productivity impact, user satisfaction, and intent-based usage patterns, with export options for external analytics tools. That turns the dashboard from a nice-to-have report into a management instrument.The significance here is subtle but real. Once analytics show who is using Copilot, how often, and for what kinds of tasks, organizations can start treating AI usage like any other enterprise system with measurable value and measurable risk. That is the sort of capability that helps security, compliance, and business teams stop arguing in the abstract and start looking at actual adoption patterns.
Why Purview Matters
Microsoft Purview has become the backbone of the company’s AI governance story, and this update reinforces that position. In Microsoft’s broader security architecture, Purview is no longer just a compliance brand or a set of classification tools; it is the data-policy layer that follows Copilot into prompts, responses, sharing, and grounding. That makes it central to the company’s claim that AI can be made governable without rewriting the entire enterprise stack.From storage-centric to workflow-centric security
For years, enterprise data protection was largely storage-centric. If the file was labeled, encrypted, or restricted, organizations could feel reasonably confident they had reduced exposure. Copilot complicates that assumption because it turns data access into a conversational workflow, where the question itself can become a vehicle for disclosure.That is why Purview’s role matters so much. Microsoft is trying to secure the path to the data, not just the file object. That is a much more realistic model for AI-enabled work, where the risk is often not a direct file download but a synthesized answer, an exported summary, or a prompt that unlocks a sensitive context the user should not have assembled on their own.
This shift also changes how admins think about policy enforcement. Instead of relying on coarse directory permissions alone, they can use data-loss controls to shape the AI experience itself. That is more precise, but it also raises the bar for policy design.
The compliance angle
The compliance value of this move is obvious. Regulated industries need evidence that AI tools are not casually exposing confidential or personally identifiable information. By putting DLP closer to Copilot interactions, Microsoft gives compliance teams a better story to tell auditors and internal reviewers.But there is a broader operational implication too. Once Purview sits in the middle of AI workflows, policy teams will need to decide what kinds of content are safe for AI to summarize, what should trigger warnings, and what should be blocked outright. That means AI governance will increasingly depend on business context, not just data type.
In practice, that will force organizations to make some hard calls:
- Which document categories are off limits to Copilot?
- Which content can be summarized but not exported?
- Which teams need tighter controls than the rest of the company?
- Which prompts should trigger remediation workflows?
- Which exceptions are acceptable, and for how long?
Why this is more than another DLP checkbox
DLP announcements can sound incremental, but this one is not. Copilot is already changing employee expectations about how quickly they can retrieve and use information. If Microsoft can insert policy into that moment without making the product unusable, it strengthens the case that enterprise AI can be both powerful and controlled.That balance is the whole game. Too little control, and Copilot becomes a liability. Too much friction, and users simply route around it. Microsoft’s challenge is to make governance feel like part of the experience rather than an obstacle to it.
Oversharing Remediation at Scale
Oversharing is one of those problems that looks minor in isolation and major in aggregate. A link here, a broad share there, a folder opened too widely for convenience, and suddenly an AI assistant can surface far more than anyone intended. The new remediation tools matter because they recognize that Copilot is only as safe as the access graph beneath it.The access problem Copilot exposes
Copilot does not invent permissions; it exposes the ones already there. That is why many organizations are discovering that their data hygiene issues were tolerable when people had to manually find things but become dangerous when an assistant can retrieve them in seconds. AI compresses the time between access and exposure.That change has enormous consequences for enterprise administration. A stale sharing link that sat unnoticed for months can become a live risk the moment Copilot starts indexing the same repository. What used to be a low-priority housekeeping issue is now a governance liability.
This is also why Microsoft’s focus on bulk remediation is smart. Security teams do not have the luxury of touching every permission manually, especially in large tenants. They need scalable actions that can reduce the blast radius quickly, even if perfect cleanup has to happen later.
Bulk controls are the real enterprise story
The phrase “bulk remediation” sounds dull, but it is one of the most important phrases in the whole announcement. Enterprises do not fail because one file was shared too broadly. They fail because thousands of files, links, folders, and permissions were allowed to drift over time.Bulk action changes the economics of response. Instead of triaging one suspicious asset at a time, admins can take wide corrective action based on policy. That is essential in environments where Copilot is amplifying hidden exposure across SharePoint, OneDrive, Teams, and connected services.
It also signals that Microsoft expects customers to use Copilot at serious scale. If the company believed adoption would stay limited to a few pilot groups, it would not need to emphasize remediation tooling so heavily. The existence of these controls is itself a clue about the size of the problem Microsoft anticipates.
What admins will actually do with it
In the real world, admins will likely use the new controls to:- Identify overexposed files and libraries.
- Disable or narrow risky sharing links.
- Review access for highly sensitive repositories.
- Coordinate remediation with owners and business units.
- Reduce the chance that Copilot surfaces stale or confidential content.
Analytics, Dashboarding, and Usage Insight
Microsoft’s analytics push may be the most underrated part of the announcement. Security controls are only half the story; the other half is knowing how Copilot is actually being used across apps, teams, and business processes. The new dashboard improvements are designed to give organizations that picture, including adoption, productivity, satisfaction, and intent-based usage patterns.Why usage data matters
The obvious value of usage data is visibility. The less obvious value is governance by evidence. If an organization can see which departments are getting real value from Copilot and which are barely using it, that information can shape licensing, training, and policy decisions.That matters because many AI rollouts will fail not from lack of enthusiasm, but from uneven adoption. Some teams will embrace Copilot immediately, while others remain skeptical or heavily constrained by compliance requirements. Analytics help administrators understand that gap instead of guessing.
It also gives IT a better way to defend the investment. If the dashboard can show productivity gains, user satisfaction, and adoption trends, then Copilot moves from “new software” to “measurable platform initiative.” That is much easier to justify to executives.
Intent-based usage patterns
Intent-based usage patterns are especially interesting because they hint at a more mature view of AI adoption. It is not enough to know whether users clicked the Copilot button. Organizations want to know why they used it, what kind of task they were trying to solve, and whether the interaction was productive or risky.That kind of insight can change training and policy design. If employees are using Copilot mostly for summarization but not for action, the organization can tailor guidance accordingly. If certain teams are using it heavily for sensitive operational work, that may trigger tighter controls or more targeted education.
The caveat, of course, is that analytics can become surveillance if mishandled. Enterprises will need to be careful not to turn productivity insight into a trust problem. Visibility is useful; creepiness is not.
Exporting data to external tools
Microsoft’s support for exporting dashboard data to external analytics tools is a useful signal. It suggests the company understands that many enterprises do not want one closed dashboard; they want to blend Copilot usage data into broader telemetry, compliance, and business intelligence systems.That makes the feature more practical. Security teams can compare AI usage against incident data, DLP events, or identity risk metrics. Business leaders can compare adoption against department-level performance measures. The value is in correlation, not just collection.
Organizational Messaging and Governance Adoption
The new messaging capability may sound small next to DLP and analytics, but it is actually a thoughtful governance feature. Microsoft is adding email delivery with usage-based targeting for organizational messaging, which allows admins to send Copilot guidance, best practices, or policy updates based on how people actually use AI tools. That is a subtle but important recognition that governance is not just about controls; it is also about communication.Governance requires education
Enterprise controls fail when users do not understand them. If employees encounter DLP blocks or sharing restrictions without context, they may view Copilot as broken rather than protected. That is why targeted messaging matters: it lets admins explain the why behind the policy.This is especially important during the early phases of deployment, when users are still forming habits. A well-timed message can prevent a lot of unnecessary help-desk friction later. It can also reduce the impulse to bypass approved tools in favor of consumer AI.
The practical upside is obvious. Admins can send guidance to power users, cautionary notes to high-risk groups, and adoption tips to teams that are underusing the tool. That creates a more mature rollout than blanket broadcast emails ever could.
Usage-based targeting is the smart part
Usage-based targeting turns messaging from generic to contextual. If a department is heavily using Copilot for document drafting, the guidance can focus on safe content handling. If another group is experimenting with Copilot but not yet integrating it into daily work, the message can be more educational than restrictive.That sort of targeting is exactly how enterprise software should work in 2026. Blanket policy announcements rarely land well. Context-aware guidance is more likely to get read, understood, and acted on.
It also mirrors a broader trend in Microsoft’s AI strategy: use analytics to inform governance, and use governance to improve adoption. The company is trying to close the loop rather than leaving security and enablement as separate silos.
A more human approach to AI control
There is a quiet intelligence to this part of the release. AI security often gets framed as a battle of tools and threats, but real adoption is as much about behavior as technology. Users need training, reminders, and policy nudges if they are going to trust the platform.That means the best governance strategy is not only restrictive. It is also communicative. Microsoft appears to be acknowledging that, and that is a good sign for enterprises that want secure adoption rather than sterile compliance theater.
Enterprise Impact vs Consumer Expectations
This update is clearly aimed at commercial customers, but its implications reach beyond enterprise IT. Microsoft is drawing a sharper line between what Copilot can do in a consumer-style workflow and what it must do inside a governed workplace. That distinction matters because the same interface can feel liberating to an individual and risky to an administrator.What enterprises gain
For enterprise customers, the benefits are straightforward. They get better control over sensitive data, better visibility into adoption, and better remediation tools for oversharing. They also get a more mature story to present to risk committees, auditors, and business leaders.The important thing is that these are not abstract benefits. They address the exact barriers that have slowed Copilot rollouts in many organizations: fear of leakage, fear of poor permissions hygiene, and fear of deploying AI without a usable governance model. Microsoft is attacking all three.
That should help larger customers accelerate adoption, especially in regulated sectors. Finance, healthcare, legal, public sector, and highly matrixed global enterprises all tend to move slowly unless the control story is strong.
What consumers and casual users may never notice
Consumer users, or business users working in lighter-touch environments, may never directly see these controls. They will experience Copilot as faster, more helpful, and sometimes more constrained. The administrative machinery behind the scenes is mostly invisible unless it blocks an action or surfaces a guidance message.That invisibility is both a strength and a weakness. It makes the product feel seamless, but it can also hide the degree to which enterprise AI depends on a very sophisticated trust stack. The average user may think Copilot is “just there,” when in reality it is being continuously shaped by policy, telemetry, and remediation logic.
That gap between perception and infrastructure is where Microsoft has real leverage. If the company can keep the experience simple while making the backend much more governable, it can satisfy both the user and the CISO.
The competitive angle
Competitively, this is a meaningful move because it raises the bar for rival AI productivity tools. Competing copilots and AI assistants will increasingly need to answer the same questions: How do you prevent oversharing? How do you detect risky usage? How do you integrate with compliance workflows?Microsoft’s advantage is that it already owns the productivity stack, the identity layer, and much of the data governance stack. That creates a built-in control plane that competitors have to assemble piece by piece. The market may still tolerate best-of-breed tools, but platform-native governance is a powerful selling point.
Strengths and Opportunities
Microsoft’s update is strong because it addresses the real problem enterprises face: not whether Copilot can write a better paragraph, but whether it can operate safely in an environment full of legacy permissions, broad sharing, and sensitive content. The company is also doing something strategically smart by pairing tighter controls with better analytics, because organizations rarely want visibility without remediation or remediation without evidence.- Better policy enforcement at the point of use
- Stronger protection against oversharing and stale links
- More usable governance for large Microsoft 365 tenants
- Clearer visibility into AI adoption and productivity
- Improved readiness for regulated industries
- A more persuasive enterprise security story for Copilot
- Potentially lower operational overhead through bulk remediation
- Better alignment between security teams and business leaders
Risks and Concerns
The biggest risk is that the new controls could expose just how messy many Microsoft 365 environments already are. Copilot does not create oversharing, but it can make it visible very quickly, and that can be uncomfortable for organizations that have lived with permissive links and weak content governance for years. There is also the danger that more analytics and more controls could create extra complexity if admins do not have a clear operating model.- Too much policy friction could slow adoption
- Oversharing remediation may uncover large legacy cleanup work
- Analytics could become noisy or hard to operationalize
- Admins may struggle to balance governance and usability
- Organizations may need significant process changes, not just new features
- Preview features can create uneven expectations during rollout
- There is always a risk of confusing visibility with actual control
Looking Ahead
The next phase of this story will be less about feature announcements and more about adoption maturity. Enterprises will want to know whether DLP for Copilot can actually reduce real exposure without creating too much false friction, and whether the dashboard insights can translate into better policy decisions rather than just prettier reporting. Microsoft is clearly betting that organizations will prefer a governed AI platform over a faster but less accountable one.What to watch next:
- Broader rollout of DLP for web search and other previewed controls
- More detail on intent-based usage analytics and export options
- How quickly customers adopt bulk remediation for overshared links
- Whether admins standardize on Purview as the AI governance layer
- How Microsoft balances security strictness with everyday Copilot usability
- Competitive responses from other enterprise AI and DLP vendors
Microsoft’s latest Copilot update is therefore best understood as a quiet but important maturation step. The company is not just making Copilot safer; it is making it administrable, auditable, and easier to justify in the enterprise. That is the real milestone, because at scale, the future of AI adoption will belong to the vendors that can prove their tools are not only smart, but governable.
Source: Petri IT Knowledgebase Microsoft 365 Copilot Gets Purview DLP Controls and New Analytics
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