Opinion
The success of enterprise AI transformation depends not only on technology but also on the AI literacy of the workforce. A World Economic Forum report shows that by 2030, 39% of core skills will change, and nearly 60% of the global workforce will need retraining. However, current AI education models face issues such as a gap between theory and practice and a lack of personalization. This article proposes an immersive, hands-on learning framework, emphasizing changes in work methods as the measure of success, to help enterprises build an adaptive workforce.
Despite the industry's push toward AI, MSPs that thrive are those that ensure every customer has a named person accountable for their experience. This piece explores why personal accountability is the new competitive edge, how to implement it, and where AI fits without replacing the human touch.
MSPs serving small and medium-sized businesses are facing severe challenges from the recurring exposure of vulnerabilities in SSL VPN devices. Products from Fortinet, SonicWall, and others have continuously seen high-risk CVEs, making unpatched devices the primary initial access vector for ransomware. This article analyzes the structural risks, proposes a phased migration strategy toward cloud-native VPN and ZTNA, and emphasizes the window of opportunity for MSPs to proactively guide customer transformation.
The AI market is still dominated by infrastructure investment, but the real value for channel partners lies in helping enterprises convert computing power investments into measurable business outcomes. This article explores how channel partners can become key enablers of enterprise AI adoption through process insights, outcome-oriented services, and governance capabilities.
Early AI pilots are exciting, but transforming experiments into production environments that generate returns on investment is difficult for infrastructure and technology leaders. This article points out that enterprises need to focus on production readiness and truly scale AI applications by restructuring operational models, strengthening governance, and driving organizational change.
Omdia's latest research shows that 49% of managed service providers (MSPs) want a fully integrated software and service delivery platform, and 91% need integrated backup and recovery capabilities, marking a continued shift from point solutions to platform-based approaches in critical data protection and AI governance. The advancement of AI adoption and agentic AI is accelerating this trend, with governance and compliance challenges being the biggest obstacles.
By 2026, AI regulation has moved from principle-based discussions to enforceable timelines, state-level laws, and contractual requirements. The EU AI Act is taking effect in phases, while US states and industry regulators are issuing specific rules. CIOs need to treat compliance as a design constraint and establish unified enterprise AI control systems to address lifecycle management challenges in a multi-regulatory environment.
Enterprise AI adoption is accelerating, and risks are rising accordingly. Gartner data shows that generative AI spending will increase by nearly 40% this year. Traditional governance models struggle to cope with non-deterministic AI architectures. CIOs need to adopt an architecture-first strategy, treating governance as a foundational technical requirement, and integrate six types of technical controls including guardrails, observability, traceability, centralized gateways, AI catalogs, and wrappers, while combining frameworks such as the NIST AI RMF, EU AI Act, and ISO/IEC 42001 to achieve responsible AI.
As enterprise agentic AI reaches a tipping point, more than half of technology leaders expect to remove humans from decision loops within a year. However, ungoverned AI can lead to issues such as hallucinations and inappropriate outputs. Anisha Vaswani, Chief Information and Customer Officer at Extreme Networks, writes that CIOs need to place AI guardrails on par with the technology itself, using strategies such as observability, security governance, and human-in-the-loop to ensure system safety while pursuing rapid ROI. The article emphasizes that cross-departmental collaboration and employee AI literacy are two pillars for the effective implementation of guardrails.
AI agents are becoming a disruptive force in IT operations for the digital workplace. Gartner predicts that by 2030, nearly one-third of enterprises will achieve autonomous operation of 80% of digital workplace services, a figure that stands at 0% in 2025. This article explores the application scenarios, governance frameworks, and skill reshaping requirements of AI agents, providing strategic reference for CIOs.