Discussion centered on the evolving role of Artificial Intelligence (AI) in the MSP technology stack, emphasizing the necessity for MSPs to deploy tools that can comprehensively manage AI, particularly concerning security and shadow IT. Multiple participants highlighted the lack of current solutions that aggregate and control AI activity via a single interface, with an explicit focus on the requirement to educate clients about AI privacy, security, and usage costs. The practical challenge of MSPs asserting thought leadership in AI was underscored, as was the complication of usage-based AI billing models leading to unexpected customer expenses.

Supporting details were drawn from the recently released Kaseya State of the MSP report, which showed that customer acquisition remains the sector’s main challenge, with 71% of surveyed MSPs identifying it as their top concern. The report further found that only a minority of MSPs are executing effective sales and marketing strategies to educate clients. Additionally, 48% of respondents reported AI and automation as top client needs, yet a significant drop was observed in customers spending more than $25,000 a year with MSPs, falling from 75% to 41%. This reduction is attributed to clients undertaking technology initiatives independently, diminishing the perceived value of MSP services.

Adjacent discussions addressed common issues around automation and AI adoption. Several practitioners noted a prevailing trend of automating legacy processes rather than leveraging AI for forward-looking transformation. It was emphasized that most AI implementations among peer groups are focused on operational efficiencies for past tasks, such as help desk and marketing automation, with few examples of innovative new service offerings. The dialogue also covered practical, risk-related aspects of managing client relationships, particularly when enforcing security measures such as multi-factor authentication in the face of client resistance.

Implications for MSPs and IT leaders include the need to strengthen governance around AI adoption and service stack adjustments, actively communicate the value of AI security and management services, and anticipate client concerns about cost control and privacy. The observed decrease in customer spending points to operational and strategic risks around client engagement and service value. MSPs are advised to ensure that automation efforts align with future requirements, not just past service models, and to enhance accountability in both vendor and client-facing operations.

Title:    Should I Adjust My Stack for AI? 

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