Sharon Florentine on Why Most SMBs Deploy AI Without Budgets or Governance

The episode highlights a pronounced governance gap in how small and mid-sized businesses (SMBs) are adopting artificial intelligence (AI) tools and services. New research from GTIA, discussed by Sharon Florentine, identifies that while AI use has become nearly universal among SMB end customers of IT service providers, most lack formal policies, leadership, and budgeting structure around their deployment of AI. This reflects a foundational misalignment between AI adoption rates and organizational preparedness.

According to the GTIA study, 97–98% of surveyed SMBs are already using AI to some extent, yet only 20–25% do so strategically. Strategic usage is defined by having AI under a leadership role, with established policies and procedures. In addition, only around one-quarter of respondents reported having a dedicated AI budget. This suggests that despite broad AI integration, most spending is ad hoc or drawn from unrelated IT priorities. The research surveyed 520 SMBs across 11 verticals, reinforcing the generalizability of the findings.

Supporting discussions emphasized that this misalignment is both an opportunity and a risk for MSPs and ITSPs. Unaddressed gaps in governance, budgeting, and cybersecurity may undermine value delivery and create liability issues. Practical challenges—such as unclear funding sources, lack of proactive customer engagement, and potential cybersecurity risks tied to unmanaged AI use—were described as persistent pain points. It was also noted that shifting to a proactive approach is essential for building trust and effective client partnerships.

For MSPs and IT leaders, the operational implications center on the need to address governance and budget planning for AI while maintaining a focus on established IT infrastructure. Relying solely on existing processes may introduce unmanaged risk, particularly as customers expand AI use without adequate oversight. Providers are advised to prepare by developing frameworks for AI budgeting, security controls, and policy development, rather than diverting focus from foundational IT services. Neglecting core infrastructure and data practices in pursuit of unstructured AI integration was identified as a critical operational miscalculation.

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