In 2025, approximately 88% of businesses reported the regular use of AI in at least one business function. Artificial intelligence is no longer part of future innovation, particularly in the IT sector. It’s now shaping how IT environments operate, how cyber threats evolve, and how organizations make business decisions. While leaders recognize AI is transforming how businesses operate, the real challenge is determining which technologies are most important, how to effectively implement them and how to keep systems secure and scalable.
The shift happening now is bigger than simply adopting new AI tools. Now organizations are moving toward AI-driven systems and integrating AI into solutions that affect everything from cybersecurity and networking infrastructures to compliance and customer experience. This is where managed IT service providers (MSPs) play a crucial role in helping organizations better adopt AI technology well.
AI is transforming cybersecurity
AI-Powered Monitoring and Automated Response
AI-powered monitoring and automated responses in cybersecurity involves machine learning to provide real-time anomaly detection, spotting unusual behaviors that traditional tools could easily miss. These systems can trigger immediate responses and actions to isolate compromised devices, shut down suspicious activity or initiate containment workflows within seconds.
Zero Trust is Now Mandatory
Zero Trust frameworks assume no user, device or application should be trusted without verification, every time. With AI-driven attacks becoming more unpredictable, Zero Trust should no longer be optional. It is foundational to preventing unauthorized access and lateral movement inside a network.
How MSPs strengthen AI-driven cybersecurity
Cybersecurity cannot be reactive and instead needs to be embedded into all aspects of a business’s organization and IT infrastructure, continuously maintained and aligned to compliance requirements. An MSP helps by:
- Delivering 24/7 managed detection and response
- Integrating AI-enabled tools for real-time threat visibility
- Creating and maintaining incident response plans
- Supporting regulatory and industry-specific compliance
- Ensuring cybersecurity scales
Smart sensing networks & predictive analytics are reshaping IT
Applied to network infrastructures, AI machine-based systems learn from data, identify patterns and make decisions with less human intervention, allow day-to-day operations to be more productive. These predictive analytics is an essential element of modern technology strategy. By collecting and interpreting data from across network infrastructures, AI systems forecast outcomes and better guide decision making from endpoints to applications and workloads.
Smarter decision-making through predictive analytics
These systems allow businesses to:
- Predict equipment failures before they happen
- Optimize performance and resource usage
- Identify patterns in user behavior
- Improve forecasting and capacity planning
- Enable proactive maintenance instead of reactive fixes
How MSPs support AI integration and infrastructure
To ensure AI works well within an IT infrastructure, it requires the right foundation. Organizations can often underestimate the infrastructure demands needed to support AI workloads whether it’s more bandwidth, the right hardware that can handle AI, high-performance GPUs and data processors that can scale and ensure connectivity.
MSPs help ensure AI implementations are not just functional, but sustainable and aligned with business objectives. This includes:
- Conducting AI readiness assessments
- Designing and deploying the required infrastructure
- Integrating AI tools with existing systems
- Providing ongoing monitoring, optimization, and technical support
- Ensuring scalability and cost-efficiency as AI usage grows
As a managed IT service and solutions provider, Computer Solutions is partnered with a variety of technology partners to support a wide range of Texas businesses and organizations. A strong MSP brings a variety of technology partners to support a wide range of use cases, including the following:
1. Cisco
Cisco’s portfolio offers a strong foundation for organizations looking to integrate AI across their IT environments. Use cases include:
- AI-optimized networking that prioritizes performance, low latency and traffic visibility which is essential for ML workloads and smart sensing networks.
- Secure access and segmentation using AI-enhanced visibility to detect anomalies in network traffic.
- Predictive network analytics that forecast system bottlenecks or outages before they impact operations.
- Scalable hybrid infrastructure designed to support cloud, on-premises and edge-based AI deployments.
- AI-driven SD-WAN for intelligent routing and application performance monitoring across locations.
2. Arctic Wolf
Arctic Wolf brings AI to the center of cybersecurity operations. Relevant use cases include:
- AI-driven threat hunting that correlates millions of events to present suspicious activity faster than other traditional tools.
- 24/7 managed detection and response (MDR) powered by machine learning behavior models.
- Accelerated incident investigation supported by AI-enriched threat intelligence.
- Automated security workflows that reduce time-to-containment during attacks.
- Security posture management that uses AI to flag vulnerabilities, misconfigurations and compliance gaps across the environment.
3. HPE
HPE provides the compute power and architecture needed to support AI training, inference and analytics at scale.
- High-performance computing (HPC) platforms designed for ML model training and large-scale data processing.
- Hybrid cloud solutions that allow AI workloads to run seamlessly across on-prem and cloud environments.
- Edge-to-cloud architectures enabling real-time insights from sensors, devices, and distributed locations.
- AI-optimized storage capable of handling high throughput and rapid data ingestion.
- Infrastructure automation to simplify deployment and scaling of AI systems.
3. Rubrik
Rubrik provides a modern, AI-driven data security, recovery and resilience. Use cases include:
- Zero Trust Data Security ensures backup data cannot be deleted or tampered with, protecting against ransomware and insider threats.
- AI-powered threat detection and anomaly analysis identify unusual activity in backup data, alerting teams to potential cyberattacks before they escalate.
- Secure cloud archiving provides encrypted storage, automated lifecycle management and cloud-native protection for hybrid and SaaS environments.
- Sensitive data discovery and compliance automation classify sensitive data, simplify compliance and provide visibility into where critical information resides.
Have questions about these vendors or any of our IT solutions and services and how they relate to AI? Our team can help. At Computer Solutions, we can help you adopt AI into your organization with a clear strategy, expert deployment and integration, continuous optimization and monitoring and more. As your managed IT services provider, we can ensure your organization remains secure, scalable so that AI is just a tool but a strategy that drive long-term growth for your business.
