AI Enablement
AI news, Copilot updates, and automation strategies for managed service providers.
AI Security for Business Leaders: Why This Risk Starts at the Top
Artificial intelligence is no longer something businesses are simply “watching.” It is already showing up in daily work: In each
Artificial intelligence is no longer something businesses are simply “watching.” It is already showing up in daily work: In each
Read full post on npi.net
How The ITeam Helps You Use Agentic AI Safely
Agentic AI has the potential to create value across many industries, but only if it is deployed with caution.
Agentic AI has the potential to create value across many industries, but only if it is deployed with caution.
Read full post on theiteam.ca
What is Shadow AI and How To Detect It
Key Takeaways Shadow AI—the use of AI tools without IT approval—is already present in most organizations, with only 22% of American workers using exclusively employer-provided AI tools, according to IBM. Employees turn to unauthorized AI primarily because enterprise-provided tools don't meet their productivity needs, not out of malicious intent. According to IBM's 2025 Cost of a Data Breach Report, shadow AI adds an average of $670,000 to breach costs, with 97% of AI-related breaches occurring in organizations that lacked proper access controls. Detecting shadow AI requires layered m
Key Takeaways Shadow AI—the use of AI tools without IT approval—is already present in most organizations, with only 22% of American workers using exclusively employer-provided AI tools, according to IBM. Employees turn to unauthorized AI primarily because enterprise-provided tools don't meet their productivity needs, not out of malicious intent. According to IBM's 2025 Cost of a Data Breach Report, shadow AI adds an average of $670,000 to breach costs, with 97% of AI-related breaches occurring in organizations that lacked proper access controls. Detecting shadow AI requires layered monitoring: network traffic analysis, browser-level auditing, and identity signal correlation, capabilities that align directly with managed IT and cybersecurity services. Detection alone isn't enough. Organizations need governance frameworks backed by policy, enforcement, and continuous auditing to close the gap between AI adoption and AI oversight. Your team is using AI every single day. Some of those tools went through IT review. Most did not.
Read full post on blog.symquest.com
Your Employees Are Using AI Tools You Don't Control. Here's Why That's a Problem.
Your team is already using AI tools you don't know about. It's called shadow AI, and it's quietly becoming one of the biggest data risks businesses face in 2026.
Your team is already using AI tools you don't know about. It's called shadow AI, and it's quietly becoming one of the biggest data risks businesses face in 2026.
Read full post on pandatechnology.com
AI Agents for Small Business: How to Automate Work Without Creating Risk
If you run a Tampa Bay business, you have probably wondered whether AI agents could take some work off your plate. You may also be thinking, “I do not want to hand a tool access to our email and files and just hope it behaves.” That hesitation is healthy. Owners and operations leaders want the...Continue Reading
If you run a Tampa Bay business, you have probably wondered whether AI agents could take some work off your plate. You may also be thinking, “I do not want to hand a tool access to our email and files and just hope it behaves.” That hesitation is healthy. Owners and operations leaders want the...Continue Reading
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AI Governance Framework: A Guide for Canadian Businesses
Build a practical AI governance framework for your Canadian SMB. Our guide covers principles, implementation, compliance, and how to get started.
Build a practical AI governance framework for your Canadian SMB. Our guide covers principles, implementation, compliance, and how to get started.
Read full post on cloudorbis.com
Is There a Right Way to Roll Out Microsoft Copilot for Your Business? What the Process Actually Looks Like.
Yes, there is a right way. And most businesses do not follow it. They buy the licenses, turn the tool
Yes, there is a right way. And most businesses do not follow it. They buy the licenses, turn the tool
Read full post on datasmithnetworks.com
Best AI Tools for Small Business: ChatGPT, Copilot, Claude, and Gemini Compared
If you’ve been paying attention to technology news over the last couple of years, you’ve heard the names: ChatGPT, Microsoft Copilot, Claude, Gemini. Choosing the best AI tools for your small business is no longer a hypothetical conversation. Employees are already using them, often without formal approval or any guidance from leadership. That reality shifts…Read more
If you’ve been paying attention to technology news over the last couple of years, you’ve heard the names: ChatGPT, Microsoft Copilot, Claude, Gemini. Choosing the best AI tools for your small business is no longer a hypothetical conversation. Employees are already using them, often without formal approval or any guidance from leadership. That reality shifts…Read more
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Microsoft Copilot Just Got Smarter: 5 Updates Your Team Should Be Using Now
Microsoft 365 is a platform most organizations are already paying for, but Copilot keeps changing what that investment actually delivers. Over the past 90 days, Microsoft pushed out a wave of updates that are easy to miss unless you’re paying close attention. Some are quality-of-life improvements. Others are legitimately workflow-changing. These five updates are the
Microsoft 365 is a platform most organizations are already paying for, but Copilot keeps changing what that investment actually delivers. Over the past 90 days, Microsoft pushed out a wave of updates that are easy to miss unless you’re paying close attention. Some are quality-of-life improvements. Others are legitimately workflow-changing. These five updates are the
Read full post on crimsonit.com
Natural Language Processing a Guide for Canadian Businesses
Discover how natural language processing (NLP) can automate tasks and drive growth. A practical guide for Canadian SMBs on NLP uses, implementation, and ROI.
Discover how natural language processing (NLP) can automate tasks and drive growth. A practical guide for Canadian SMBs on NLP uses, implementation, and ROI.
Read full post on cloudorbis.com
Copilot 2.0: From AI Hype to Practical ROI. Watch the Full Webinar Recording
On June 16, Larry Schwartz and Julie Hodges from Ingram Micro spent 45 minutes cutting through the noise on Microsoft 365 Copilot. No vendor pitch. No product demo. A straight conversation about what actually works, what can go wrong, and how Pittsburgh-area firms can start using AI in a way that holds up under scrutiny.
On June 16, Larry Schwartz and Julie Hodges from Ingram Micro spent 45 minutes cutting through the noise on Microsoft 365 Copilot. No vendor pitch. No product demo. A straight conversation about what actually works, what can go wrong, and how Pittsburgh-area firms can start using AI in a way that holds up under scrutiny.
Read full post on midnightbluetech.com
Taming the Wild Dog: Agentic AI Security with HashiCorp
Agentic AI is already in your organization — whether you realize it or not. It’s like a wild dog running around your office. Wily, fast, and capable of mass destruction. It needs a fence, a leash, and some serious training. That’s the reality facing IT and security leaders today. Autonomous AI agents are proliferating across enterprises at a
Agentic AI is already in your organization — whether you realize it or not. It’s like a wild dog running around your office. Wily, fast, and capable of mass destruction. It needs a fence, a leash, and some serious training. That’s the reality facing IT and security leaders today. Autonomous AI agents are proliferating across enterprises at a
Read full post on voltainc.com
AI-Ready Infrastructure: Is Your Network Built for What Is Coming?
Most networks are not ready for AI. Only 15% of organizations have infrastructure fully capable of handling modern AI workloads, while 83% of companies plan to deploy AI agents in the next year. AI-ready infrastructure is not a single product. It is the combination of network capacity, low-latency edge compute, scalable storage, clean data pipelines, and security designed for decisions made at machine speed. The Gap Between Ambition and Wiring AI is in every pitch deck, every earnings call, every Monday morning meeting. Nearly 88% of companies now use AI in at least one business function.2
Most networks are not ready for AI. Only 15% of organizations have infrastructure fully capable of handling modern AI workloads, while 83% of companies plan to deploy AI agents in the next year. AI-ready infrastructure is not a single product. It is the combination of network capacity, low-latency edge compute, scalable storage, clean data pipelines, and security designed for decisions made at machine speed. The Gap Between Ambition and Wiring AI is in every pitch deck, every earnings call, every Monday morning meeting. Nearly 88% of companies now use AI in at least one business function.2 The urgency is obvious. What is less obvious, and far more dangerous, is the quiet gap between where your business wants to go with AI and what your existing network can actually carry. Most business networks were built for a different era. They were designed for email, file shares, web browsing, and the occasional video call. Agentic AI, real-time inference, and copilots embedded in every app are not occasional traffic. They are constant, bursty, and unforgiving of latency. You are the one accountable for whether the business can actually use AI. The good news is that becoming AI-ready is a process, not a moonshot. You do not need a data center in Reykjavik. You need a plan. What Does “AI-Ready Infrastructure” Actually Mean? AI-ready infrastructure is a network and compute environment that can support AI workloads today and scale to support more of them tomorrow, without creating security, performance, or cost surprises. Practically, that means five things working together: Network capacity and low latency. AI-powered operations, especially inference and agentic workflows, demand near-zero latency to function effectively.3 Compute built for AI workloads. GPUs, accelerators, and cloud access sized for the models you plan to run. Cisco’s 2024 AI Readiness Index found only 21% of organizations had sufficient GPUs for current and future demand.4 Clean, accessible, well-governed data. AI is only as good as the data it touches. Only 19% of organizations have fully centralized data infrastructure.5 Security designed for machine-speed decisions. Identity, access, and monitoring that assume AI agents will act on behalf of your people. Governance and observability. Visibility into what AI is doing, with whom, on which systems, at what cost. Miss any one of these, and you are not AI-ready. You are AI-aspirational. Why Your Current Network Is Already Behind Here is the uncomfortable part. Cisco’s 2025 AI Readiness Index found that 54% of organizations say their networks cannot scale for today’s complexity or data volume.1 That is before most have deployed agentic AI at scale. Three specific pressures are reshaping what “enough” looks like: Inference is latency-sensitive. AI training happens in big centralized data centers, but inference, the live decisions AI makes in your apps, needs to happen fast and close to the user. Industry guidance is pushing enterprises toward scalable edge infrastructure to keep data processed close to the source.3 Agents create compounding traffic. When AI agents talk to other agents, every hop matters. Small delays that were invisible at human speed become costly at machine speed. With 83% of companies planning to deploy AI agents, the volume of machine-to-machine traffic on your network is about to change shape.1 AI workloads spike unpredictably. Unlike payroll or billing, AI load is not a calendar event. A single new use case can multiply bandwidth requirements overnight. The Five Pillars of an AI-Ready Infrastructure If you want a framework to evaluate where you stand, here it is. 1. Network You need bandwidth, low latency, and the ability to segment traffic. That usually means a modern SD-WAN or SASE posture, Wi-Fi 6E or better for in-office AI workloads, and quality-of-service policies that understand AI traffic is not optional. 2. Compute Not every business needs on-premises GPUs. Most do not. What they need is a clear answer to: where does our AI workload run, at what cost, under what latency ceiling, with what data residency requirements? For many SMBs and franchise operators, the right answer is a mix of cloud inference plus thoughtful edge compute at key locations. 3. Data Your AI is only as strong as your data pipeline. That means knowing where data lives, who owns it, how it is cleaned, and how it gets to the model that needs it. It also means resolving the data silos that will otherwise quietly starve your AI investment. 4. Security and Identity Identity is the new perimeter, and AI agents need identities too. You need conditional access, strong MFA, logging, and a clear policy on what AI agents are permitted to touch. Assume agents will, at some point, try to do something you did not plan for. Design for that. 5. Governance and Cost Control AI consumption can get expensive fast. Governance is not just about privacy policies. It is about knowing which AI tools are running in your environment, what data they see, and what they cost per month. Without that visibility, your AI budget is a hope, not a plan. How Do I Assess My AI Readiness? A practical first pass takes about 30 minutes with your leadership team and your IT partner. Ask: Can our network deliver consistent, low-latency performance to every user, including remote and in-store? Do we know where our most important business data lives, and is it clean enough to feed an AI model? Do we have MFA, endpoint protection, and logging in place across every user and device? Do we know which AI tools our team is already using (approved or not)? Do we have a budget line item for AI consumption and a way to monitor it? If you hesitate on more than two, your infrastructure is not ready to carry the AI story your leadership team is already telling customers and investors. Where the Technology Maturity Model Fits Sentry built the Technology Maturity Model (TMM) because infrastructure cannot be fixed in one sprint. It is built in stages: Operate, Secure, Integrate, Innovate. AI-ready infrastructure lives at the Integrate and Innovate stages of the model. You cannot leapfrog. If your organization is still firefighting tickets (Operate) or patching exposures after the fact (Secure), trying to bolt on agentic AI will amplify whatever is already brittle. The Pacesetters in Cisco’s 2025 research are not magical. They are disciplined. 98% of them design their infrastructure with future demand in mind.1 That is exactly what the TMM forces a business to do: decide what the next two years need to look like and build toward it. The Cost of Waiting IDC forecasts global AI infrastructure spending will reach over $902 billion by 2029.6 Your competitors are spending now. So are your vendors. So is every platform your business depends on. Downtime caused by under-built infrastructure is expensive even when AI is not in the picture. Gartner’s industry figure for IT downtime is roughly $5,600 per minute, with small and mid-sized businesses typically feeling $137 to $427 per minute depending on industry.7 Add AI-dependent workflows to that equation, and the cost of an outage is not just lost productivity. It is a customer-facing AI experience that fails in front of the very people you were trying to impress. FAQ: AI-Ready Infrastructure Do I need on-premises GPUs to be AI-ready? No. Most small and mid-sized businesses will never need on-prem GPUs. Cloud inference, thoughtful edge compute, and disciplined data practices are usually the right starting point. What is the biggest AI infrastructure mistake businesses make? Assuming AI is a software problem. Leaders buy AI tools, then find the network, data, and security underneath them cannot support what the tools promised. How long does it take to become AI-ready? Most organizations can reach a baseline in 90 to 180 days. Reaching the Innovate stage of the Technology Maturity Model, where AI is integrated into the business model, typically takes 12 to 24 months of focused work. Is AI-ready the same as cloud-ready? No. Cloud readiness focuses on where workloads run. AI readiness adds requirements around latency, data quality, model governance, and agent-aware security. A business can be fully in the cloud and still not AI-ready. Who owns AI readiness inside the company? It is a shared responsibility between the CEO, CIO or technology partner, and the business unit leaders deploying AI. One-person ownership is a red flag. So is zero-person ownership. The Sentry Take The question is not whether AI will change your business. It is whether your infrastructure can keep up with the AI your team is already using, with or without permission. You do not need a research lab. You need a roadmap, a partner who understands what AI-ready actually means, and a commitment to build in stages. Trusted. Secure. Connected. Ready to assess where your infrastructure stands? Let’s have a 30-minute conversation. Visit sentryitsolutions.com to schedule a Technology Maturity Model assessment. References Cisco, “2025 AI Readiness Index: Realizing the Value of AI,” October 2025. Retrieved from cisco.com. McKinsey & Company, “The State of AI 2025: Agents, Innovation, and Transformation,” November 2025. Retrieved from mckinsey.com. Cisco Blogs and Lightpath Communications industry guidance, “Optimizing Networks for AI in 2025” and “AI-Ready Infrastructure: A New Era of Data Center Design,” 2025. Retrieved from blogs.cisco.com and lightpathfiber.com. Cisco, “2024 AI Readiness Index,” November 2024. Retrieved from cisco.com. Cisco, “2025 AI Readiness Index,” October 2025. Retrieved from cisco.com. IDC, “Artificial Intelligence Infrastructure Spending to Reach $902Bn by 2029,” 2025. Retrieved from idc.com. Gartner industry benchmark referenced in Erwood Group and SysTech MSP analyses, 2024-2025. Retrieved from erwoodgroup.com and systechmsp.com.
Read full post on sentrytechsolutions.com
Netrio Survey Finds Mid-Market AI Adoption Is Widespread, but Readiness and Governance Gaps Remain
Censuswide survey of 401 U.S. mid-market enterprise IT leaders finds 82% already using AI in production, but only 26% say
Censuswide survey of 401 U.S. mid-market enterprise IT leaders finds 82% already using AI in production, but only 26% say
Read full post on netrio.com
How to Evaluate AI Tools and Prepare Your Business the Right Way
Businesses rushing into AI without a plan often create more problems than solutions. Learn how to properly evaluate AI tools, prepare your business for Microsoft Copilot, and build a secure, scalable AI strategy.
Businesses rushing into AI without a plan often create more problems than solutions. Learn how to properly evaluate AI tools, prepare your business for Microsoft Copilot, and build a secure, scalable AI strategy.
Read full post on snaptechit.com
Inside a Modern Generative AI Center of Excellence: Roles, Skills, and Team Structure
Are you tired of watching your artificial intelligence experiments sit in a sandbox while your competitors build real value? Most organizations hit a wall when they try to move from isolated proofs of concept to actual enterprise adoption. They end up with fragmented tools, siloed data, and teams that do not speak the same language.
Are you tired of watching your artificial intelligence experiments sit in a sandbox while your competitors build real value? Most organizations hit a wall when they try to move from isolated proofs of concept to actual enterprise adoption. They end up with fragmented tools, siloed data, and teams that do not speak the same language.
Read full post on trndigital.com
How AI-Powered Cyberattacks Work — And Why Traditional Defenses Miss Them
How AI-Powered Cyberattacks Work — Expert Guide | Ridge IT Cyber AI Threat Education · June 11, 2026 How AI-Powered Cyberattacks Work — And Why Traditional Defenses Miss Them One AI model found 10,000 critical vulnerabilities in a month. Another wrote a working exploit overnight — with no human in the loop. Here’s exactly how...
How AI-Powered Cyberattacks Work — Expert Guide | Ridge IT Cyber AI Threat Education · June 11, 2026 How AI-Powered Cyberattacks Work — And Why Traditional Defenses Miss Them One AI model found 10,000 critical vulnerabilities in a month. Another wrote a working exploit overnight — with no human in the loop. Here’s exactly how...
Read full post on ridgeit.com
The No-BS AI Automation Guide for Small Business Owners
PRACTICAL GUIDE FOR LOCAL SMBS
PRACTICAL GUIDE FOR LOCAL SMBS
Read full post on securebiznetworks.com
The Best Approaches to AI Adoption for Professional Services Firms in 2026: What’s Actually Working
What ‘AI is working’ means for the firms in this article Before the list, the criteria. Working does not mean impressive demos or teams who can describe what they did. Working means: measurable time recovered per employee, a clear and defensible compliance posture, adoption above 60 percent of licensed users within 90 days, and outcomes the
What ‘AI is working’ means for the firms in this article Before the list, the criteria. Working does not mean impressive demos or teams who can describe what they did. Working means: measurable time recovered per employee, a clear and defensible compliance posture, adoption above 60 percent of licensed users within 90 days, and outcomes the
Read full post on midnightbluetech.com
How AI-Powered Cybersecurity Is Changing Threat Detection
Cybercriminals are no longer relying on simple malware or mass phishing campaigns. Today’s attacks are…
Cybercriminals are no longer relying on simple malware or mass phishing campaigns. Today’s attacks are…
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Microsoft 365 E7 & Agent 365: What the Next Phase of Enterprise AI Means for Businesses
Artificial intelligence adoption is entering a new phase. Over the past few years, most organizations have focused primarily on experimentation by testing copilots, automating repetitive tasks, and exploring how generative AI can improve productivity. Now, however, the conversation has evolved beyond simple experimentation. Businesses are no longer asking whether AI can create value; instead, they are trying to determine how to deploy AI securely, govern it consistently across departments, monitor AI behavior at scale, prevent shadow AI risks, and generate measurable business outcomes from the
Artificial intelligence adoption is entering a new phase. Over the past few years, most organizations have focused primarily on experimentation by testing copilots, automating repetitive tasks, and exploring how generative AI can improve productivity. Now, however, the conversation has evolved beyond simple experimentation. Businesses are no longer asking whether AI can create value; instead, they are trying to determine how to deploy AI securely, govern it consistently across departments, monitor AI behavior at scale, prevent shadow AI risks, and generate measurable business outcomes from their AI investments. Microsoft’s general availability launch of Microsoft 365 E7 represents one of the company’s largest efforts to address these operational challenges at the enterprise level.
Read full post on datalinknetworks.net
Should Your Business Use Microsoft Copilot? An Honest Answer.
The short answer Wondering if your business should be using Copilot? The short answer is yes, if two specific conditions are in place. If either is missing, the right move is to get those conditions right first. Rushing into Copilot without them does not usually end with a failed AI project. It ends with a
The short answer Wondering if your business should be using Copilot? The short answer is yes, if two specific conditions are in place. If either is missing, the right move is to get those conditions right first. Rushing into Copilot without them does not usually end with a failed AI project. It ends with a
Read full post on midnightbluetech.com
AI Copilot 1.0 Webinar Recording: Beyond the Hype
On June 23, 2026, Datasmith hosted a live webinar on Microsoft Copilot with Julie Hodges, a Microsoft Copilot Specialist from
On June 23, 2026, Datasmith hosted a live webinar on Microsoft Copilot with Julie Hodges, a Microsoft Copilot Specialist from
Read full post on datasmithnetworks.com
AI Cost Sprawl: The Spend You Can’t See and How to Get It Under Control
AI Readiness Assessment Download Now Most leaders can tell you what they spend on Microsoft 365, their ERP, or their cybersecurity stack. Ask them what they spend on AI, and the room goes quiet. That silence is the problem. AI tools are multiplying across departments — a ChatGPT subscription here, a Copilot rollout there, a
AI Readiness Assessment Download Now Most leaders can tell you what they spend on Microsoft 365, their ERP, or their cybersecurity stack. Ask them what they spend on AI, and the room goes quiet. That silence is the problem. AI tools are multiplying across departments — a ChatGPT subscription here, a Copilot rollout there, a
Read full post on corsicatech.com
Microsoft Copilot Is Not Going to Train Itself. What It Actually Takes to Get Your Team Using It Every Day.
You activated the licenses, sent the announcement, maybe you even ran a quick walkthrough. Three weeks later, most of
You activated the licenses, sent the announcement, maybe you even ran a quick walkthrough. Three weeks later, most of
Read full post on datasmithnetworks.com
Construction Firms Don’t Need More AI Tools—They Need a Better AI Foundation
AI has enormous potential for construction firms, but success doesn't begin with buying another tool. It begins with clean processes, clear governance, and solving the right business problem first.
AI has enormous potential for construction firms, but success doesn't begin with buying another tool. It begins with clean processes, clear governance, and solving the right business problem first.
Read full post on snaptechit.com
What Is MCP (Model Context Protocol)? A Business Leader’s Guide to AI Integration
Learn what MCP (Model Context Protocol) is, how it connects AI to business software, and why Long Island business leaders should understand its role in secure AI adoption.
Learn what MCP (Model Context Protocol) is, how it connects AI to business software, and why Long Island business leaders should understand its role in secure AI adoption.
Read full post on flexibleit.com
From Pilot to Productivity: Embedding Microsoft Copilot Across Enterprise Workflows
Discover how to embed Microsoft Copilot across enterprise workflows for higher productivity, ROI, and streamlined AI adoption.
Discover how to embed Microsoft Copilot across enterprise workflows for higher productivity, ROI, and streamlined AI adoption.
Read full post on trndigital.com
How AI-Driven Network Monitoring Catches Problems Before You Notice
Direct Answer: AI-driven network monitoring establishes behavioral baselines for every device and traffic pattern on your network, then flags deviations automatically — often resolving issues before anyone at your business notices something is wrong. Most business owners in the Salinas Valley know the sequence by heart: something stops working, someone calls IT, IT investigates, and
Direct Answer: AI-driven network monitoring establishes behavioral baselines for every device and traffic pattern on your network, then flags deviations automatically — often resolving issues before anyone at your business notices something is wrong. Most business owners in the Salinas Valley know the sequence by heart: something stops working, someone calls IT, IT investigates, and
Read full post on adaptiveis.net
AI-Driven IT Support: Enhancing Productivity and User Experience
Instead of taking on your help desk, AI-driven IT support seeks to remove the friction that slows down your staff. This results in fewer recurrent tickets, faster resolutions, and a more modern support experience for SMBs—self-service that truly works, proactive fixes before customers complain, and technicians who devote more time to high-value issues. This will show you how to apply AI in the help desk, where it fits, and what to automate first, without sacrificing security, compliance, or human interaction.
Instead of taking on your help desk, AI-driven IT support seeks to remove the friction that slows down your staff. This results in fewer recurrent tickets, faster resolutions, and a more modern support experience for SMBs—self-service that truly works, proactive fixes before customers complain, and technicians who devote more time to high-value issues. This will show you how to apply AI in the help desk, where it fits, and what to automate first, without sacrificing security, compliance, or human interaction.
Read full post on leaftechit.comPopular MSPs
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