Convergence Networks

Microsoft Build 2026 – 3 Key Announcements Business Leaders Should Know

umair — Thu, 11 Jun 2026 03:45:21 +0000

Microsoft Build 2026 kicked off on June 2nd in San Francisco, bringing together developers, technology leaders, and industry experts to showcase Microsoft’s latest innovations and vision for the future of AI.

Every year, the event offers a glimpse into where technology is heading. While Build is primarily a developer conference, this year’s announcements carry real implications for how businesses operate, spend on technology, and think about AI adoption. The overarching signal from Build 2026 is clear:

Microsoft is moving AI from a productivity assistant to something that works autonomously on your behalf

Here are the three key announcements that you should be aware of.

1. Microsoft Scout and the Rise of Autopilot Agents

One of the most significant announcements from Build 2026 was Microsoft Scout, Microsoft’s first “Autopilot” agent.

Unlike traditional AI assistants that wait for a prompt, Scout is designed to work continuously in the background, it can monitor activities, understand context, identify actions that need attention, and execute tasks on behalf of users.

Imagine an AI agent that:

Monitors project deadlines and schedules meetings automatically
Tracks customer requests across Teams and Outlook
Identifies emerging issues and notifies the right stakeholders
Performs routine administrative work without manual intervention

Microsoft describes Scout as an always-on agent that operates across Teams, Outlook, SharePoint, OneDrive, and other Microsoft 365 services.

While the technology is still in its early stages, the direction is clear. AI is moving beyond helping employees complete tasks. It is beginning to take ownership of specific workflows.

Why Business Leaders Should Care

The organizations that gain the most value from AI over the next several years may not be those using chatbots most effectively. They may be the ones who successfully identify repeatable business processes that can be delegated to trusted AI agents.

“Now is a good time for business leaders to start thinking about which day-to-day processes could eventually be handled by AI agents and what guardrails need to be in place before that happens,” said Adam Crate, Director of Strategic Services at Convergence Networks. “The organizations that take the time to prepare today will be much better positioned to take advantage of AI’s benefits while keeping security, compliance, and risk management front and centre.”

2. Work IQ Opens the Door to Context-Aware Business AI

Work IQ is Microsoft’s organizational intelligence layer that helps AI understand how work happens inside a company. It connects information from across Microsoft 365, including emails, documents, meetings, chats, files, projects, and business relationships, to create a richer understanding of people, teams, and workflows.

Microsoft has already been using Work IQ to power Microsoft 365 Copilot’s understanding of organizational context. At Build 2026, the company announced the Work IQ API, which allows developers and organizations to build custom AI solutions that can leverage that same contextual understanding.

This is a significant development. As Elijah Straight, Member of Technical Staff at Microsoft, put it:

“Agents are only as good as the context you give them.”

That statement captures exactly why this matters. Historically, organizations have struggled to help AI understand how their businesses actually operate. Generic AI models can answer questions, but they often lack the organizational knowledge required to provide meaningful business value. The Work IQ API is Microsoft’s answer to that gap.

Why Business Leaders Should Care

The next wave of AI value will come from systems that understand company-specific context, not just general knowledge. Business leaders should focus on data readiness now. Well-governed information, structured documentation, and strong Microsoft 365 adoption will determine how effectively organizations can deploy context-aware AI.

See this in action below

3. Secure Agent Deployment Becomes an Enterprise Priority

As you may have seen us discussing recently, the rapid adoption of AI tools and the rise of “shadow AI” present new risks for organizations. Recognizing this challenge, Microsoft made several announcements focused on secure agent execution, including Windows 365 for Agents, Microsoft Execution Containers, and expanded identity and policy controls.

These technologies are designed to help organizations ensure that AI agents can:

Operate within approved security boundaries
Follow organizational policies
Maintain auditability
Protect sensitive information
Support compliance requirements

One thing that stands out in Microsoft’s approach is that AI agents aren’t treated like anonymous background services. Instead, they’re given governed identities, much like employees have user accounts and permissions. That means organizations can see what an agent is doing, what systems it can access, and what actions it has taken. For business leaders, that added transparency can make it easier to manage risk and build confidence as AI becomes more deeply embedded in day-to-day operations.

Why Business Leaders Should Care

While AI is exciting and can offer meaningful productivity gains, the security of your organization’s data should always remain top of mind for business leaders. As AI agents gain access to systems, files, applications, and workflows, strong governance becomes just as important as the benefits these tools can deliver. Microsoft’s latest announcements represent a step forward, but organizations should establish AI governance frameworks, acceptable use policies, security controls, and oversight processes now to help manage risk and support responsible AI-driven automation.

Other Notable Microsoft Build 2026 Developments Worth Watching

Expanded Local AI for Windows Devices

Microsoft announced new Windows AI capabilities that extend beyond Copilot+ PCs. New AI models and APIs are being optimized to run on a broader range of hardware, reducing the need for specialized devices.

The Copilot+ PC Brand Was Missing in Action

One notable shift at Build was how little attention the Copilot+ PC brand received despite being a major focus in 2024. Microsoft still showcased new hardware, but the conversation centred on agentic AI experiences that work across a broader range of devices, not just specialized Copilot+ PCs. This aligns with concerns we raised in September 2024, when we advised organizations to take a cautious approach before investing heavily in that hardware category. The direction is clear: AI features are becoming less dependent on premium hardware.

Web IQ

Web IQ introduces a new approach for grounding AI agents with current information from across the web. This can help improve accuracy and reduce reliance on outdated training data.

Project Solara

Project Solara provides an early look at what Microsoft calls an agent-first future, including dedicated devices designed specifically for interacting with AI agents throughout the workday.

Microsoft Security’s Agentic Security Initiatives

Microsoft also announced several security-focused innovations, including Mdash, a multi-agent security testing framework, deeper integration between Microsoft Defender and GitHub Code Security, and the Agent 365 SDK for building secure and compliant AI agents.

Majorana 2 Quantum Chip

While still a longer-term initiative, Microsoft’s Majorana 2 quantum chip represents another step toward commercially viable quantum computing. Although not an immediate business priority, it highlights Microsoft’s continued investment in next-generation computing platforms.

What Business Leaders Should Do Next

The biggest takeaway from Microsoft Build 2026 is the shift from AI assistants to AI agents. Microsoft’s vision is clear: AI is moving beyond helping employees complete tasks and toward autonomously executing work within defined guardrails.

As Glenn Kemp, Senior Director of Intelligence Solutions Group at Convergence Networks, puts it,

“Business leaders should start thinking now about which processes could be influenced by AI and where work can become more efficient. Build doesn’t mean all of these capabilities are fully here today, but it signals what the coming year will look like as developers around the world become proficient in building and deploying these technologies.”

For business leaders, the priority now is preparation. Organizations that invest in strong data governance, clear AI policies, and well-defined automation opportunities will be best positioned to capture the value of this next wave of AI innovation.

The post Microsoft Build 2026 – 3 Key Announcements Business Leaders Should Know appeared first on Convergence Networks.

Outlook and Teams Features That Make Work Easier

umair — Thu, 11 Jun 2026 03:27:21 +0000

Most people spend more time managing their inbox than they do acting on it. Emails get read, set aside, forgotten, or buried under newer messages. Action items get lost in long threads. The result is a workday that feels reactive instead of productive.

Outlook and Microsoft Teams both include a wide range of built-in features designed to change that pattern. This article highlights a few of them, each one available in most business Microsoft 365 environments right now, with no additional configuration required. There is a lot more the platform can do, but these are a strong place to start.

Microsoft Outlook

1. Sweep: Clear Out Entire Senders in Seconds

If your inbox has dozens of emails from the same sender, such as a vendor newsletter, a subscription service, or an automated notification system, deleting them one at a time is a waste of time. Sweep handles all of them at once.

Select any email from the sender you want to clear, then click Sweep in the Outlook toolbar. Outlook gives you several options:

Move all messages from that sender out of your inbox
Move all existing and future messages automatically
Keep only the most recent message
Move messages older than a specified number of days

You can choose where the messages go, such as Deleted Items or another folder, and Outlook applies the action immediately.

This feature is particularly useful during inbox cleanup sessions. If your inbox has accumulated months of automated emails that you have never opened, Sweep can clear them out in one step and prevent the same accumulation from happening again.

Sweep options in Outlook allow you to clear messages from a sender all at once or on an ongoing basis.

2. Snooze: Keep Only What Needs Attention Right Now

Not every email requires immediate action, but leaving them all in your inbox creates noise that makes it harder to focus on what actually matters today. Snooze gives you a way to temporarily remove an email from view, and have it return at a time when you can act on it.

Right-click on any email and select Snooze. Outlook will offer a set of preset times, such as later today, tomorrow morning, this weekend, or next week, as well as the option to choose a custom date and time. The email disappears from your inbox and reappears at the top, marked as new, exactly when you need to deal with it.

This is especially useful for emails that contain information you need for a meeting that has not happened yet, requests that depend on something else being completed first, or anything you want to review at the start of a specific workday. Snooze removes the mental load of tracking those emails manually.

Snooze returns an email to the top of your inbox at a time of your choosing, removing clutter without losing the message.

3. Scheduling Poll: Stop the Back-and-Forth on Meeting Times

Finding a time that works for everyone is one of the most common sources of unnecessary email chains. Scheduling Poll, available directly in Outlook, eliminates most of that friction by letting you propose multiple time options and allowing recipients to vote on their availability.

When composing a new email, click the three-dot menu in the toolbar and select Scheduling Poll. You will be able to propose several date and time options based on your calendar availability, and Outlook generates a clean polling interface that recipients access from the email. Votes are collected, and you receive a summary, at which point you can confirm the meeting with one click.

This feature is particularly effective for external meetings where you do not have visibility into the other party’s calendar, or for group meetings where coordinating five or more schedules through individual replies quickly becomes unmanageable.

4. Folders: Build a System That Does Not Rely on Search

An inbox is not a filing system. Leaving every email in one place, regardless of whether it has been actioned, makes it harder to find important items later and harder to keep track of what still requires a response. Folders give you a structure that separates active work from archived communication.

The most effective folder systems are simple. A few well-named folders, organized around clients, projects, or departments, are more useful than an elaborate hierarchy that requires effort to maintain. Once an email has been responded to or filed for reference, move it out of the inbox. The inbox should contain only what still requires attention.

Outlook also supports nested folders, so you can create a top-level folder for a client or project and then add subfolders for action items, decisions, and reference material. Pair folders with the Sweep and Snooze features described above, and you have the foundation of an inbox that stays manageable over time.

A simple folder structure in Outlook helps keep your inbox focused on what still requires action.

Microsoft Teams

5. Schedule Messages: Send at the Right Time Without Being Online

Microsoft Teams includes a feature that is easy to overlook but highly useful in practice: the ability to schedule a message to be sent at a future date and time. This is useful when you want to communicate something at a specific moment without having to remember to send it manually.

To schedule a message, type your message in the compose box, then click the small arrow next to the Send button. Select Schedule send, choose the date and time you want the message to be delivered, and confirm. The message will sit in a draft state and be sent automatically at the scheduled time.

If you finish work early or late but do not want to pressure colleagues to respond outside of business hours, scheduling the message for the next morning respects their time and avoids the implicit expectation of an immediate reply. It is also useful for time-sensitive reminders that need to land at a precise moment, such as a heads-up before a meeting or a status update tied to a project milestone. The feature is available in both direct messages and channel posts, and it works across time zones.

Scheduling a Teams message lets you control delivery timing without requiring you to be active at that moment.

6. Channels: Organize Conversations by Topic, Project, or Team

A general group chat where every conversation happens in the same thread gets cluttered quickly. Channels solve that problem by giving teams a dedicated space for specific topics, projects, or departments. Each channel has its own conversation history, file storage, and tab structure, so the context for any given piece of work stays organized and accessible.

Teams can be structured in a number of ways depending on how the organization works. Common examples include:

Project-specific channels: Project Alpha Launch, Client XYZ Website
Departmental channels: Marketing Team, Sales Updates, HR Corner
Topic-based channels: General Announcements, Brainstorming Ideas, Social Committee

Channels reduce the noise that comes from routing everything through a single thread. Team members can follow the channels relevant to their work, catch up on specific conversations without scrolling through unrelated messages, and post updates where the right audience will see them. For organizations managing multiple clients or parallel workstreams, channels are one of the most effective ways to keep communication structured without adding overhead.

Creating a new channel in Teams keeps project and department conversations organized in their own dedicated space.

7. Microsoft Whiteboard: A Shared Canvas That Stays After the Meeting Ends

Most meetings generate ideas that live and die in someone’s notes. Whiteboard addresses that by giving every Teams meeting a shared visual workspace where participants can sketch out concepts, map processes, organize ideas with sticky notes, and build on each other’s thinking in real time.

What makes it more useful than a screen share or a photo of a physical whiteboard is that the canvas persists. When the meeting ends, the whiteboard stays accessible inside Teams. Teams can return to it the next day, pick up where they left off, and continue building on it without reconstructing the original work from scratch.

The tool is built into Teams directly, so there is no separate application to open or link to share. Any meeting participant can contribute during the session, and the board remains available to the team afterward through the channel or meeting chat. For distributed teams that cannot get everyone in the same room, Whiteboard makes visual collaboration feel closer to in-person than most other tools in the Microsoft 365 stack.

Microsoft Whiteboard inside Teams provides a persistent shared canvas that teams can access during and between meetings.

A Starting Point, Not a Complete List

Microsoft 365 includes far more than what is covered here. Outlook and Teams alone have dozens of features that most users have never opened. The seven highlighted in this post are worth learning first because they address problems that come up every day and require almost no setup to start using.

Getting the most from Microsoft 365 is not just about having the tools. It is about helping people use them effectively. Convergence Networks provides instructor-led Microsoft 365 training designed to help teams work more efficiently, improve collaboration, and make better use of the technology they already have. Whether you are introducing new features, improving adoption, or building consistent practices across your organization, we can help. Contact us to learn more about our Microsoft 365 training programs and how we can help your team get more value from the tools they use every day.

The post Outlook and Teams Features That Make Work Easier appeared first on Convergence Networks.

AI in the Workplace: Productivity Gains, Shadow AI and Privacy Risks

umair — Thu, 21 May 2026 14:18:14 +0000

Employees are already using AI across your organization, whether leadership has approved it or not.

They are summarizing meetings, rewriting emails, analyzing spreadsheets, generating reports, and connecting AI tools to business systems every day. In many organizations, this is happening with little visibility, no governance framework, and no clear understanding of where sensitive data is going.

An employee pastes confidential meeting notes into a public AI chatbot to summarize action items before the end of the day. Another uses AI to search across SharePoint for old project templates and accidentally surfaces sensitive financial documents. A manager asks an AI assistant to review employee performance trends without realizing the tool is storing that information outside the organization’s visibility.

None of these situations starts with malicious intent. Most employees are simply trying to work faster, reduce repetitive tasks, and save time.

In many ways, AI is delivering exactly that. But productivity without governance is where the risk begins.

What Is Shadow AI?

Shadow AI refers to the use of artificial intelligence tools outside approved organizational oversight. This often includes employees using personal AI accounts, browser extensions, meeting summarization tools, AI transcription platforms, or unauthorized automation software without IT or security review.

In many cases, employees are not acting irresponsibly. They are solving real business problems quickly. The challenge is that AI tools process, store, and interact with information differently than traditional workplace software.

When someone pastes client information into a public AI tool, uploads confidential specifications into an external system, or connects an AI assistant to corporate data sources, the organization may lose visibility into:

Where that data is stored
How long is it retained
Who can access it later
Whether it is used to train external models

According to the Netskope Cloud & Threat Report covering October 2024 to October 2025, 47% of employees using generative AI are doing so through personal, unmonitored accounts outside organizational IT visibility.

AI Is Like a Junior Employee

One useful way to think about generative AI is to treat it like a highly capable junior employee.

AI is fast. It can summarize documents, analyze large amounts of information, generate drafts, and automate repetitive work in seconds. But it also lacks judgment, context, and professional awareness.

Like a junior employee, AI:

Can sound confident even when wrong
Works quickly but does not always understand what matters most
Requires clear instructions, or it begins guessing
Does not understand confidentiality obligations on its own
Uses whatever data it can access without human judgment
Requires supervision and validation to remain defensible

This is where many organizations underestimate the risk. Employees often trust AI outputs because they sound polished and authoritative. That trust can lead to overreliance, poor decision-making, or accidental disclosure of sensitive information.

The Data Privacy Problem in Plain Terms

Without proper access controls, employees can inadvertently expose sensitive HR and financial data through public AI tools.

The scenario illustrated above is not hypothetical. Employees routinely ask AI tools questions that contain or imply sensitive organizational data. Consider a few common examples:

An HR manager copies performance review notes into a public AI tool to generate a termination letter
A finance team member asks an AI chatbot to help interpret salary benchmarks after pasting in internal compensation data
A sales employee uploads a customer list to an AI tool to generate personalized outreach
A developer pastes proprietary source code into a public AI assistant for debugging help

In each case, the employee is solving a real problem. In each case, the organization has potentially exposed data that was never meant to leave its environment. Depending on the jurisdiction, the industry, and the nature of the data, this can trigger regulatory obligations, contractual breaches, or reputational damage.

Privacy regulations such as PIPEDA in Canada, GDPR in Europe, and HIPAA in healthcare settings impose obligations on how personal data is collected, stored, and shared. Using a public AI tool to process personal employee or customer data without appropriate data processing agreements in place likely violates these frameworks.

What a Corporate AI Policy Needs to Cover

A well-designed AI policy enforces access controls that match data sensitivity, not just department boundaries.

The contrast between the two office diagrams in this blog captures the core of the policy challenge. Without controls, any question posed to an AI tool returns sensitive answers regardless of whether the person asking should have access to that information. With the right policy and technical guardrails in place, the same questions produce appropriate refusals or redirects.

A corporate AI policy should address the following:

1. Approved Tools and Platforms

Specify which AI tools employees are permitted to use and under what circumstances. Enterprise-grade versions of tools such as Microsoft Copilot, Google Workspace AI, or dedicated business tiers of AI platforms typically offer data isolation and contractual data protection that consumer-facing free versions do not. Default browser access to public AI tools should be treated as unapproved unless explicitly sanctioned.

2. Data Classification and AI Interaction Rules

Not all data carries the same risk. A policy should categorize data and define clearly what categories may be submitted to which classes of AI tools. Confidential data such as employee records, client contracts, financial data, and source code should require explicit review before any AI interaction.

3. Training and Awareness

Employees do not adopt Shadow AI out of malice. They adopt it because it works, and no one told them the risk. Regular, plain-language training that explains what data can and cannot be submitted to AI tools, and why, is essential. Training is not a one-time event. As AI tools evolve, the guidance must evolve with them.

4. Monitoring and Enforcement

Policy without enforcement is guidance at best. Organizations should implement technical controls that make it harder to paste sensitive data into unapproved tools, including data loss prevention solutions that flag or block specific data types. Browser policies that restrict access to consumer AI tools on corporate devices add an additional layer of protection.

5. Incident Response for AI-Related Data Exposure

If an employee inadvertently submits sensitive data to a public AI tool, the organization needs a clear process for assessing the exposure, notifying affected parties if required, and documenting the incident. Most organizations have data breach response plans. Few have adapted them specifically to AI-related exposures.

The Vendor and Supply Chain Dimension

AI risk does not stop at the employee. Organizations should also evaluate the AI capabilities embedded in the tools they already use. Many software vendors have added AI features to their products without making those features prominent in their changelog or contract updates.

A document management platform that introduces an AI summarization feature may, by default, send document content to a third-party AI provider. The organization may have no awareness this is happening unless they read every product update carefully. Vendor security reviews should now explicitly ask about AI capabilities, data routing, and training data practices. The same principle extends to understanding broader cybersecurity risks that AI introduces at the network level.

The Cost of Poor AI Governance

The risks are no longer theoretical.

According to IBM’s 2025 Cost of a Data Breach Report:

1 in 5 surveyed organizations suffered a breach directly caused by Shadow AI
97% of organizations reporting AI-related breaches lacked proper AI access controls at the time of the incident
16% of all breaches involved attackers using AI, including AI-generated phishing and deepfake impersonation attacks

The challenge is not simply external attackers. Organizations are also struggling with internal misuse, overexposure of information, and uncontrolled adoption patterns.

Getting Ahead of the Risk

AI adoption in the workplace is not a future concern. It is happening now, at scale, largely without formal oversight in most organizations. The gap between what employees are doing with AI tools and what IT and leadership know about it is widening every month.

Closing that gap does not require blocking AI entirely. It requires building a framework that gives employees access to appropriate AI tools, educates them on what data those tools can and cannot touch, and creates technical guardrails that back up that education.

Organizations that build that framework now will be better positioned to capture the productivity benefits of AI while protecting the data, relationships, and regulatory standing they have spent years building.

If your organization is at the early stages of thinking through AI governance, or if you suspect Shadow AI is already a factor in your environment, contact us today.

The post AI in the Workplace: Productivity Gains, Shadow AI and Privacy Risks appeared first on Convergence Networks.

What is Mythos and What It Could Mean for AI in Cybersecurity

umair — Thu, 21 May 2026 13:57:51 +0000

You have probably seen the name floating around. Anthropic’s Mythos is an AI model that its own creator refuses to release to the public. Not because it is not ready, but because it is considered too dangerous. That is not marketing language. That is a company drawing a line that has rarely been drawn in this industry.

So what is actually going on, and should your organization be paying attention?

What Mythos Is and Why It Is Different

Mythos is an AI model built by Anthropic, the company behind the Claude chatbot. Unlike most AI announcements that come with product access, Anthropic revealed Mythos on April 7 without a public release. The stated reason was straightforward: the model poses a serious threat to cybersecurity infrastructure if it falls into the wrong hands.

The specific concern is its ability to find and exploit zero-day vulnerabilities. These are flaws in software that nobody knows about yet; no patch exists, no defence has been built. Mythos, according to Anthropic, can identify them across every major operating system and web browser. Some of those flaws, it turns out, had been sitting undetected for decades. Anthropic described the implications as a “watershed moment for cybersecurity.”

The Evidence Behind the Claim

This is not just self-reported. The AI Safety Institute (AISI), the world’s leading AI safety body, independently assessed Mythos and confirmed it represents a genuine step up from anything seen before. The AISI flagged its ability to execute multi-step attacks and identify vulnerabilities autonomously, without human prompting. In one test, Mythos became the first AI model to complete a 32-step simulated cyberattack designed by the institute. Anthropic also reported that Mythos had already uncovered thousands of high-severity vulnerabilities, including findings across every major operating system and web browser.

The AISI did offer one note of caution: its assessment covered weaker, smaller IT systems. How Mythos performs against hardened, enterprise-grade defences remains an open question, but some news outlets claimed that security researchers at Palo Alto-based firm Calif used Mythos Preview to uncover two previously unknown vulnerabilities in Apple’s macOS, one of the most hardened operating systems in the industry. They chained those bugs into a privilege escalation exploit capable of bypassing Apple’s Memory Integrity Enforcement protections on its latest M5 hardware, a security feature Apple spent five years building. The team developed the working exploit in under five days. The researchers were clear that Mythos did not do this alone, human expertise was essential throughout, but the speed and depth of what it uncovered was enough that they personally drove to Apple’s Cupertino headquarters to hand-deliver a 55-page technical report. Apple confirmed it is reviewing the findings.

News headlines following Mythos-assisted macOS security breaches

Who Has Access and Why That Matters

Rather than a broad release, Anthropic has given selective access to a small group of major organizations, including Microsoft, Apple, AWS, etc., to evaluate what the model means for their risk posture. That controlled approach reflects the seriousness with which Anthropic is treating the model.

What complicates that picture is a separate, concerning development. Anthropic confirmed it is actively investigating a report that a group of individuals gained unauthorized access to Mythos. If true, it raises a legitimate question about whether controlled access is enough of a safeguard when the underlying technology is this sensitive.

This Is Now a Boardroom and Policy Issue

The conversation has moved well beyond the security community. Canadian Finance Minister Francois-Philippe Champagne confirmed Mythos was raised at an International Monetary Fund meeting in Washington, calling it an “unknown unknown” and noting it was serious enough to warrant attention from finance ministers globally. Reports also point to significant turbulence in technology stocks tied to concerns about Mythos and similar frontier AI systems, and US officials are reportedly pushing major financial institutions to begin testing advanced AI models like this in controlled environments.

That kind of signal, from regulators, policymakers, and markets simultaneously, is worth taking seriously.

The Real Question: Defenders or Attackers?

Here is where the debate gets genuinely important for anyone responsible for organizational security. The same capability that makes Mythos alarming also makes it potentially valuable. A tool that can surface thousands of unknown vulnerabilities before attackers do is, in theory, exactly what defenders need.

Ciaran Martin, Professor of Practice at Oxford’s Blavatnik School of Government, said:

“In the medium-term, there’s an opportunity to use these tools to fix a lot of the underlying vulnerabilities in the internet.”

On the other hand, here is a word of caution. John Stephens, CISO of Convergence Networks, said:

“Given how quickly AI is advancing, it may not be long before these capabilities become widely available, potentially extending beyond organizations committed to using them responsibly.”

That is the broader point. Mythos may be controlled today, but the capability trend is not limited to one company or one model.

Is Mythos overhyped?

There is almost certainly some hype around Mythos, because every major AI advancement now arrives with a mix of excitement, fear, speculation, and market reaction. Some headlines make it sound like the cybersecurity landscape has changed overnight. That is not the right way to look at it.

Most cyber incidents still start with familiar weaknesses: poor identity controls, unpatched systems, weak policies, phishing, exposed services, unmanaged devices, and unclear response plans. Attackers do not always need advanced AI when basic security gaps already give them a way in.

This is where businesses should be careful not to let the most advanced threat distract them from the most common ones. Worrying about Mythos while leaving basic cyber hygiene unfinished is a little like installing a biometric lock with a retina scanner, then leaving the door unlocked. The advanced control may sound impressive, but it does not help much if the basic control is missing.

At the same time, dismissing Mythos as only hype would be a mistake. The real issue is not whether one model is as powerful as the loudest headline suggests. The real issue is that AI systems are improving quickly, and cybersecurity teams need to prepare for a world where technical discovery, attack planning, and misinformation can move faster.

For business leaders, the right response is not panic. It is awareness, planning, and clear communication. Organizations should be asking whether their security basics are consistent, whether they know where their most important systems are exposed, whether employees understand acceptable AI use, and whether leadership has a clear process for evaluating new AI tools before they enter the business.

The AI Governance Risk Businesses Should Not Ignore

There is another important point in this conversation. Even if an organization is doing a solid job with basic cyber hygiene, it may still have a gap in how employees are allowed to use AI.

For many small and mid-sized businesses, the more immediate risk may not be Mythos itself or similar tools. It may be a well-intentioned employee using AI to save time and accidentally entering sensitive information into a public AI system. That could include client details, employee information, financial data, contracts, internal notes, or other business information that should not leave the organization.

The intent may be harmless. The outcome can still create a privacy issue, compliance concern, or security incident. That is why AI governance matters. Businesses need clear rules around which AI tools are approved, what information can and cannot be shared, who reviews new AI use cases, and how employees should handle sensitive data when using AI.

AI governance is not about stopping people from using helpful tools. It is about giving employees enough structure to use AI safely, especially as these tools become more common in everyday work.

What businesses should take from this

Keeping John Stephens’ perspective in mind, it may not be long before these capabilities become more widely available. That means businesses should use this moment to strengthen their security planning, set clearer internal expectations, and have more informed conversations about AI-related risk. Mythos may not be publicly available today, but it points to a future where AI can influence how quickly security weaknesses are found, how quickly misinformation spreads, and how prepared organizations need to be.

For most SMBs, the first priority should not be worrying about the most advanced AI capability before the basics are in place. The first priority should be strong cyber hygiene: identity protection, endpoint visibility, patching discipline, data controls, monitoring, backups, and incident response planning.

The second priority is AI governance. Businesses should create clear AI use policies, train employees on what information should never be entered into public tools, test new AI systems in controlled environments, and make sure security leaders are involved before sensitive tools are adopted.

Mythos is worth paying attention to, but it should not pull focus away from the steps businesses can take right now. Stronger cyber hygiene and clearer AI governance are simpler, more immediate ways to reduce risk as AI becomes more capable and more deeply embedded in everyday work.

The post What is Mythos and What It Could Mean for AI in Cybersecurity appeared first on Convergence Networks.

Convergence Networks at the Ottawa Food Bank Food Sort Challenge 2026

umair — Mon, 18 May 2026 21:36:15 +0000

As part of our Convergence Care initiatives, our team at Convergence Networks proudly participated in the Ottawa Food Bank’s Food Sort Challenge 2026. This year marked the 10th edition of the event, bringing local teams together for Battle of the Cans, a fast-paced race to sort 1,000 pounds of food as quickly and accurately as possible.

Hosted at Hard Rock Hotel & Casino Ottawa, the event brought great energy, teamwork, and a shared commitment to supporting an important cause in our community. Our team worked together to sort 1,000 lbs. of food, staying focused, coordinated, and accurate throughout the challenge.

We are proud to share that Convergence Networks came in 2nd place in our round. Even more importantly, our team met its donation target of $2,500 in support of the Ottawa Food Bank and the individuals and families who rely on its programs.

The Ottawa Food Bank continues to play an essential role in helping people across the community access the food and support they need. With demand remaining high, events like the Food Sort Challenge help raise awareness, provide direct support, and bring people together around a shared purpose.

At Convergence Networks, giving back is part of who we are. Events like this give our team the opportunity to support the communities we serve while strengthening the relationships we build with one another. We are grateful to have participated again this year and proud of the effort our team brought to the challenge.

We would like to send a big thank you to the Ottawa Food Bank team, volunteers, organizers, and everyone involved in making the Food Sort Challenge 2026 a success.

You can learn more about the Ottawa Food Bank at their website here to learn how you can get involved!

The post Convergence Networks at the Ottawa Food Bank Food Sort Challenge 2026 appeared first on Convergence Networks.

The Hidden Cost of Inconsistent IT Environments and How to Fix It

umair — Thu, 16 Apr 2026 16:14:03 +0000

Most organizations do not set out to build inconsistent IT environments. It happens gradually. A new tool is introduced to solve a specific problem. A vendor is added during a period of growth. A quick fix is implemented during an urgent issue. Over time, these decisions layer on top of each other, creating an environment that looks functional on the surface but is fragmented underneath. This is often the result of gaps in IT infrastructure management, where tools and systems are added without a consistent standard or long term structure.

At first, the impact is not obvious. Systems are running. Teams are working. Issues are handled as they arise. But behind the scenes, the cost begins to build in ways that are harder to measure and often overlooked until something breaks.

This is where many businesses find themselves today. Not lacking technology, but lacking structure in how their IT infrastructure management is defined and applied.

The Real Cost of One-Off IT Decisions

When every system is configured differently, every issue becomes unique. Support teams cannot rely on known patterns. Security controls vary from one environment to another. Documentation becomes inconsistent or outdated. Even simple changes require more effort because there is no shared baseline to work from.

This creates friction across the entire organization. Internal teams spend more time troubleshooting. External partners need more time to understand the environment. Leadership has less visibility into risk because there is no consistent standard to measure against.

The cost is not just operational. It shows up in missed opportunities, delayed initiatives, and increased exposure to security threats.

According to IBM’s Cost of a Data Breach Report, the average breach reached $10.22 million in U.S in 2025. A growing portion of these incidents are tied to identity-based attacks and misconfigurations, both of which are more likely in environments that lack consistency.

Inconsistent environments do not just increase risk. They make it harder to manage that risk effectively.

Security Gaps Multiply Without a Common Foundation

Security is only as strong as its weakest point. In fragmented environments, those weak points are often hidden. Controls vary, configurations drift, and recovery becomes uncertain.

Without a consistent baseline, even basic questions become difficult to answer. Are systems protected the same way? Are backups reliable everywhere? Are controls aligned to current threats?

This is why leading frameworks emphasize consistency. It is not just about having controls, but applying them uniformly.

Requirements like HIPAA expect documented, consistent handling of data. When controls are applied unevenly, such as encrypting some systems but not others, it creates gaps that often surface during audits.

NIST reinforces this through the concept of a target profile, where security controls are applied consistently across the environment rather than configured on a case-by-case basis.

CMMC goes further by requiring security practices to be documented, repeatable, and consistently enforced. Because it aligns with NIST SP 800 171, variation across systems can introduce audit risk and impact contract eligibility.

The message across all of these is simple. Consistency is not optional. It is foundational to security, compliance, and long-term risk management.

At Convergence Networks, this is how we design environments. Our approach is aligned with recognized frameworks, with the goal of building a consistent, secure foundation that can evolve with the business.

What a Consistent Environment Actually Looks Like

Consistency does not mean every business is identical. It means core elements are aligned to a defined standard. This includes identity protection, device configuration, backup integrity, network resilience, and cloud security controls.

When these areas follow a consistent model, several things change immediately. Security controls become predictable and repeatable. Issues can be addressed using known approaches rather than starting from scratch each time. Teams can operate with greater confidence because they understand how systems are structured.

It also creates a stronger position for cyber insurance and audits. When controls are documented and aligned to recognized frameworks, organizations can demonstrate maturity in a way that fragmented environments cannot.

Consistency brings clarity. And clarity reduces risk.

Breaking the Cycle of Constant Firefighting

One of the biggest challenges in inconsistent environments is the constant cycle of reactive work. Each issue is handled individually, without addressing the underlying structure. Over time, this creates a pattern where teams are always responding, but rarely improving the environment as a whole.

A consistent approach changes that dynamic. Instead of solving the same problems repeatedly, improvements can be applied across the entire environment. When a better control or configuration is identified, it can be rolled out in a structured way.

This is where scale becomes an advantage. Convergence evaluates trends across its broader client base and applies those insights to improve environments proactively. Whether it is preparing for AI adoption, adapting to new Microsoft security capabilities, or addressing emerging threat vectors, changes are made with intention and consistency.

The result is an environment that evolves alongside the business, not one that reacts after incidents occur.

The Role of the Security Operations Center (SOC)

A consistent environment also strengthens the value of a Security Operations Center. When systems are aligned, telemetry becomes more reliable. Alerts can be correlated more effectively. Detection and response processes can follow established patterns.

Convergence’s standardized approach feeds directly into our 24/7 Security Operations Center. This allows for continuous monitoring, detection, and response using consistent tooling and data across environments.

Without this level of alignment, even the most advanced SOC capabilities are limited. Inconsistent data leads to gaps in visibility. Inconsistent tools lead to fragmented response efforts. Consistency ensures that security operations are not just active, but effective.

Reducing Friction Across the Organization

Operational friction is one of the most immediate impacts of inconsistent environments. It shows up during onboarding, when new systems need to be integrated. It appears during growth, when additional locations or users are added. It becomes more visible during change events, such as mergers or technology upgrades.

In structured environments, these transitions are smoother because there is a defined model to follow. Teams know what to expect. Systems are aligned to known configurations. Support processes are consistent regardless of location or scale.

This reduces escalation volume and simplifies day to day operations. It also creates a more consistent experience for users, who are not dealing with different systems or processes depending on where they are or how they connect.

Over time, this consistency builds trust. Not just in the technology, but in the overall experience of working within it.

A More Predictable Path Forward

Beyond operations and security, consistency has a direct impact on planning and budgeting. When environments are structured, technology lifecycles become more predictable. Investments can be aligned to a roadmap rather than driven by urgent fixes.

This allows leadership teams to make informed decisions about where to allocate resources. It also creates a clearer connection between IT investments and business outcomes.

Instead of reacting to issues as they arise, organizations can plan for growth, resilience, and innovation with confidence.

Fixing the Problem Starts with Structure

The path forward does not begin with adding more tools. It begins with evaluating the current environment and identifying where inconsistency exists. From there, the focus shifts to building a defined standard based on recognized frameworks and aligning systems to that model.

This is not a one-time project. It is an ongoing process that evolves as technology and business needs change. But the impact is immediate. Reduced friction. Stronger security. Greater visibility. A foundation that supports long term success.

Inconsistent IT environments are common. But they are not inevitable. With the right approach, they can be transformed into structured, secure, and scalable systems that work the way your business needs them to.

If your environment feels harder to manage than it should be, it may not be a technology problem. It may be a structure problem.

The post The Hidden Cost of Inconsistent IT Environments and How to Fix It appeared first on Convergence Networks.

The Buzz Around OpenClaw and the Growing Risks of Uncontrolled AI Adoption

umair — Thu, 16 Apr 2026 15:26:21 +0000

In late November 2025, a new AI agent quietly entered the scene. Built by developer Peter Steinberger, OpenClaw, originally known as Clawdbot, did not take long to gain attention. Within weeks, it crossed 100,000 stars on GitHub, quickly becoming one of the most talked-about AI projects in the developer community.

What sets OpenClaw apart is simple. It does not just respond. It acts. The creator, Peter Steinberger, describes it as “the AI that actually does things.” That claim is what sets OpenClaw apart. While most AI tools stay within chat interfaces, OpenClaw connects directly to your systems and executes real-world tasks.

Think about what that means in practice. An AI that can go through your inbox and act, interact with websites on your behalf, run commands directly on your machine, keep your schedule in order, trigger workflows across tools, and handle tasks like coordinating travel or organizing files without constant input.

Running locally on your own hardware, it connects to large language models through APIs and interacts directly with your digital environment. Over time, it builds memory through stored context and user preferences, allowing it to operate more like a persistent assistant than a traditional tool.

While this represents a significant step forward, it comes with a trade-off. To operate effectively, OpenClaw requires access to sensitive data and systems, including emails, credentials, files, financial information, and application integrations. That same level of access is exactly what threat actors look for.

The growing cyber risks behind the hype

Security is not properly built into the core of the platform. It is left to the user to configure and manage. Even its own documentation acknowledges that there is no perfectly secure setup and that giving an agent broad access can create significant exposure.

A scenario to consider

Imagine a finance manager using OpenClaw to stay on top of daily tasks.

They connect it to their email, calendar, file storage, and accounting tools. Over time, the agent learns patterns. It knows which vendors are paid regularly, where invoices are stored, and how approvals are handled.

Now introduce a seemingly harmless community skill designed to improve workflow automation.

Behind the scenes, that skill contains hidden instructions. When OpenClaw processes an email or webpage, those instructions are triggered. Because the agent operates with elevated permissions, it does not question the request. It executes it.

Without any visible signs, the agent begins accessing financial records and transmitting sensitive data externally.

No alerts. No immediate failures. Just silent exposure.

This is not a far-fetched scenario. Research has already identified more than 18,000 OpenClaw instances exposed to the internet, along with a portion of community skills containing malicious instructions designed to extract data or introduce malware.

Where the risks come from

The architecture that makes OpenClaw powerful also creates multiple points of vulnerability:

Unrestricted access

The agent often requires elevated permissions to perform tasks. If those permissions are too broad, any misuse can have a wide-reaching impact.

Unverified ecosystem

With hundreds of community-developed skills and no formal review process, organizations are effectively trusting external code with internal system access.

Hidden instruction attacks

Since OpenClaw processes web content and messages, it can be influenced by embedded prompts that trigger unintended actions.

Persistent data exposure

Its memory and integrations allow it to retain and access sensitive data over time, increasing the impact of any compromise.

Public exposure

Instances exposed to the internet create an additional entry point for attackers.

This is where the risk becomes operational, not theoretical. As Raphael Ebba, Penetration Tester at Convergence Networks, notes, “OpenClaw introduces a new level of convenience, but also a new level of exposure. When an AI agent can access emails, files, and system commands, it becomes a high-value target. Without proper governance, monitoring, and control, it is not just a tool. It becomes a pathway into your environment. In the wrong configuration, OpenClaw can quickly turn into a recipe for disaster.”

What organizations should do next

The issue is not the technology itself, but how it is adopted. Organizations looking to use tools like OpenClaw need to establish structure before deployment by clearly defining access boundaries and limiting what the agent can and cannot do. Critical systems should not be connected without oversight, and third-party skills must be treated as untrusted software that requires review, testing, and ongoing monitoring. At the same time, organizations need full visibility into agent activity, with logging and auditing treated as standard practice rather than optional controls. Where possible, deployments should be isolated in controlled environments to reduce risk. Most importantly, there must be clear ownership and accountability, ensuring that AI systems operate within defined governance frameworks rather than without oversight.

Final thoughts

OpenClaw represents a shift in how AI is used, moving from assistance to execution. That shift brings measurable value, but it also expands the attack surface in ways many organizations have not yet accounted for. At its current stage, OpenClaw is not ready for corporate environments. The level of access it requires, combined with the lack of built-in security and oversight, introduces risks that most organizations are not equipped to manage.

For that reason, our recommendation is clear. Avoid deploying tools like OpenClaw in production environments until stronger controls, validation, and enterprise-ready safeguards are in place. Experimentation may have a place in isolated environments, but not within systems that handle sensitive business data.

This is where taking a step back and being intentional about how you adopt AI really matters. At Convergence Networks, our AI Accelerator service helps organizations evaluate, deploy, and scale AI in a controlled and secure manner, ensuring that new technologies align with business goals without introducing unnecessary risk. The focus should not be on adopting every new tool, but on adopting the right tools at the right time, with the right controls in place. With AI evolving rapidly, discipline in how it is introduced into the organization will define whether it becomes a competitive advantage or a liability.

The post The Buzz Around OpenClaw and the Growing Risks of Uncontrolled AI Adoption appeared first on Convergence Networks.

Cybersecurity for Nonprofits: What Leaders Need to Know to Reduce Risk

umair — Tue, 31 Mar 2026 20:00:26 +0000

Nonprofits run on trust. Donors expect their contributions to be handled responsibly, beneficiaries rely on their data being protected, and partners depend on consistent operations. That trust is fragile, and cybersecurity now plays a direct role in maintaining it. While most leaders recognize cyber risk, many are not prepared to respond. About 70% of NGOs are unsure whether they could recover from a disruptive cyberattack, turning risk into real operational impact.

Moreover, Nonprofits are managing more data across more systems, often with limited internal resources. Distributed teams, volunteers, and third-party access increase exposure, making it harder to control who has access and how securely they operate. Attackers recognize this gap and target organizations where valuable data exists, but defenses are inconsistent. Cybersecurity is no longer just an IT concern. It is a leadership priority tied to continuity, funding, and long-term stability.

Cybersecurity Risks for Non-Profits

Understanding risk in a nonprofit context requires looking beyond technical vulnerabilities and focusing on how attacks affect operations, funding, and reputation.

Phishing remains the most common entry point. About 83% of organizations experienced a phishing attack in the last year. Nonprofits are particularly exposed because communication with donors, sponsors, and vendors is frequent and often time-sensitive. A well-crafted email that appears to come from a donor or board member can lead to credential theft or unauthorized financial transfers.

Ransomware poses a direct threat to service delivery. For nonprofits, system downtime is not just an inconvenience. It can halt programs, delay services, and disrupt communities that rely on them. Losing access to donor databases or case management systems for even a few days can have a measurable impact on funding and outcomes.

Data exposure carries both ethical and legal consequences. Nonprofits often handle sensitive personal information, including financial records and data related to vulnerable populations. A breach does not just create compliance issues. It directly impacts the people the organization is trying to support.

Limited internal resources increase risk. Many nonprofits lack dedicated cybersecurity leadership or structured security programs. A study by NTEN found that only about 40% of nonprofits provide regular cybersecurity training. This creates gaps that attackers can exploit through social engineering and credential-based attacks.

Reputation damage has long-term effects. Donor trust is difficult to rebuild once lost. A single incident can reduce future donations, delay grants, and impact partnerships. Cybersecurity incidents are no longer contained events. They influence how stakeholders evaluate the organization moving forward.

Why Nonprofits Are an Attractive Target for Cybercriminals

Consider a simple but damaging scenario. An attacker gains access to your website or donation platform and alters the banking details associated with online contributions. Donors continue giving, unaware that funds are being redirected. In other cases, a compromised donation page can be used to collect card details, exposing donors to fraud while the organization loses both revenue and trust. This is where cybersecurity for nonprofits becomes critical, as even small gaps can lead to significant financial and reputational damage.

Cybercriminals know nonprofits are mission-driven and use that urgency to their advantage. They research organizations, map users and systems, and spend days or weeks finding the easiest way in. In many cases, they quietly gain access, move through email and cloud accounts, and wait for the right moment to act.

Nonprofits offer a strong return for that effort. Donor records, payment details, healthcare data, and personal information can be sold or used for fraud. Timing and access make these attacks effective. When teams are moving quickly, a single convincing message or small system change can lead to financial loss.

The Business Impact of a Cyber Incident

For nonprofit leaders, the most important question is not how an attack happens, but what it means for the organization when it does.

A successful attack can lead to:

Loss of access to critical systems and data
Interruption of programs and services
Financial loss through fraud or ransom payments
Increased operational costs for recovery and investigation
Regulatory penalties depending on the nature of the data exposed
Long term erosion of donor and stakeholder trust

These are not isolated IT issues. They affect fundraising, service delivery, and overall organizational stability. Cybersecurity decisions should be evaluated with the same level of importance as financial planning and program strategy.

5 Cybersecurity Controls Every Nonprofit Should Have

Strong cybersecurity does not start with tools. It starts with structure, accountability, and consistency. The following controls form the foundation of a resilient nonprofit security program.

1. Implement a Clear Cybersecurity Policy

A cybersecurity policy sets expectations across the organization. It defines how staff should handle data, devices, passwords, and email. It also establishes accountability and provides a reference point for decision making.

This policy should not be static. It needs to be reviewed regularly, communicated clearly, and reinforced through training. As the organization grows and adopts new technologies, the policy should evolve to reflect those changes.

2. Establish Strong Data Governance

Nonprofits need clear visibility into what data they collect, where it is stored, and who has access to it. Donor information, financial records, and personal data should only be accessible to authorized individuals.

Data governance also includes understanding legal and regulatory requirements. Whether it involves donor privacy laws or healthcare data regulations, leadership must ensure that data handling practices align with compliance expectations.

3. Provide Cybersecurity Training for Staff

Technology alone does not prevent breaches. People play a critical role in identifying and stopping threats. Regular training helps staff recognize phishing attempts, suspicious activity, and risky behaviour.

Given that only about 40% of nonprofits provide ongoing training, this is one of the most immediate opportunities to reduce risk. Training should be practical, relevant, and continuous rather than a one-time initiative.

4. Use Multi Factor Authentication

Multi factor authentication is one of the most effective ways to prevent unauthorized access. It blocks more than 99.9% of automated account compromise attempts.

MFA should be required for email, cloud platforms, and any system that provides access to sensitive data. This is a low-cost control with a high impact on reducing risk.

5. Maintain Secure Backups

Backups are essential for recovery. In the event of ransomware or system failure, they provide a way to restore operations without paying a ransom.

Backups should be encrypted, immutable, tested regularly, and stored separately from the primary network. Leadership should also ensure that recovery processes are documented and tested to avoid delays during an actual incident.

Building a Stronger Cybersecurity Foundation

Beyond core controls, nonprofit leaders should focus on building a structured approach to managing cyber risk. This involves aligning security initiatives with operational priorities and ensuring that decisions are made with a clear understanding of risk and impact.

Conduct a Risk Assessment

A risk assessment provides visibility into current vulnerabilities and potential threats. It helps prioritize investments and ensures that resources are allocated effectively. This should be conducted regularly and updated as the organization changes.

Implement Strong Password Policies

Weak or reused passwords remain a common entry point for attackers. Enforcing strong password requirements and encouraging the use of password managers can significantly reduce this risk.

Educate Board Members on Cybersecurity Awareness

Cybersecurity is not just an operational issue. It is a governance issue. Board members should understand the risks, the organization’s current posture, and the potential impact of an incident. This ensures that cybersecurity is included in strategic discussions and funding decisions.

Use Secure Communication Channels

Sensitive information should not be shared through unsecured channels. Implementing secure communication tools and guidelines helps protect data in transit and reduces the risk of interception.

Regularly Update and Patch Systems

Outdated systems create vulnerabilities that attackers can exploit. Regular patching and updates ensure that known security issues are addressed promptly. This should be managed through a structured process rather than ad hoc updates.

Develop a Cyber Incident Response Plan

An incident response plan defines how the organization will respond to a cyber event. It should include roles, responsibilities, communication protocols, and recovery steps.

This plan should be tested through exercises to ensure that teams are prepared. During an incident, speed and clarity are critical. A well-defined plan reduces confusion and helps contain the impact.

Moving from Reactive to Resilient

Many nonprofits approach cybersecurity reactively. Controls are implemented after an incident or when a requirement arises. This approach creates gaps and leaves the organization exposed.

Leadership teams need to shift toward a proactive model where cybersecurity is integrated into planning, budgeting, and operations. This includes:

Aligning cybersecurity investments with business priorities
Treating cybersecurity as part of risk management rather than IT overhead
Ensuring ongoing training and awareness across the organization
Establishing accountability at both the leadership and operational levels

Cybersecurity is not about eliminating all risk. It is about managing risk in a way that protects the organization’s ability to operate, serve, and grow.

What This Means for Leadership

Nonprofits exist to create impact. Cybersecurity supports that mission by ensuring that operations remain stable, data remains protected, and trust remains intact.

The organizations that will succeed in the coming years are those that treat cybersecurity as a leadership priority rather than a technical afterthought. This often includes working with experienced partners that deliver Managed IT Services for Nonprofits, helping bring structure, visibility, and accountability to cybersecurity efforts.

For nonprofit leaders, the question is not whether to invest in cybersecurity. It is whether the organization is prepared to operate without it.

The post Cybersecurity for Nonprofits: What Leaders Need to Know to Reduce Risk appeared first on Convergence Networks.

How Teams Get More Done: A Guide to Microsoft Copilot Prompts

umair — Thu, 19 Mar 2026 16:53:17 +0000

Most teams are not short on tools. They are short on time, clarity, and alignment. Emails pile up, chats get buried, and meetings happen back-to-back with little time to prepare or follow through. Important context is spread across Outlook, Teams, SharePoint, and individual inboxes, making it harder to stay aligned. The result is not a lack of effort; it is friction that slows down progress and decision-making.

Integrating AI helps reduce that friction by making it easier to find information, prepare for conversations, communicate clearly, and move work forward with confidence. About 75% of workers say AI improves the speed or quality of their work, with typical time savings of 40 to 60 minutes per day.

At Convergence Networks, teams are using Microsoft Copilot in structured, repeatable ways across roles. This is not about occasional use. It is about embedding Copilot into daily workflows. Below are real use cases, along with prompts and practical ways teams are applying them.

Find Documents and Conversations Faster

Copilot helps teams quickly locate and understand information across emails, chats, and files without manual searching.

Instead of digging through Outlook or Teams, you can ask Copilot to find relevant content, summarize it, and provide direct access.

Prompt:
Find the document or message about [topic] that involved [person or team], likely stored or sent via Outlook or Teams in the last [x] weeks. Summarize it and give me the link.

Prepare for Meetings

Copilot helps you walk into meetings with context by analysing past interactions and surfacing what matters most.

This is especially useful for one-to-one meetings, leadership discussions, or client conversations where preparation impacts outcomes.

Prompt:
Based on my prior interactions with [person], give me 5 things likely top of mind for our next meeting.

Start Better Team Discussions

Copilot can help structure conversations so meetings are more productive and not repetitive.

This is commonly used for retrospectives, team reviews, or project debriefs.

Prompt:
Suggest common questions that can be asked to get a retrospective started with my colleagues.

Catch Up on Threads and Conversations

Copilot simplifies long or complex conversations so you can quickly understand what is happening without reading everything.

This is useful when joining a discussion late or reviewing long email chains.

Prompt:
Explain this to me like I am 5 years old.

Prepare Client Communication

Copilot helps structure communication based on actual project context, reducing guesswork and improving clarity.

This is useful for project managers, account managers, and consultants who need to align messaging with client priorities.

Prompt:
I am a Project Manager; my client is focused on cost, performance, or change. Reference the relevant documents and communications, and suggest 1 to 3 items I should keep top of mind. Format these as if I were a Business Analyst.

Communicate Changes Clearly

Copilot supports change management by helping teams address resistance, highlight value, and reduce confusion.

This is useful when rolling out new systems, processes, or updates.

Prompt:
Please reference this document and act as my change management authority. Based on recent communications with [client or team], suggest how to manage risk and resistance to change. Include what is in it for the end user.

Keep Communication Simple

Copilot helps translate technical or complex topics into clear, client-friendly language. This is especially important when communicating with non-technical stakeholders.

Prompt:
Draft a client-facing email explaining [topic], using a professional and calm tone. Avoid technical jargon.

Review Project Workplans

Copilot helps identify issues early by reviewing plans for gaps, dependencies, and unrealistic assumptions.

This reduces risk before execution begins.

Prompt:
Review this workplan and identify gaps, sequencing issues, unrealistic assumptions, or missing dependencies.

Create Escalation Summaries

Copilot helps structure clear, concise summaries for leadership, making it easier to communicate urgency and decisions.

Prompt:
Create a concise escalation summary outlining the problem, business impact, options, and recommended decision. Reference the relevant chats, emails, and documents.

Plan Your Week

Copilot helps prioritize work by combining calendar events, emails, and tasks into a structured plan.

This reduces reactive work and improves focus.

Prompt:
Plan my week. Aggregate my calendar, flagged emails, and Teams mentions. Produce a prioritized top 10 actions and propose time blocks. Flag conflicts and suggest reschedules.

Track Progress and Risks

Copilot helps provide a quick view of progress and potential risks across projects.

This supports faster decision-making without needing full reports.

Prompt:
Are we on track for the [project or launch]? Check progress, results, and risks. Give me a probability.

Gain Insight Into Your Time

Copilot can analyze how time is spent across meetings and communications, helping identify priorities and inefficiencies.

Prompt:
Review my calendar and email from the last month and create 5 to 7 buckets for projects I spend most time on, including percentage of time and short descriptions.

Draft Internal Documentation

Copilot helps create structured documentation quickly, reducing the effort required to maintain internal knowledge.

Prompt:
Draft an SOP for submitting a change request form to Inside Sales.

Build Executive Summaries

Copilot can turn detailed reports into concise summaries that are easier for leadership to review.

Prompt:
Create a brief executive summary based on this report.

Identify Risks and Assumptions

Copilot helps surface risks and assumptions early in projects, improving planning and reducing surprises.

Prompts:
Identify all risks associated with this project based on the scope. Identify all assumptions associated with this project.

Support Performance and Management

Copilot can assist managers with structured feedback and performance planning.

Prompt:
Identify the top 10 things a manager should do for a [low, medium, high] performer in a [role] within [industry].

Making Copilot Repeatable with Saved Prompts

One of the most important ways to scale Copilot is by saving and reusing prompts. This ensures consistency across teams and reduces the need to recreate effective prompts.

To save a prompt, open Copilot in a Microsoft 365 app such as Word, Excel, or Teams. Type the prompt you want to save in the Copilot input box. If you’ve already used a prompt and want to save it, locate it in your recent prompt history.

To use a saved prompt, open the prompt library in Copilot, search or browse for the prompt, insert it into the input box, and run it.

Building a shared prompt library allows teams to standardize how Copilot is used across the organization.

What This Looks Like in Practice

The real value of Copilot is not in individual prompts. It is in how they connect across the workday.

Teams spend less time searching for information and more time acting on it. Meetings are more focused because preparation is faster, with Copilot helping create clear agendas and keep discussions on track. Communication is clearer because it is grounded in a real context. Projects move forward with fewer surprises because risks are identified earlier.

This is where teams start to see consistent gains in productivity, not by working more, but by removing the friction that slows them down.

The post How Teams Get More Done: A Guide to Microsoft Copilot Prompts appeared first on Convergence Networks.