Blogs on IT Support and Cybersecurity for Small Business

Nearly one in five Canadian businesses now use artificial intelligence to produce goods or deliver services, triple the share recorded two years earlier. That pace is why Microsoft Copilot readiness for White Rock businesses has become a permissions question well before it becomes a productivity one.

Copilot Does Not Break Your Permissions. It Uses Them.

Microsoft is unambiguous on this point. Copilot reaches only the organizational data that the signed-in user already has at least view permission to open. It does not escalate access, and it does not hand anyone a key they were not already carrying.

That reassurance is accurate. It is also the source of the problem most companies never see coming.

How Access Piles Up Without Anyone Deciding

Permissions inside a Microsoft 365 tenant accumulate quietly over years. Someone shares a folder with the whole company to save a minute. A project site outlives the project and keeps its original membership. A departed manager's files sit in a location nobody has audited since.

None of that caused visible harm before, because nobody went looking. Finding an overshared payroll spreadsheet buried three folders deep required knowing it existed in the first place. A natural-language assistant removes that requirement entirely.

Microsoft states the risk plainly in its own documentation. Content that is overshared or poorly governed affects Copilot results and increases exposure.

Latent Access Becomes Live Access

The distinction worth understanding is between what your staff can technically reach and what they have ever actually found. In most tenants, those two sets look nothing alike.

Ask an assistant to summarize what the company knows about compensation. It will search everything the person asking is permitted to see. It carries no sense that a file was shared broadly by accident four years ago.

Common sources of accumulated access include:

• Sharing links set to anyone in the organization and never revisited
• Sites where permission inheritance was broken for one folder and never restored
• Project workspaces that are inactive, ownerless, or long past their purpose
• Personal cloud storage folders shared widely during a deadline and never unshared
• Legacy groups that still include people who have changed roles internally
• Site memberships inherited from a distribution list nobody maintains

Every one of those is ordinary. Together they define what your assistant can retrieve on its first day.

The scale of the gap tends to surprise people who have run the same tenant for a decade. A site created for a single acquisition or hiring round often still carries the membership it had when the work was active. Most of the people on that list moved into other roles years ago.

Search was the accidental safeguard here, and it was never a good one. Traditional keyword search only rewarded people who already knew roughly what they were looking for and what it was called. Conversational search rewards curiosity instead, which is the entire point of the product and also the reason the access layer now matters more than it did.

The Compliance Angle Under PIPEDA

Canadian privacy law does not name AI tools, but its safeguards principle applies cleanly. The Office of the Privacy Commissioner advises organizations to keep sensitive files on secure systems and to limit employee access on a need-to-know basis.

Broad internal access to personal information was already a weak position under that guidance. Making it searchable in plain English does not create a new legal obligation. It does make an existing gap much harder to describe as theoretical.

What Is Actually Sitting in There

Consider what personal information sits in a typical tenant. Employee records, client files, accommodation and health notes, payroll banking details, performance documentation. Any of it may be resting somewhere with wider permissions than anyone intended.

Statistics Canada found that cybersecurity or privacy concerns are the leading barrier limiting AI use among Canadian businesses, ahead of cost. Among businesses with 20 to 99 employees, more than one in five named it.

That caution is well placed. It is also solvable, which is what makes Microsoft Copilot readiness for White Rock businesses worth treating as a project rather than a switch.

What a Readiness Review Actually Covers

The work is unglamorous and finite. It is a permissions cleanup with a deadline attached, and it returns value whether or not you ever license the software.

A proper review examines:

• Which sites hold sensitive content, and who can reach them today
• Where permission inheritance has been broken, and whether the reason still holds
• Sharing links that are live, broad, and no longer needed
• Sites with no owner, no recent activity, or no defined purpose
• Whether the organization-wide access group has been applied where it should not be
• Which files carry sensitivity labels, and which ones should

Microsoft ships tooling for exactly this work, and the licensing that includes the assistant includes the cleanup tools. Reports surface oversharing patterns across sites. Site owners can be prompted to review their own permissions rather than routing every decision through one administrator.

There is also a containment option worth knowing about. Individual high-risk sites can be excluded from the assistant's discovery while permissions get sorted out, without changing how staff open those files normally.

Warning Signs Your Tenant Needs This First

Some environments are close to ready already. Others carry a decade of collaboration debt, and the difference is usually visible without running a single report.

• Nobody can name the owner of at least three of your busiest sites
• Files get shared by link because requesting proper access takes too long
• Departing staff are removed from email quickly but from site memberships eventually
• Payroll, HR, or client financial records live in the same platform as everything else
• Your last permissions review predates your current head of operations

Any two of those signals suggest the cleanup deserves its own timeline rather than a slot inside a rollout week. The finding stage moves quickly, because the reports do most of the heavy lifting. Remediation depends on how many owners need tracking down and how many decisions require a conversation rather than a click.

None of this makes Microsoft Copilot readiness for White Rock businesses a long engagement. For a company of thirty or forty people, the discovery work is measured in days and the remediation in a few focused weeks. What extends the timeline is almost never technical complexity. It is waiting on the one person who knows why a folder was shared the way it was.

Sequencing Matters More Than Speed

The temptation is to license a few seats, see what happens, and clean up afterward. That order reverses the risk.

Once staff begin using the assistant, anything overshared becomes visible immediately, and often to the wrong person. Retroactive cleanup does not un-see a summary of an executive compensation file.

Microsoft's own deployment guidance puts oversharing remediation first, ahead of guardrails and compliance work. That first step has its own internal order, and the order is the point:

• Find the exposure, using reports that show which sites hold sensitive content and who can reach it
• Contain the highest-risk locations temporarily, so cleanup happens without a live audience
• Fix access and permissions properly, then remove the temporary controls once the sites are clean

Each stage is checkable. You can confirm the assistant no longer surfaces restricted content before moving on, which turns a vague worry into a pass-or-fail test.

The Governance Habit That Keeps It Fixed

Cleanup without governance decays. Sharing decisions get made daily by people focused on finishing work, not on access architecture.

What holds is a small set of durable defaults. New sites get an owner and a review date. Broad sharing links expire on a schedule. Site membership gets confirmed periodically rather than whenever someone happens to remember.

Keeping the Cleanup From Undoing Itself

Reviewing permissions quarterly is not exciting work. It is inexpensive compared with discovering the problem through a privacy complaint. Organizations that already run structured technology reviews tend to fold this in without adding meaningful overhead.

The same discipline covers the assistants and agents built on top of the platform. Those tools inherit the same permission model, so a clean access layer underneath means every tool built above it starts from a defensible position.

This is also where Microsoft Copilot readiness for White Rock businesses stops being a one-time project and becomes an operating habit. The tenant you cleaned up in March will drift by September if sharing defaults stay permissive, because collaboration platforms are built to make access easy rather than deliberate.

Why This Is Worth Doing Regardless

Businesses with no AI plans at all benefit from the identical exercise. Overshared data is a risk with or without a natural-language front end attached to it.

An employee leaves with access they should never have held. A compromised account reaches further than anyone expected. A privacy request surfaces files nobody knew were reachable. All three predate this technology, and all three shrink when permissions reflect current reality.

Professional services firms hold the sharpest version of the problem. Statistics Canada put AI use in professional, scientific and technical services at roughly a third of businesses, well above the national average. Those are the same firms holding client files under professional confidentiality obligations.

Encouragingly, none of this demands a rebuild of how your company stores or shares its work. It demands knowing what your tenant currently permits, which is a question most organizations have never sat down and answered.

Where to Start

Begin with an inventory rather than a policy. List the sites holding your most sensitive material, then find out who can currently reach each one.

The answer is usually more people than expected, and the reason is usually explainable. A rushed share during a busy quarter. A group that grew past its original purpose. An inheritance break someone made for a sound reason that outlived the reason.

None of that reflects poorly on anyone. It reflects how collaboration platforms behave when nobody is watching the access layer.

What changes with an assistant in the tenant is the cost of leaving that layer unexamined. The permissions were always there. Now they answer questions.

Sources:

• Statistics Canada, Analysis on artificial intelligence use by businesses in Canada, second quarter of 2026
• Microsoft Learn, Security for Microsoft 365 Copilot
• Microsoft Learn, Data, Privacy, and Security for Microsoft 365 Copilot
• Microsoft Learn, Configure a secure and governed data foundation for Microsoft 365 Copilot
• Office of the Privacy Commissioner of Canada, PIPEDA Fair Information Principle 7, Safeguards

Small businesses seemingly always need to take a long look at the way they do things because they need to be as efficient as possible to carve out a market share. This often means using technology to make everything work. There are many different types of technologies that can help any SMB build more efficient operations, but the two we will outline in today’s blog, are two technologies that are probably doing the most to help SMBs improve. 

By now, you’ve probably started hearing a lot about AI and how it’s doing a lot of things to disrupt the world. It seems like every modern software application boasts AI capabilities, social media feeds are plastered with generative AI content, and techy people everywhere are providing their two cents on this new technology. The main star of artificial intelligence right now is ChatGPT, so we figured we’d shed some light on exactly what it does in plain English, and how you might be able to take advantage of it.

Artificial Intelligence is beginning to sweep over modern computing and it can present some stark benefits for a business. AI has been deployed in various ways to help streamline your operations. Let’s look at five ways AI is helping businesses be their best.

Maintaining network security has proven to be more difficult for organizations as time has gone on. Like the people trying to keep them out of networks they don’t have access to, hackers are increasingly using artificial intelligence (AI) to enhance their cyberattacks and achieve various malicious objectives. Here are some ways in which hackers are using AI.

Technology can be a huge benefit or an annoying hindrance for a business. It really depends on how it is maintained or used. Just like the PC in the 1980s, Internet access in the 1990s, and the advent of social media over the past decade or so, there are a couple interesting technologies that, if properly used for business, can bring substantial value for workers, customers, and the organization as a whole. Let’s take a look at three of them.

In recent years, artificial intelligence (AI) has emerged as a powerful tool that can revolutionize small businesses. With its ability to analyze vast amounts of data and make intelligent decisions, AI has the potential to streamline operations, improve customer service, and drive growth. Let’s explore some practical applications of AI that can benefit small businesses and help them thrive in today's competitive landscape.

Artificial intelligence is becoming an integral technology for modern businesses, but you can’t just roll up to the AI store and get some AI. The machine learning algorithms that make up modern AI are integrated into the software that your business relies on. Microsoft, long known for being amongst the top business computing companies, has begun to integrate AI into their software. One place that most businesses will get first-hand experience with this technology is through their Microsoft 365 subscription. We will introduce you to Microsoft Copilot and what benefits it ultimately brings users. 

We get it: you’d expect to read the statement “AI is everywhere nowadays” as a science fiction story about the enslavement of humans by the very machines they’ve created. We aren’t quite there yet, but more and more humans are coming to rely on artificial intelligence to automate a lot of different tasks inside their businesses. Let’s take a look at what people are actually using AI for. 

Artificial intelligence, or AI, is just one way of describing the concept of machine learning technologies. AI has grown considerably over the past couple of years, so much that automation as we know it today wouldn’t exist without it. Throw in some data-driven insights and you have a technology that has cemented itself for use in a business environment, but there are some concerns with how fast it is growing and evolving.

To Identify Trends

The number one thing you need to know about data analysis is that the data you use needs to be structured in a way to allow you to get the most accurate information possible. This isn’t always easy. In order to put your business in the right position you can’t just rely on decision makers to go with their gut reaction, you need a definitive plan fueled by empirical data so that you avoid huge costs to solve small problems. The simplest way to do this is to identify trends inside and outside of your business. You can do this through a dedicated business analytics platform, using your organizational data to help you make sound business decisions. 

Improving Operational Effectiveness

Another part of the business that can be improved through the use of analysis is operations. Traditionally, the more efficient your business is, the more effective it is. This doesn’t change because you have data; but, with the data you can get a better perspective about how your business works, how your customers interact with your company, and a lot more. The better you understand the separate parts of your business the more you can confront its pain points and build effectiveness. 

Shifting Your Revenue Generation Strategies

Since you are in business to make money, it stands to reason that using any resources to help you do that is beneficial for the company. Combing through your operations and marketing data can provide opportunities that you didn’t know were there. It can make all the difference for the small business that needs to transition quickly in order to sustain operations. 

It’s been said that data is the new oil. That may or may not be true, but for the small business, drilling into your data to see the best way forward is a solid practice that will become commonplace before long. To get out in front of it, call the IT professionals at Coleman Technologies at (604) 513-9428 and we will help you get started using your data to benefit your business today.

Some of the best cybersecurity methods are practices developed over the past few years. This is because social engineering, specifically phishing, has become a major problem. There are billions of phishing emails sent each year, and some of those are so convincing that even people who have had some basic cybersecurity training fall victim to them. To fight this, security firms have started to look to tomorrow’s technologies to help them mitigate risk today. 

Artificial Intelligence - The Future of Cybersecurity 

One of the most effective ways of combating this rise in hacking is to use the most dynamic technology you have access to and make a tool that will help you mitigate the massive risks. One way is to reduce the effectiveness of these hacks. In this case the technology is artificial intelligence.

When we talk about artificial intelligence, we are talking about having a machine that learns as it is continually exposed to threats. This will work to solve common issues at first, but as these systems advance, and are exposed to user behaviors, they will be able to replace access management systems. Since the AI will be constantly monitoring systems, as well as user behaviors, workplace roles, and common actions, it will be able to recognize a person without, the need for password-protected accounts and creating ubiquitously secure endpoints. If the system recognized any deviations, an additional form of authentication such as biometrics would grant or deny access. 

Cost will initially be a factor for businesses, especially small and medium-sized businesses, but as large companies begin to truly trust these platforms, they will have viable endpoint-protection systems for small businesses. 

Cybercrime Accelerates with 5G

5G and beyond will bring a lot of changes to the user experience, of course, but it will also make huge changes to cybersecurity. Before long, the AI systems that are being developed to thwart today’s cyberthreats will become essential systems for the sustainability of mobile computing. Just think about how much cyberthreats have multiplied over the past decade after the jump from 3G to 4G. The jump to 5G isn’t going to any less dramatic.

It will be crucial for cybersecurity professionals to be able to leverage systems that are both ubiquitously available to search through large streams of data while also being capable of learning on the fly in order to ascertain what data is potentially malicious and what data is less so.

Luckily there are still years before these types of systems will be needed. Unfortunately, there are enough threats out there to be a major problem going forward. The IT professionals at Coleman Technologies can help you protect your hardware and data. Give us a call at (604) 513-9428 today!

Smarter Machines?
The first thing you have to understand about machine learning is that it is just a branch of A.I. As such, it basically describes a method of analyzing huge amounts of data in which prospective models of problem solving are automated. In layman’s terms, the computer solves basic problems without human intervention. This is significant for a few reasons, but the most glaring is that businesses today, and even small businesses, take in a lot of data. Traditionally, humans were paid to go through all this data, or it was archived and disregarded until there was a major question.

This shift is in the manner in which these machine learning systems analyze data, identify patterns, and make decisions from the analysis of those patterns.This seemingly advanced technology is being deployed at a dizzying rate and is beginning to surround us all, in our phones, on search engines, and in the systems that we manage our business data. For the small business, there are opportunities to utilize this technology to help carve out a larger market share.

Small Business Machine Learning
The philosophy behind utilizing machine learning for a business is just an extension of the overarching strategy of deploying automated systems to cut down on personnel and human resources costs. This strategy has worked in several sectors, albeit with automated systems that were more pre-programmed than “smart” like the machine learning systems.

An issue many small businesses will run into when deciding whether or not to try and innovate to the point where machine learning is an option, is where exactly it fits. Other questions persist as well. They include:

• What is the capital and operational investment of deploying this technology?
• How it will have to be utilized to provide a competitive advantage?
• What systems can be improved through the use of machine learning?
• How much time do you have until you would be at a competitive disadvantage if you didn’t invest in the technology?

Once you’ve ascertained how exactly to deploy machine learning, you can go ahead implementing it where you feel it is warranted.

Benefits of Machine Learning
A.I. and machine learning carry with it specific benefits. Some of them include:

• Forecasting business - What might be the most popular use of machine learning, the technology can be used to replace data and service analysis while being used to replace processes that were done manually or not done at all.
• Customer service - Chatbot technology essentially automates the customer service experience by directing customers to certain solutions based on query.
• E-commerce - Rolling out machine learning for your e-commerce site helps customers by adapting to customer behavior. Giving prospects and customers easy access to obtain the the products and services they are most interested in is sure to improve revenue generation.
• Reputation management - Machine learning can be set up to analyze internal and external data sources to monitor brand popularity. When it finds negative sentiment, you can use the information provided to smooth the situation over, fast.

These are only four of the many processes that can really help improve your business. As the technology improves, more A.I. and machine learning applications will be used to manage, maintain, and streamline a lot of your business’ slow-moving manual processes.

Machine Stupidity
These technologies are extremely advanced and are programmed to learn for themselves, so oversight of them may be difficult. If you are one of the many business owners that have a difficult time trusting technology, machine learning may not be for you. These constructs tend to be less predictable than typical analysis, because it is so thorough. Also, you may run into problems getting all of the data that needs to be analyzed into the system, providing results that may not be accurate for your entire business.

One could see how a small business owner can be in ‘wait and see” mode, but the problem with that strategy, however, is that your competitors may be using it now to improve their business. If you are interested in learning more about how this emerging technology can be used to make your business better, contact the professionals at Coleman Technologies today at (604) 513-9428.

Part of the problem for many healthcare institutions is that there is a staggering amount of physical documents that are used to keep track of patients, processes, and procedures. As reported by SiliconAngle, Dr. Vasi Philomin of Amazon Web Services claims there are 1.2 billion medical documents created every day in the healthcare industry, in the United States alone. With so many documents, it’s no surprise that it’s difficult for people to manage them.

And what’s a way to take out the menial tasks done throughout the workday, or organize countless documents accumulated in a collection that is impossible for humans to go through on their own? That’s right--artificial intelligence. While it might seem like a weird way to use A.I., it is certainly a viable option, and one that industry professionals are considering to boost efficiency of care and ease of use.

The Health Insurance Portability and Accountability Act (HIPAA) complicates this issue, but Amazon Web Services is hoping to challenge this with new initiatives. A service called Academic Comprehend Medical aims to help narrow down candidates for clinical trials--something that is impossible without the help of computers and artificial intelligence. Of course, this is only a small amount of what could be accomplished through the use of A.I. in the medical industry, so the future could potentially be very bright for any organizations that utilize this technology.

You can count on Coleman Technologies to keep our fingers on the pulse of any interesting technology developments in the industry. For more information about healthcare solutions, call us today at (604) 513-9428.

To get the most out of A.I., we first need to understand why A.I. seems to be the likely answer to a lot of troubles surrounding network security.

What Makes A.I. So Helpful?
Automated systems might be able to help organizations protect a network to a certain degree, but there are a lot of reasons to be cautiously optimistic about their inclusion in modern network security. Considering the lack of technology education in today’s business environment, it can be difficult to acquire the skills needed to protect against high-level threats and implement necessary security solutions. This doesn’t change the fact that security is more important than ever before, though, as more devices are being introduced to networks every day. The more devices, the more likely threats are to surface, and the more difficult it is to protect networks. A.I., backed by algorithms to detect threats, has the potential to improve network security, as well as make the jobs of internal IT departments much easier.

Of course, there are several reasons why A.I. for network security isn’t the best solution. Here are a few of them.

Considering How Threats Are Detected by Artificial Intelligence
How does A.I. detect threats? Even if machine learning gives these solutions the ability to learn over time, it has to start somewhere. A.I. initially identifies threats based on algorithms assigned to them. According to the MIT Technology Review, A.I. is essentially “trained” to detect threats based on tags assigned to specific data sets. The unfortunate side-effect of this is that the programs can essentially be reverse-engineered by hackers if they get ahold of them, effectively giving malware developers the ability to create threats that aren’t identifiable by the majority of automated systems.

Overreliance on a Single Method
With only one way to detect threats, A.I. is quite vulnerable to being exploited, as hackers can simply turn that into their own advantage. This is why it’s so important to have multiple algorithms to detect threats, as only one isn’t going to be enough to keep all threats out of your network. Consider this hypothetical scenario: your office hires a single security guard that keeps watch over the front door of your building. There are no other guards on-site to protect the building, and you don’t have security cameras. While nobody is getting in the front door, what about the other entry points? It’s a simple fact that one algorithm is easily exploitable and far from an ideal security situation.

Coleman Technologies can help your business determine the best security solutions on the market, and they can be combined with our expertise and active monitoring to ensure data security from a variety of threats. To learn more, reach out to us at (604) 513-9428.