AI is already part of everyday business workflows, whether organizations have a formal strategy for it or not. As employees adopt these tools, businesses need to understand where AI adds value, what their technology can support, and how to manage potential risks.
Effective AI management goes beyond choosing the right tools. It requires clear usage guidelines, appropriate permissions, data protection, and ongoing oversight as technology and business needs evolve.
AI adoption also brings a need for clear ownership, with someone responsible for overseeing tools, managing risks, and ensuring they support business goals.
The experts at Varay Managed IT help businesses adopt and manage technology with security, productivity, and long-term IT needs in mind. Here’s what AI management involves and how to decide whether an internal AI manager or a managed IT service provider is the right fit for your business.
Why AI Has Become an IT Management Issue
AI tools are easy to access. Employees can create accounts, upload documents, and start using AI assistants within minutes. Managing how those tools are used across a business takes more planning, particularly when company data, security, and existing systems are involved.
Businesses need to account for several areas of AI management:
- Shadow AI: Identifying employees’ use of unapproved AI tools or personal accounts for company work.
- Data security: Protecting sensitive business, customer, and employee information from exposure.
- Permissions and access: Determining who can use specific tools and what information they can access.
- Microsoft Copilot administration: Configuring access, reviewing existing permissions, and helping employees use Copilot appropriately.
- Policies and training: Setting expectations for acceptable AI use and helping employees understand their responsibilities.
- Ongoing support: Troubleshooting issues, managing updates, evaluating new tools, and adjusting controls as technology evolves.
Although these responsibilities overlap with traditional IT management, AI adds another layer of complexity. New tools and features emerge regularly, making it difficult for businesses to maintain visibility and consistent oversight without a defined management approach.
Without that structure, organizations risk accumulating redundant tools, creating security gaps, and losing track of how company information is being used across AI platforms.
What Happens When Employees Use AI Without Oversight?
Consider a healthcare organization where employees use personal AI accounts to summarize patient information or draft internal documents.
Although these tools may save time, entering protected health information (PHI) into an unapproved service could expose sensitive data and create compliance risks.
Healthcare organizations must account for the Health Insurance Portability and Accountability Act (HIPAA), including applicable privacy, security, and vendor requirements. Businesses handling financial records, confidential client information, and other sensitive data face similar responsibilities.
Data handling also varies by AI provider. Some consumer services may use submitted information to improve their models, depending on their terms and settings. Business offerings may include stronger privacy protections and administrative controls, but these vary by product and configuration.
Before approving an AI tool for company use, businesses need to understand how it handles data and whether its protections meet their security and compliance requirements. IT teams can help evaluate those tools, configure appropriate controls, and establish clear guidelines for employees.
Should You Hire an AI Manager or Work With an MSP?
Once AI becomes part of daily operations, businesses need a clear plan for managing it. Some may benefit from hiring an internal AI manager, while others may find that working with a managed IT service provider is a better fit.
The right approach depends on the organization’s size, technical resources, and AI goals.
Option 1: Hire an Internal AI Manager
An internal AI manager focuses on integrating AI into business operations, identifying opportunities for automation, coordinating projects, and helping departments adopt new tools.
This role can be particularly valuable for larger organizations with extensive automation initiatives, complex AI projects, or a need for dedicated internal leadership.
The advantages:
- Dedicated AI strategy: Focused attention on AI adoption and its role in business growth.
- Internal collaboration: Direct communication with leadership and department heads.
- Business familiarity: A strong understanding of internal workflows, goals, and operational challenges.
- Cross-department coordination: Help aligning AI initiatives across teams.
Hiring internally also comes with ongoing costs, including salary, benefits, training, and professional development. The role may require a combination of business strategy and technical expertise, particularly when AI tools interact with sensitive information or existing company systems.
Assigning AI management to an existing employee can be another option, but adding these responsibilities without adjusting their workload or providing adequate training may leave important tasks unattended.
Option 2: Partner With a Managed IT Service Provider
A managed IT service provider (MSP) can help businesses implement, secure, and maintain AI tools within their existing technology environment.
Instead of building all the necessary technical expertise in-house, businesses can draw on an IT team experienced in areas such as cybersecurity, identity management, system configuration, and ongoing support.
The advantages:
- Broader technical expertise: Access to multiple skill sets without hiring a full-time specialist.
- Tool configuration: Assistance setting up business AI platforms and managing user permissions.
- Security guidance: Help evaluating approved tools, protecting company data, and implementing appropriate controls.
- Ongoing maintenance: Support with updates, troubleshooting, and changing technical requirements.
- System integration: Help connecting AI tools with existing platforms, including Microsoft 365, where appropriate.
AI management also involves technical details that can be easy to overlook. Configuring single sign-on, connecting tools to a company directory, reviewing access permissions, and managing integrations all require more than simply purchasing an AI subscription.
An MSP’s involvement, however, depends on the services included in its agreement. Business leaders still need to set priorities, establish employee expectations, and make decisions about how AI should support their organization. They should also confirm that their provider offers the specific AI administration and governance services they need.
Striking the Right Balance
For many small and mid-sized businesses, combining internal ownership with external technical support offers a practical approach. Internal leaders can guide business priorities and employee adoption, while an MSP helps manage the underlying technology and security.
This arrangement allows businesses to pursue AI opportunities without necessarily building an entire technical function in-house.
Ready to put a plan behind your AI adoption?
How Varay Can Help You Manage AI More Effectively
AI adoption involves more than choosing a tool and giving employees access. Businesses need to consider security, permissions, employee training, and ongoing management from the beginning.
Varay’s AI and automation services can help businesses evaluate opportunities to use AI and determine what support may be needed to implement it responsibly.
Why Business AI Accounts and Permissions Matter
Establishing which AI tools employees can use for company work is an important first step in managing AI.
Organizations using Microsoft 365, for example, may evaluate Microsoft Copilot or other business AI offerings. Depending on the product and licensing arrangement, these tools may offer centralized administration, organizational account management, and additional data protection features.
Connecting AI access to existing identity management systems, including single sign-on where supported, can help administrators control who uses each service and apply the appropriate security settings.
However, these controls are only part of the picture. Microsoft Copilot, for example, can surface information that a user already has permission to access. If company files have been shared too broadly, AI may make sensitive information easier to find. Reviewing file permissions and access controls is therefore an important part of preparing for AI adoption.
A managed IT provider can help assess these settings, configure available controls, and establish a consistent set of approved tools. Standardizing platforms also makes ongoing support easier by reducing the number of different systems IT teams need to maintain.
AI Policies and Employee Training Are Essential
Responsible AI management requires clear policies and employees who understand how to apply them. Policies should identify approved tools, define what information employees can share, and outline when additional authorization is needed.
Training should address situations employees encounter in their daily work, such as handling customer records, verifying AI-generated information, and knowing where to turn when a task raises concerns.
Businesses in regulated industries, including healthcare and financial services, must also evaluate AI practices against their applicable compliance requirements. Policies alone do not guarantee compliance, and using an approved tool does not remove the need for appropriate safeguards.
Putting these expectations into practice requires collaboration between IT, Human Resources, and leadership. HR can communicate employee responsibilities, IT can implement technical controls, and leadership can establish who approves new tools, reviews policies, and responds to incidents.
AI Management Requires Ongoing Attention
AI management requires ongoing attention as tools, business needs, and security risks change. Organizations need a process for reviewing configurations, updating employee access, resolving technical issues, and determining whether their existing tools remain appropriate.
These responsibilities can be shared among internal leadership, an existing IT team, and a managed service provider rather than assigned to a dedicated AI manager.
The priority is to establish clear accountability and ensure AI tools remain secure, supported, and aligned with business needs.
The Biggest Risk May Be Not Using AI at All
Avoiding AI altogether can mean missing opportunities to innovate, improve productivity, automate routine tasks, and free employees to focus on higher-value work.
Businesses can pursue these benefits without adopting every new tool or leaving employees to navigate AI on their own. A more effective approach starts with identifying useful applications, selecting appropriate solutions, and establishing the safeguards needed to support them.
That process includes reviewing current employee usage, evaluating security and access controls, setting clear policies, and assigning responsibility for ongoing management.
Let Varay Help You Manage AI With Confidence
From Microsoft Copilot to Shadow AI and automation, integrating AI into your business requires the right tools, technical foundation, and oversight.
Varay Managed IT helps small and mid-sized businesses evaluate technology, strengthen IT security, and manage the systems their teams rely on. Our team can help you establish a practical approach to AI that supports your business goals without losing sight of security or day-to-day operations.
Ready to put a plan behind your AI adoption?
