If your experience with AI so far has been asking ChatGPT to draft an email or summarize a meeting, then you are familiar with the power of generative AI. Generative AI, as experienced using traditional chat-style interfaces, has proven to be an incredibly useful tool. Still, it has a major limitation: it sits there and waits for you to type.

We are now entering the next phase of the technology: Agentic AI, which can seamlessly integrate with your existing systems like CRM, email, and spreadsheets, addressing common technical concerns for small businesses.

For small business owners, this distinction is critical. It's about giving small teams a sense of empowerment and confidence by starting small with pilot projects that let software initiate, decide, and act within clearly defined boundaries. This takes AI from passive observer to active participant. However, it isn't about replacing employees or deploying sci-fi autonomy; it's about augmenting your current workforce.

You can think of it this way:

• Generative AI is a tool, such as a typewriter or a calculator
• Agentic AI is a system, such as a workflow or a delegation

Agentic AI is the difference between software that waits for instructions and software that gets things done.
 

Agentic AI is your junior assistant

Technically, agentic AI refers to systems that can take a high-level goal, break it down into steps, use tools (like your email, CRM, or spreadsheets), make intermediate decisions, and act repeatedly until the goal is met.

But this sounds abstract. To understand how this fits into your business, don't compare it to software; instead, compare it to a junior operations assistant.

Imagine hiring a bright, junior employee. You wouldn't just say "write this email." Instead, you might say, "Check our inventory every morning. If stock is below 10 units, draft a reorder form, but if it's below 5 units, mark it as urgent and Slack me immediately."

A junior assistant can:

• Check systems - look at inventory
• Follow procedures - compare against the 10-unit rule
• Make decisions - standard reorder vs. urgent escalation
• Escalate - when a situation calls for it, or if unsure of what action to take

Agentic AI does exactly this. It doesn't just talk; it does.
 

Why this matters specifically for small businesses

Enterprise companies solve problems by throwing headcount at them. Small businesses don't have that luxury, and may face specific constraints:

• The many hats problem: Your best salesperson is also your support lead and occasionally your IT fix-it person
• Trapped knowledge: Critical processes exist only in the owner's head
• Inconsistent execution: You know what to do, but because you are busy, it doesn't always get done

The value proposition here is non-technical. Agentic AI isn't about making your business "smarter" in a creative sense; it makes your business more consistent. 
 

The agentic AI framework: Delegate → guardrail → observe

Let’s see how a framework can help with implementation. The delegate, guardrail, observe paradigm is both lean and sufficient to get the job done without massive disruption to your business.

1. Delegate outcomes, not tasks

Don't ask "What can this AI tool do?" Ask "What outcome do we repeatedly want to achieve?"

• Bad delegation: "Write a sales email."
• Good delegation: "Manage the follow-up process for all leads who haven't replied in 48 hours."

2. Add guardrails before autonomy

Agentic AI works best when it is constrained, not free roaming. You must define what the agent is not allowed to do.

• Permissions: Can it draft the email, or send it?
• Budget: Can it spend up to $50, or $0?
• Escalation: "If the customer uses the word 'angry' or 'refund', stop and alert a human."

3. Observe before you scale

To eliminate faulty autonomous actions and tweak your agentic workflow early, start in "recommendation mode." Phase in your autonomy plan to avoid being surprised by outcomes.

• Phase 1: The agent suggests an action ("I recommend sending this email"). You approve it.
• Phase 2: You review the agent's logs weekly.
• Phase 3: Once the agent is 99% accurate, you allow it to act autonomously.

Practical use cases: Focus on leverage, not magic

When implementing agents, we stop thinking about prompts (single interactions with AI) and start thinking about loops. We want to think in, and build, a cycle of goal → decision → action. 

Here are some examples of what this looks like in the real world.

1. Operations: The "inventory watchdog"

The agentic loop for our inventory watchdog would be rooted in monitoring your inventory database 24/7. The goal could be something like "prevent stockouts without manually checking spreadsheets daily." Then comes the decision: Is stock item A < threshold B? If yes, is the preferred vendor available? Finally comes the action: The agent drafts a purchase order and places it in your "to approve" folder. It creates the leverage; you provide the final sign-off.

2. Sales and CRM: The "lead nurturer"

The lead nurturer has an agentic loop of watching incoming leads and CRM activity. Its goal? To ensure no lead goes cold. The decision could be a simple set of rules such as: Has this lead responded in 3 days? If no, send follow-up #1. If yes, analyze the sentiment. Is it positive or negative? If positive, the action could be to schedule a meeting on your calendar. If negative, tag as "not interested" in the CRM to keep your data clean.

3. Finance: The "invoice chaser"

The agent's loop. Scan unpaid invoices. The goal would be to reduce the number of days sales outstanding (DSO). The decision: Is the invoice 5 days overdue? Send a polite reminder. Is it 30 days overdue? Draft a sterner email and flag it for the CFO. And finally, the action would be for the agent to automatically manage the follow-up cadence, ensuring cash flow isn't disrupted by human forgetfulness.
 

Reality check: What agentic AI is not

To prevent disappointment, limitations should be clearly outlined. Despite its robust capabilities, agentic AI is not a silver bullet. It won’t fix broken processes. If your current invoicing process is a mess that no one understands, an AI agent will automate the mess. Agentic AI also requires ownership. As the process manager, you are responsible when the agent makes a mistake. Remember this agentic golden rule: If a process is unclear to a human, it will be unclear to an AI agent.
 

Getting started: A sensible entry path

Don't overhaul your entire company overnight. You should treat your experimentation with agentic AI as a pilot program. First, identify one boring workflow. Pick something rules-based, repetitive, and low-risk, such as categorizing support tickets or checking for missing receipts. Then, document the decision points in the workflow by writing down exactly how you make the relevant decisions (e.g., "If X then Y"). Make sure you define evaluation metrics as well to assess outcomes.

Time to implement. Start with limited autonomy: allow the agent to draft the work, but require human approval before completing the action, such as "send" or "finalize." Once this is done, you measure outcomes. Was there a measurable positive impact on your business results? Did you save time? Did consistency improve? Did you increase revenue? Success begets success. Once you see the possibilities of agentic AI in your own business, practical success can follow by repeating this incremental approach.

The strategic takeaway

Over the coming few years, the competitive gap between small businesses won't be about who uses AI; it will be about who delegates effectively to it. Agentic AI allows you to scale your execution, not just your ideas. It is the force multiplier that allows a team of five to operate with the consistency and capacity of a team of twenty.

If you've been hearing about "the cloud" for years but still aren't sure what it means for your business, we get it. Let's cut through the noise.

Put simply, cloud computing (aka “the cloud”) is renting computing power instead of buying it. Rather than purchasing servers, software licenses, and IT gear that sits in your office, you access these resources over the internet on a pay-as-you-go basis.

It’s like switching from owning a car to using rideshare. You still get where you need to go, but someone else handles maintenance and repairs while you focus on running your business.


What cloud computing IS
Cloud computing delivers servers, storage, databases, and software over the internet on-demand. Instead of investing in expensive hardware that becomes outdated, you access resources as needed from cloud providers. The three main types are Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

For most businesses, SaaS applications like email, accounting software, or CRM tools are your first cloud experience. These web-based apps eliminate software installations and provide automatic updates. All you need to do is select the provider that fits your needs, and their software is available for your business to use nearly instantaneously.


What cloud computing ISN'T
Cloud computing isn't just storing files online, though that's often where you start. It's also not a magic solution that automatically fixes all IT problems. Many business owners worry about security, but reputable cloud providers often offer better security than most small businesses can implement on their own.

Cloud computing also isn't necessarily more expensive. While costs vary based on services, resources, and usage, many businesses find significant savings by eliminating hardware purchases, maintenance contracts, and extensive IT staff needs.


Why the cloud actually makes sense for your business
Immediate cost relief: You can achieve over 35% in annual operating cost savings by deploying cloud services. This is accomplished by eliminating large upfront expenses for hardware and software, reducing IT maintenance costs, and only paying for what you actually use.

Business agility that works: The cloud lets you scale resources up or down based on actual demand rather than planning for peak capacity year-round. Busy season? Increase computing power instantly. Slower periods? Scale back and reduce costs. This flexibility is gold for growing businesses that can't predict future IT needs.

Real disaster recovery: Cloud providers store your data in multiple locations, offering better disaster recovery than most businesses achieve independently. Power outage, flood, or other disruption? Your data and applications remain accessible from any internet connection. Many cloud services provide 99.9% or better uptime guarantees.


The hard truth about getting started
Before moving to the cloud, it’s imperative that you assess your current IT costs including hardware, software licenses, maintenance, and staff time. Consider your growth projections and whether your current systems can scale appropriately.

Start small with one or two applications rather than attempting a complete migration immediately. Many businesses begin with email or file storage services before moving critical applications to the cloud. This gradual approach builds confidence while minimizing risk.

Work with experienced partners who can guide you through the decision-making process. Look for providers who offer comprehensive support, transparent pricing, and proven expertise across multiple cloud platforms. The right partner helps you understand not just what's possible, but what makes sense for your specific situation.

Cloud computing isn't about following technology trends. It's about positioning your business for sustainable growth while reducing operational complexity. When implemented thoughtfully, cloud services provide the foundation for innovation, efficiency, and competitive advantage.

For years, many technology resellers have viewed the SMB market as a volume play—competitive hardware deals, transactional software sales and tight margins. But today's SMB customers are changing, and with that change comes a significant opportunity for partners willing to evolve alongside them.

Small and midsize businesses are investing in technology differently than they were just a few years ago. They're looking for solutions that help them operate more efficiently, strengthen security, support hybrid work and unlock the benefits of AI. More importantly, they're looking for trusted advisors who can help them navigate these decisions.

The question isn't whether SMB customers are spending on technology. It's where they're spending and how partners can position themselves to capture more of that investment.


The rise of recurring revenue.

One of the biggest shifts happening in the SMB market is the move toward recurring revenue models.

Cloud subscriptions, managed services, security monitoring, device lifecycle management and AI services all create opportunities for partners to build predictable revenue streams while delivering ongoing value to customers. SMBs increasingly prefer technology solutions that are easy to consume, scalable and supported by experts they trust.

For resellers, this means moving beyond one-time transactions and identifying opportunities to attach services, support and recurring solutions that deepen customer relationships over time.

The most successful partners aren't simply selling products. They're building practices around outcomes.


AI is creating new conversations.

Nearly every SMB customer has questions about AI.

Some want to improve productivity. Others want to automate repetitive tasks. Many are trying to understand where AI fits into their business at all.

The good news is that SMB customers don't need complex AI strategies to see value. Most are looking for practical use cases that help employees work smarter, save time and make better decisions.

This creates a natural opportunity for partners to lead conversations around AI readiness, data management, governance, device modernization and productivity solutions. The partners that can simplify AI for SMB customers will be well positioned to grow alongside them.


Security is becoming a business priority.

Not long ago, cybersecurity was often viewed as an IT issue. Today, it's a business issue.

SMB customers understand that a security incident can impact operations, customer trust and revenue. Yet many still lack the resources or expertise needed to manage an increasingly complex threat landscape.

This creates opportunities for partners to deliver more than products. Security assessments, managed security services, identity protection, networking security and compliance support are all areas where customers need guidance.

Security conversations also tend to open the door to broader technology discussions, making them one of the most effective ways to expand customer relationships and increase long-term value.


Workplace modernization is still a growth driver.

Many SMBs are running aging devices, outdated collaboration tools and fragmented technology environments that create friction for employees and IT teams alike.

As organizations continue to embrace hybrid work and AI-enabled productivity tools, modernizing the workplace has become more than a hardware refresh. It's an opportunity to improve employee experiences, strengthen security, simplify management and support future growth.

Partners that connect device modernization to broader business outcomes are finding new ways to expand opportunities beyond the initial sale.


Services are where relationships grow.

Ask successful partners where some of their most profitable opportunities originate, and many will point to services.

Whether it's cloud migrations, cybersecurity assessments, lifecycle services, deployment support, data readiness initiatives or ongoing managed services, professional services create deeper customer engagement and help uncover future opportunities.

Services don't just increase revenue. They help establish credibility, build trust and position your business as a strategic resource rather than a technology supplier.


Turning opportunity into action.

The SMB market isn't standing still. Customers are adopting new technologies, facing new challenges and looking for partners who can help them move forward with confidence.

That's exactly why we created the SMB Growth Hub.

The SMB Growth Hub brings together practical growth strategies, solution guidance, training resources and ready-to-use programs designed to help you identify new opportunities and expand your SMB business. Whether you're focused on growing recurring revenue with Microsoft Cloud, monetizing AI, leading with security, modernizing workplaces or building professional services practices, you'll find actionable resources built specifically for technology resellers.

The opportunity is already here. The question is where you'll start.

Visit the SMB Growth Hub

Let’s talk about overcoming reservations, understanding your options and leveraing AI to align with specific business goals.

AI helps businesses simplify, automate and improve business outcomes, but it is not meant to be the only thing your company relies on.

For SMBs, this message is: AI is for everyone. There are two main variations of AI that many businesses choose from—assistants and agents. Think of assistants as tools that respond when you ask for help—drafting emails, summarizing meetings or generating content. Agents go a step further by carrying out defined workflows with minimal intervention, such as qualifying leads, managing customer onboarding or routing support requests.

But making investments into your business with the right AI is not a simple decision and shouldn’t be made based on hype alone.

To add AI to your business toolbox, you’ll need ABC-style guidance and we’re here to provide just that.

A—address your concerns, overcome your objections and dispel misconceptions.

B—build your understanding of the AI landscape and discover your right-fit options.

C—connect the right AI tools to the business outcomes that you’re trying to achieve.

Addressing concerns

Let’s start with the common reservations many SMBs have for adopting AI into their business. Some of the most common questions we’ve heard are:

• Is AI safe for my business?
• Do I need a technical team?
• What if no one on my team knows how to use it?
• Can my business actually afford AI?

While these are all valid questions, they do have answers.

Media headlines like to paint AI as a safety risk when it comes to data exposure, workforce reductions, morality and environmental sustainability. And we certainly can’t guide your moral compass, but we can dispel some of the rumors. Many of these concerns can be remediated through having conversations with real businesses utilizing AI tools right now. Ask questions, engage in dialogue and gain a better understanding of the impacts businesses are seeing from using AI. Additionally, piloting AI tools for free is another great way to determine if it’s a good fit for your business. Try it before you buy it, as they say.

As far as engaging in a formal technical team—no, you don’t need that. AI isn’t as inaccessible and complicated as it used to be. It no longer requires multiple team members in rotating shifts to implement and maintain it. All you need is someone willing to learn—and there are plenty of both paid and free tools for your team to leverage. While it does take a little bit of time to learn the AI tool and develop some level of skillset to master it, you don’t need to be an AI expert to implement it in your business.

AI affordability is relative. Enterprise-grade, customized, multi-agent AI systems are expensive. But smaller models, even lightweight agents, can be affordable and achievable for every SMB. Remember, AI is an investment in your business—so you get to decide how much money you’re comfortable spending on this business aide.

As Michael Wier, technical enablement architect at Ingram Micro says, “AI is a much more mature market now and the past fears of investing into the technology without much of a return is not as big of a concern as it used to be. Success is seen much sooner.”

Building an understanding of the AI landscape

Exploration is key in navigating AI. The more you explore, the more you will discover what feels right and what doesn’t work. Before you start exploring, there are two main questions you need to consider:

1. What is the return on investment (ROI) and how long will it take before I see it?

2. Am I getting innovation in return?

ROI is an important factor in every business decision. But ROI can mean different things to different people. Sure, there’s a real financial benefit to implementing AI. Time is also a form of ROI that matters. How much time are you getting back in your day because of AI?

There’s also an innovation benefit that becomes realized when you allow AI to assist in taking over tasks, giving room for your business to do things it hasn’t done before.

AI is built for pattern recognition. It can produce some incredible results for your business that humans wouldn’t naturally think of, or take a long time to discover. And that benefit is absolutely worth focusing on, too.

Here are the main things you need to keep in mind when finding the right AI tool:

• Set realistic goals and find the right AI tool to achieve said goals. The focus should always be on the outcomes you’re hoping to achieve with AI—this is the most important thing to remember.
• Have perspective—you shouldn’t expect AI to come into your business and perform a miracle. Stay grounded and remember it’s just a tool.
• Pilot your options. Almost every AI solution on the market today has a free tier or low-cost option that you can try.

Connecting AI solutions to outcomes

Think of AI along the same lines of having a successful employee—it fulfills the role or task it is assigned and does it well. Aim for the ROI or the innovation you want immediately. Give it time—but not too much time. In roughly 6 months, you should have a good idea if it’s achieving the goal you’ve set for it. Just don’t let it become a money pit or waste of time.

While there are some simplistic, plug-and-play agentic AI solutions on the market where you can pick a task and implement an agent with a few clicks, it’s always good to ensure your investment is going towards an agent that is designed for your business with your customizations. Using an off-the-shelf AI solution is akin to everyone hiring the same person—it might get the job done, but it won't reflect your processes, your expertise or what makes your business different.

Again, think of those outcomes. Instead of searching for an AI agent, search for a client onboarding assistant that answers common questions 24/7 while your team focuses on serving customers. Instead of automating everything, automate repetitive tasks so your team can spend more time building relationships and growing the business. Placing your value in the AI tool on actual outcomes you want to achieve is the best approach in finding the right one for your business.

AI doesn't have to be intimidating, expensive or all-encompassing. Start with a challenge you want to solve for and explore the tools available. The businesses seeing the greatest success with AI aren't chasing every new trend—they're making thoughtful investments that solve real problems. When you’re ready to take the step in customizing your AI tool, Ingram Micro is here to help.

Explore AI Solutions

If your experience with AI so far has been asking ChatGPT to draft an email or summarize a meeting, then you are familiar with the power of generative AI. Generative AI, as experienced using traditional chat-style interfaces, has proven to be an incredibly useful tool. Still, it has a major limitation: it sits there and waits for you to type.

We are now entering the next phase of the technology: Agentic AI, which can seamlessly integrate with your existing systems like CRM, email, and spreadsheets, addressing common technical concerns for small businesses.

For small business owners, this distinction is critical. It's about giving small teams a sense of empowerment and confidence by starting small with pilot projects that let software initiate, decide, and act within clearly defined boundaries. This takes AI from passive observer to active participant. However, it isn't about replacing employees or deploying sci-fi autonomy; it's about augmenting your current workforce.

You can think of it this way:

• Generative AI is a tool, such as a typewriter or a calculator
• Agentic AI is a system, such as a workflow or a delegation

Agentic AI is the difference between software that waits for instructions and software that gets things done.
 

Agentic AI is your junior assistant

Technically, agentic AI refers to systems that can take a high-level goal, break it down into steps, use tools (like your email, CRM, or spreadsheets), make intermediate decisions, and act repeatedly until the goal is met.

But this sounds abstract. To understand how this fits into your business, don't compare it to software; instead, compare it to a junior operations assistant.

Imagine hiring a bright, junior employee. You wouldn't just say "write this email." Instead, you might say, "Check our inventory every morning. If stock is below 10 units, draft a reorder form, but if it's below 5 units, mark it as urgent and Slack me immediately."

A junior assistant can:

• Check systems - look at inventory
• Follow procedures - compare against the 10-unit rule
• Make decisions - standard reorder vs. urgent escalation
• Escalate - when a situation calls for it, or if unsure of what action to take

Agentic AI does exactly this. It doesn't just talk; it does.
 

Why this matters specifically for small businesses

Enterprise companies solve problems by throwing headcount at them. Small businesses don't have that luxury, and may face specific constraints:

• The many hats problem: Your best salesperson is also your support lead and occasionally your IT fix-it person
• Trapped knowledge: Critical processes exist only in the owner's head
• Inconsistent execution: You know what to do, but because you are busy, it doesn't always get done

The value proposition here is non-technical. Agentic AI isn't about making your business "smarter" in a creative sense; it makes your business more consistent. 
 

The agentic AI framework: Delegate → guardrail → observe

Let’s see how a framework can help with implementation. The delegate, guardrail, observe paradigm is both lean and sufficient to get the job done without massive disruption to your business.

1. Delegate outcomes, not tasks

Don't ask "What can this AI tool do?" Ask "What outcome do we repeatedly want to achieve?"

• Bad delegation: "Write a sales email."
• Good delegation: "Manage the follow-up process for all leads who haven't replied in 48 hours."

2. Add guardrails before autonomy

Agentic AI works best when it is constrained, not free roaming. You must define what the agent is not allowed to do.

• Permissions: Can it draft the email, or send it?
• Budget: Can it spend up to $50, or $0?
• Escalation: "If the customer uses the word 'angry' or 'refund', stop and alert a human."

3. Observe before you scale

To eliminate faulty autonomous actions and tweak your agentic workflow early, start in "recommendation mode." Phase in your autonomy plan to avoid being surprised by outcomes.

• Phase 1: The agent suggests an action ("I recommend sending this email"). You approve it.
• Phase 2: You review the agent's logs weekly.
• Phase 3: Once the agent is 99% accurate, you allow it to act autonomously.

Practical use cases: Focus on leverage, not magic

When implementing agents, we stop thinking about prompts (single interactions with AI) and start thinking about loops. We want to think in, and build, a cycle of goal → decision → action. 

Here are some examples of what this looks like in the real world.

1. Operations: The "inventory watchdog"

The agentic loop for our inventory watchdog would be rooted in monitoring your inventory database 24/7. The goal could be something like "prevent stockouts without manually checking spreadsheets daily." Then comes the decision: Is stock item A < threshold B? If yes, is the preferred vendor available? Finally comes the action: The agent drafts a purchase order and places it in your "to approve" folder. It creates the leverage; you provide the final sign-off.

2. Sales and CRM: The "lead nurturer"

The lead nurturer has an agentic loop of watching incoming leads and CRM activity. Its goal? To ensure no lead goes cold. The decision could be a simple set of rules such as: Has this lead responded in 3 days? If no, send follow-up #1. If yes, analyze the sentiment. Is it positive or negative? If positive, the action could be to schedule a meeting on your calendar. If negative, tag as "not interested" in the CRM to keep your data clean.

3. Finance: The "invoice chaser"

The agent's loop. Scan unpaid invoices. The goal would be to reduce the number of days sales outstanding (DSO). The decision: Is the invoice 5 days overdue? Send a polite reminder. Is it 30 days overdue? Draft a sterner email and flag it for the CFO. And finally, the action would be for the agent to automatically manage the follow-up cadence, ensuring cash flow isn't disrupted by human forgetfulness.
 

Reality check: What agentic AI is not

To prevent disappointment, limitations should be clearly outlined. Despite its robust capabilities, agentic AI is not a silver bullet. It won’t fix broken processes. If your current invoicing process is a mess that no one understands, an AI agent will automate the mess. Agentic AI also requires ownership. As the process manager, you are responsible when the agent makes a mistake. Remember this agentic golden rule: If a process is unclear to a human, it will be unclear to an AI agent.
 

Getting started: A sensible entry path

Don't overhaul your entire company overnight. You should treat your experimentation with agentic AI as a pilot program. First, identify one boring workflow. Pick something rules-based, repetitive, and low-risk, such as categorizing support tickets or checking for missing receipts. Then, document the decision points in the workflow by writing down exactly how you make the relevant decisions (e.g., "If X then Y"). Make sure you define evaluation metrics as well to assess outcomes.

Time to implement. Start with limited autonomy: allow the agent to draft the work, but require human approval before completing the action, such as "send" or "finalize." Once this is done, you measure outcomes. Was there a measurable positive impact on your business results? Did you save time? Did consistency improve? Did you increase revenue? Success begets success. Once you see the possibilities of agentic AI in your own business, practical success can follow by repeating this incremental approach.

The strategic takeaway

Over the coming few years, the competitive gap between small businesses won't be about who uses AI; it will be about who delegates effectively to it. Agentic AI allows you to scale your execution, not just your ideas. It is the force multiplier that allows a team of five to operate with the consistency and capacity of a team of twenty.

So you have generative AI—now what?

Generative AI (GenAI) is going for gold and making Olympic leaps and bounds to be the go-to model of AI that every business wants their hands on. And it’s definitely worth the hype—it’s the more affordable AI solution and it can definitely transform the way we all work. But like every new technology, you need to have a solid security plan to avoid being targeted by hackers.

Before we dive into the topic of securing GenAI, we first must understand the difference between private and public instances. Public GenAI uses data from the internet to generate answers. They also model log prompts and often use them to retrain. Private GenAI is a more controlled version of public, as it can be trained to pull information from a business specifically with governed data flows. They can also be fully isolated and not connected to the public internet at all.

Now that we’ve got that out of the way, there’s a few common risks of GenAI models that AI developers need to understand:

• Model inversion—Did you know that attackers have been known to try to extract information about the training data from the model itself? Yikes. This could expose sensitive training data like customer records.
• Data—If a hacker can get into your model, what can they learn from it? What kind of information would they then have access to? It’s important to know the answers to these questions before data is fed to any GenAI model.
• Prompt injection—Hackers can manipulate models by pushing guardrails with prompts. Yes, using your own guardrails against you. This could override instructions and leak internal information.
• Data poisoning—Hackers can also modify or inject malicious data into the training dataset so the model learns incorrect behavior. This could cause AI-generated outputs to become unreliable or harmful.
• Data exfiltration—This is the act of accessing and stealing sensitive data through phishing, misused privileges and the like. You know, traditional cybersecurity risks.

Alright, housekeeping checklist is complete. Let’s talk about how you can protect your specific model of GenAI.

Securing private models

The most common approach to securing private GenAI models is actually just following the industry standard strategies and frameworks. These include governance, risk and compliance (GRC) strategies. Following the EU AI Act for international standards is also a great move, too. Here are a few more:

• Have a strong data collection process—Know your data. Don’t just take it from any old public source. Guard it like your business depends on it (because it does).
• Get a good AI security software—There are options out there that help you monitor data analytics and govern your AI models. This could look like AI model monitoring or anomaly detection, data leakage prevention, prompt security tools and transparency or traceability platforms. Of course, our Ingram Micro experts can help you find the right one for your customers’ specific model and needs. And all of these options do not require a specific AI model.
• Set up guardrails—I know I just told you that your guardrails are vulnerable, but don’t let that stop you from setting them up. You still want to do everything in your power to protect sensitive data.
• Partner with a great, trustworthy infrastructure partner—There are so many options out there to help you with your infrastructure. The biggest ones are AWS, Azure, Google and IBM. But they all have strong reputations for secure infrastructures and you truly can’t go wrong with any of them.

Securing public models

Considering that people are using these from public domains, there’s not a whole lot that you can do as a service provider or a business to securing the GenAI models themselves, but you can educate your customers and their staff on how to use them safely.

The number one rule for using a public GenAI model is to be very careful what you put into it. It is meant to provide you with answers using publicly available internet resources, remember? So, you should never ask it to review important and sensitive information like spreadsheets or contracts. Don’t ever feed it anything with credit card information or personal details.

To that point, public GenAI also can get it wrong. Never rely on them for legally binding or sensitive business decisions.

Many businesses opt to block their employees from using public GenAI models as a just in case, and that’s not a bad idea. But so long as your customers and their staff understand that prompts and outputs could indirectly influence model behavior or future training data, they should be okay to use these models in moderation.

Key takeaways

AI is an incredible opportunity for businesses of all shapes and sizes to streamline workflows, obtain more productivity and reach ultimate efficiency. But like everything linked to technology, it’s not exempt from cyber attacks.

Here’s a quick summary of what everyone with GenAI needs to do to keep it secure:

• Understand how AI handles data—where data and prompts are stored, whether the model is trained on that data and who can access it.
• Humans are still needed— ensure people provide oversight for AI-generated decisions and maintain accountability.
• Check it often—AI isn’t perfect. Follow your standard cybersecurity policies, monitor outputs regularly and use auditing tools where possible.

Farhan Chowdhury, Ingram Micro senior technical enablement engineer, explains it like this: “Generative AI should be treated like any other enterprise application. It requires the same security discipline—governance, monitoring and controlled access to ensure it delivers value without introducing unnecessary risk.”

Personally, I think AI is here to stay and we need to embrace it. But most importantly, we need to treat it like any other technology tool and ensure that we don’t give hackers more access to the things we don’t want them to have. Zero trust, right?

When you’re ready to dive deeper into this conversation to figure out what kind of additional security softwares you’d like to explore for your customers, our team of AI experts are here.

The basics and beyond—understanding AI through an enterprise lens.

No matter how big or small a company is, everyone can benefit from incorporating AI into their daily workflows. We’ve talked a lot about how SMBs can get on the AI train, but what about enterprises?

Here are 3 things every enterprise level business needs to know about AI:

AI is customizable.

If you have the budget, we can help you build any AI solution. The key is understanding the outcome your customer wants. Ideally, AI is supposed to alleviate repetitive and redundant tasks to complement the humans in office.

There are three levels of AI: entry level, mid-tier and high-end. Entry level AI solutions are essentially plug and play—simply buy a license and have AI capabilities. Mid-tier is where you get more involved—creating AI solutions that increase efficiency by removing simpler tasks from busy plates. High-end is the most extensive—automating as much as possible and leaving QA for the humans.

Many businesses, including SMBs and enterprise organizations, opt for the entry level AI solutions. But enterprises with bigger budgets, the ones looking to get the most out of AI, are all in for those mid-tier and high-end options.

Security and the AI market.

Security has high market value in the AI world. Businesses are using AI security solutions in two different ways: monitoring networks and monitoring AI solutions.

With AI, you can create and monitor a baseline for an entire network, as AI notices differentiations and can automatically shut down or isolate the affected systems to prevent spread of attacks.

Organizations also need to keep in mind that if they’re using AI, they’ll need a secondary, security-minded bot to ensure that chat bots and generative AI solutions don’t say or do anything they shouldn’t. For example, some schools are leveraging AI security functions to monitor their chat bots and limit what students can ask. Essentially, you want to protect your chat bot, and your users, from using AI for the wrong purposes. This also includes applying guardrails directly to AI solutions to ensure nothing leaks out and nothing nefarious creeps in.

How are enterprises using AI?

In the mid-tier world of AI, we’ve seen (and helped) many enterprise-level organizations create customized solutions, including:

• Custom chat bots that place and track orders, provide responses to basic questions, handle appointment booking and more
• AI-powered inspection solutions that review footage from body cams to catch anything the human inspector may have missed
• Drones that take video surveillance and feed the footage into AI to catch anomalies

Medical field

During the COVID-19 pandemic, AI played a huge role in developing the vaccines and the speed at which we were able to receive them, helping to identify viral genomes with the best viability to be effective.

Other healthcare facilities are using chatbots for symptom analyses. In fact, chip manufacturers have libraries of all known and identifiable cancers and are using AI with radiology images to quickly assess. While licensed and trained doctors still review before giving official diagnoses, AI expedites the process.

Retail and warehouse logistics

Life is starting to look a lot like the picture of the future that shows like The Jetsons painted for us. We’re using AI to build robotics for warehouses, people. Humans are finally getting the help we need to stop abusing our bodies with heavy lifting, as robots take on tasks like loading, scanning, product picking, packing and shipping.

Automotive

For those with big budgets and high-end AI solutions, AI can build virtual cities as a training facility for self-driving vehicles. As autonomous cars flood the streets in some major city hubs, AI helps with city mapping and planning to anticipate every possible scenario. The future of travel looks like a big, bright open canvas for us to paint as we go.

We’re just at the beginning of understanding what’s possible with AI, and there’s so much more to come. If you or your customers are looking to add AI to your workflows, Ingram Micro can certainly help you map out what that looks like—whether you’re looking for entry level, mid-tier or even high-end solutions. If you can dream it, we can help you build it through AI.

How can you effectively sell something if you’re not using it, too?

Maybe it’s just me, but I think customers know the difference between a sales pitch and a genuine success story. And I’m willing to bet that those testimonies hold a heavier weight than a sales pitch.

So, if you want to really jump into the generative AI (GenAI) space, then I double dog dare you to implement it in your house first.

I’m sure your next question is, “How can GenAI really benefit my business as an MSP?” And don’t worry—we’ve got you covered. Here are just a few of the ways you can see impactful changes in your MSP business model by implementing GenAI:

1. Acceleration of timelines. Did you know that GenAI lets MSPs build 24/7 natural-language front doors for support roles? Your team, or even your customers, can ask questions in plain English and get accurate answers sourced from your and your customers’ own documentation. “How do I reset my SSO?” “Why can’t I connect to VPN?” Asked and answered in minutes. This creates a faster response rate, fewer low-value tickets and even allows your humans to focus on higher-impact work.
2. Instant upgrade for ticket quality and triage. Instead of cryptic, one-line tickets, GenAI can guide your customers to describe their issues better, auto-tag them and summarize logs or leverage screenshots. It will also group related incidents and propose priorities on the backend on your behalf. This enables your customers to feel heard. Tickets will land in the right queue the first time.
3. Smarter security conversations, not alerts. We’re all bogged down with alerts and notifications, often with little understanding of what’s actually happening or how we can handle it. GenAI gives you the ability to leverage a nice little piece of tech heaven to summarize those security incidents, explain impact in business terms and draft recommended actions—without having to do a bunch of back and forth. You won’t receive as many panicked emails, reports will be easier to digest, and the next steps for your customers will be clearer.
4. Current knowledge, not outdated. Would it be fair to say that every MSP struggles with stale documentation? We hear that complaint a lot. Well, GenAI can continuously index tickets, change logs and run books, and turn them into searchable, conversational knowledge. Then, it will find new patterns and propose document updates as they emerge. Your customers will get an up-to-date experience, not “haven’t been updated in three years” how-tos.
5. Personalized self-service, not generic portals. You know what your customers are really tired of? Seeing the same old portal that doesn’t even say “Hi” to them. It feels so impersonal. There’s nothing that says, “I know your business, and I know your employees by name.” GenAI allows you to offer context-aware experiences. Answers that respect the user’s role, device and policies. Step-by-step, tailored instructions. Embedded actions of frequently accessed functions like “open a change,” “request access,” and “start a reset.” No more mazes that are confusing to navigate.
6. Better reviews, better roadmaps. You’re already doing quarterly business reviews and strategy sessions, but are you relying too heavily on raw data and not telling a visionary story? Sure, data is great and we love the numbers. But the numbers only tell part of what’s happening. GenAI can help you summarize tickets, incidents and changes—by theme. It can help you highlight trends in adoption, risk or satisfaction. It will even draft simple narratives and visuals for your C-team (and your customers’). This shifts the energy of these meetings from “Ugh, not another one of these” to “Oh, wow, this is really working and now we know where to go from here.”
7. New managed services, not just project work. You want ongoing services that customers can clearly understand and buy, not just a quick project. GenAI offers:

• Managed AI knowledge search and retrieval-augmented generation (RAG) over internal content.
• Managed GenAI security posture, including policies, guardrails and monitoring.
• Managed “AI ops co-pilot” for infrastructure and cloud.

The biggest flex? GenAI shifts the relationship between MSP and customer from “IT folks helping non-IT folks” to “the team that helps safely put AI to work in day to day operations.” You want to be your customers’ team, not their IT folks. And we want to be part of your team, too.

Our in-house team of AI experts are here to guide you through all things AI so you can be the AI experts to your customers. Ingram Micro’s Technology Lead, Global AI Program, John McNelly, is confident that we can help all MSPs, no matter which verticals their customers are in, succeed with a successful GenAI model.

“Ingram Micro addresses such a broad spectrum of AI maturity throughout our partner relationships and their customers that this framework is foundational to helping MSPs develop their own customer-facing strategies,” he says.

GenAI is for everyone—including MSPs. Let’s get you confident to be the safe AI experts for your customers.

Not every IT asset transition can happen from a warehouse. Whether you're decommissioning a data center, refreshing thousands of employee devices or consolidating office locations, some projects require experienced technicians onsite to protect security, maintain compliance and keep operations moving.

Ingram Micro's Onsite ITAD Services bring certified professionals directly to your facilities, providing secure, audit-ready support for every stage of your IT asset transition.

Enterprise expertise delivered onsite.

Large-scale IT projects often involve more than simply removing equipment. They require careful planning, documented chain of custody and experienced project teams that can execute consistently across one location—or hundreds.

Ingram Micro provides onsite support for:

• Data center decommissioning and equipment removal
• Device refresh and deployment programs
• Workplace relocations, consolidations and office closures
• Secure onsite data sanitization and physical destruction
• Infrastructure removal and logistics coordination

Reduce risk while accelerating projects.

From initial site surveys through final asset disposition, Ingram Micro helps organizations maintain visibility and control throughout every phase of an onsite engagement. Certified technicians perform NIST SP 800-88-compliant data sanitization, hard drive shredding, asset auditing and chain-of-custody documentation to help meet security and compliance requirements while reducing operational burden on internal teams.

Supported by secure certified facilities, global logistics capabilities and experienced project managers, Ingram Micro delivers consistent execution for multi-site initiatives ranging from technology refreshes to complete data center transitions.

Learn more about our Onsite ITAD Services.

View the Onsite ITAD Services guide to learn how Ingram Micro helps organizations accelerate onsite IT projects while maintaining security, compliance and operational efficiency throughout the IT asset lifecycle.

When organizations think about IT asset management, the focus is often on deployment at the beginning of the lifecycle or secure disposition at the end. But what happens in between can have just as much impact on operational efficiency, inventory costs and employee productivity.

A well-managed warehouse and fulfillment strategy gives organizations the visibility and control needed to keep technology moving where—and when—it's needed. Instead of storing equipment across multiple offices or relying on manual inventory tracking, enterprises can centralize assets, improve utilization and streamline deployments from a secure, scalable environment.

More than secure storage.

Ingram Micro's Warehouse & Order Fulfillment Services are designed to support every stage of the IT asset lifecycle. From receiving and storing equipment to inventory management, order fulfillment and deployment support, organizations gain a single partner to help manage technology assets efficiently across multiple locations.

Key capabilities include:

• Secure storage for new and existing IT assets
• Serialized inventory tracking and reporting
• On-demand pick, pack and ship services
• Multi-site distribution and employee device fulfillment
• Asset staging and deployment support
• Inventory visibility and lifecycle status management

Built for today's distributed enterprise.

Whether you're preparing for a large technology rollout, supporting remote employees, maintaining spare inventory or coordinating device refreshes, centralized warehousing can reduce operational complexity while improving responsiveness. Secure inventory management helps ensure assets remain protected, organized and ready for deployment whenever they're needed.

These services also integrate seamlessly with Ingram Micro's broader IT lifecycle offerings, including depot repair, remote asset recovery, redeployment and IT asset disposition (ITAD), giving organizations a single, trusted partner from procurement through retirement.

Contact us to learn more.

Download the Warehouse & Order Fulfillment Services sell sheet to explore how Ingram Micro helps organizations improve inventory visibility, simplify asset distribution and maintain greater control throughout the entire IT asset lifecycle.

Key playbook strategy: unified lifecycle services

In the channel, the real win doesn’t happen at the purchasing stage. It happens after the chaos of deployment schedules, tech stack puzzles, migrations that make your eye twitch and everyone’s desire for everything to ‘just work.’

Complexity isn’t creeping in, it’s kicking down the door. Whether you’re supporting 100 employees or 50,000, keeping IT projects aligned, secure, scalable and on schedule is a full-contact sport.

This is why more teams are leaning toward consolidating their lifecycle services with a single, end-to-end provider.

You could assemble your own team roster of niche players, or work with one powerhouse team that already knows the drill.

Research says the powerhouse team is the smarter choice.

Today’s buyers switch across 10 different channels during their journey, which translates to 10 different touchpoints for your experience to reach the goal. When you can clearly see the goal, but it requires 10 different plays to get you there, it slows the journey, to say the least. But when services and strategies align to one powerful team that’s obsessed with customers, you retain more customers and, as a result, your revenue grows. The smoother the experience, the stronger your customer retention.

Why full stack services matter

When you deliver everything from pre-sales design to deployment to IT asset management (ITAM) under one umbrella, you’re not just selling a device—you’re making your customers’ lives significantly easier. Running marketing, sales, delivery and customer success from one playbook creates a unified experience long after your kickoff call.

Bridging those gaps has a financial benefit, too. McKinsey found that top-tier IT organizations drive up to 35% more revenue growth and 10% higher margins, thanks to smarter productivity and better execution.

In other words, clean deliveries = more trust = more business.

Over 70% of enterprises are investing in modern service capabilities that are designed to reduce fragmentation, and increase enterprise-wide efficiency with the goal of improving engagement and reducing multiple handoffs.

Leaders are seeing the value of connected capabilities—when lifecycle services play together on the same team, support becomes proactive instead of reactive. Data flows cleanly through it’s process and, best of all, customers get a consistent experience that encourages them to cheer for the same, unified team.

If you are a company that wants to scale, retain customers and give them a great outcome, not to mention create a big fan base of customer loyalty, unified lifecycle services are becoming the standard.

Learn how your business can team up with Ingram Micro.

For the last several decades, speed has been a key factor in business savviness. Moving fast while remaining nimble sounds like startup territory and if you’re a larger organization, may sound as impossible as keeping a city bus above 50 MPH. But this is not the classic action movie “Speed” and, (very) unfortunately, Keanu Reeves isn’t coming to save the day.

But cloud migration is.

“The cloud provides a foundation for adopting cutting-edge technologies like generative AI and advanced analytics, offering scalability and infrastructure to support them without the need for massive capital investment,” said Rafael Marangoni, executive director of Global Cloud Services at Ingram Micro.

Cloud migration offers a wealth of benefits for businesses large and small, like scaling operations, reducing costs and enhancing collaboration. Here’s how it can give you that extra competitive edge—sans fast-moving vehicles.

Makes your business more scalable and flexible

Traditional on-location infrastructure requires companies to predict their future needs for resources and hardware years in advance, which leads to costly and inflexible investments. Cloud services, on the other hand, allow companies to scale up or down according to demand—you only pay for the resources you use. This flexibility is especially beneficial for small and midsize businesses operating with limited resources that still need to be agile to stay competitive.

Helps your pocketbook

Marangoni says by moving to the cloud, businesses can eliminate the need for costly upfront investments in hardware and other ongoing maintenance expenses, like power consumption and real estate. Instead, companies can shift to a pay-as-you-go model, which helps improve cash flow and reduces total cost of ownership. As an added bonus, cloud providers invest heavily in security, redundancy and infrastructure, offering your business access to advanced technologies at a fraction of the cost.

Enhances collaboration

Employees can access work from any location, which is crucial for today’s remote and hybrid workforce. Cloud-based tools like Slack, Microsoft Teams and Google Workspace make communication and project management seamless, while the ability to store data in multiple regions minimizes latency and optimizes performance for global teams.

“Cloud has unlimited bandwidth—there’s not one collaboration platform that is not a SaaS platform right now,” said Marangoni. “It doesn’t make sense for companies to use something outside the cloud—it enables collaboration.”

Builds with tomorrow in mind

We can’t get enough of that word “future-proofing,” and as technology advances, safeguarding your business and making it easier to address what’s next has never been more imperative. Technologies like AI, IoT and big data analytics require large amounts of processing power and storage, and the cloud offers the necessary scalability for this purpose, according to Marangoni.

Keeps your TCO in check

One of the biggest advantages of cloud migration is the potential to lower total cost of ownership (TCO). Instead of making large, upfront capital investments in servers and data center infrastructure—which can quickly become obsolete—companies shift to a subscription-based or pay-as-you-go model for computing resources. This means you only pay for what you actually use. By eliminating the cost of physical hardware, dedicated maintenance staff, and ongoing real estate and energy expenses, organizations can reallocate those resources elsewhere—like new product development or marketing. Plus, cloud providers continually invest in state-of-the-art technology (such as security enhancements, compliance updates and hardware upgrades), so you benefit from cutting-edge capabilities without bearing the full replacement cost.

“Lowering total cost of ownership is a game changer,” notes Marangoni. “It frees businesses from expensive hardware refresh cycles and unpredictable maintenance costs, all while ensuring your systems remain modern and secure.”

Get a return on your investment

Cloud migration’s return on investment (ROI) can help reduce capital expenditures on hardware and software and help you move to an operation expenditure model that aligns more closely with cash flow. Accessing the cloud also helps create new revenue stream opportunities.

“Cloud migration supports ROI by enabling faster time to market, reducing project timelines and offering businesses the opportunity to leverage advanced technologies at a fraction of the cost of maintaining them in house,” said Marangoni.

With cloud-based tools, improved collaboration also helps boost productivity, which can ultimately drive innovation, as well.

Shifting to the cloud is more than a speedy boon sans Hollywood dramatics—it’s a strategic move that allows businesses to operate more efficiently, reduce costs and enhance collaboration while staying ahead of technology’s winding roads. We’ll help you keep your foot on the accelerator and safely navigate those curves.

Choosing a cloud provider is a long-term strategic decision. Before you commit, ask these 3 essential questions about vendor lock-in, hidden costs, and tool integration to protect your business future.

Start by understanding the risk of vendor lock-in. Ask how easy it is to migrate data, what data egress fees look like, and whether portability is realistically achievable. Next, uncover hidden cloud costs that often hide behind “free” services, including API calls, microservice charges, and operational fees that inflate total cost of ownership. Finally, evaluate how well the cloud platform supports third-party tool integration, ensuring your team can continue using preferred open-source, security, and monitoring solutions.

Regardless of which provider you are evaluating as a potential partner, asking these three questions will help you build flexible, future-proof cloud environments that support innovation.

Want to meet customers where they are without overthinking it? It’s easier than it sounds. Pay attention to their signals, keep things simple, and guide them step by step. Dham Pathervellai, Chief Technology Officer at Ingram Micro, shares the five ways to do this effectively and how Xvantage can help.

What does it take to lead a tech-driven company without losing the human touch? Joanna Muzzatti, CEO of Commerx, has the answer: start with “We Care.” In this episode of B2B Tech Talk, she shares with host Tiffani Bova how this philosophy guides every decision, from empowering employees to delivering client solutions that genuinely make a difference.

Muzzatti also reveals how Commerx embraces AI not as a replacement for people, but as a partner that frees teams to focus on creativity, empathy, and relationship-building. She explores how organizations can navigate rapid technological change responsibly, stay authentic to their values, and turn innovation into meaningful growth for employees and clients alike.

Check out more conversations with people who love tech and subscribe to stay tuned in: https://usa.ingrammicro.com/cep/app/cms/en-us/general/b2b-tech-talk-podcast

Data disruptions are no longer rare events. Hardware failures, ransomware, and unexpected outages can interrupt operations at any time. The difference between a temporary setback and a major business disruption often comes down to preparation.

A strong data recovery strategy helps organizations maintain continuity when systems fail or data becomes unavailable. One widely recommended approach is the 3-2-1 backup rule, which ensures multiple copies of data are stored across different media with at least one copy offsite. This layered approach protects businesses against both technical failures and security threats.

Organizations should also define clear recovery time objectives (RTOs) to determine how quickly systems must be restored to avoid operational or financial impact. Finally, routine recovery testing ensures that backup systems and recovery processes work as expected when they are needed most.

By implementing these practices, businesses can move from reactive crisis management to a more resilient and controlled recovery process.