Navigating Invisible Work: AI, Automation, and the Challenge of Proving Value as an MSP
A significant risk area discussed is the challenge of “invisible work” in managed services due to increasing automation and the adoption of artificial intelligence (AI). Customers, according to participants, increasingly lack awareness of the work being performed on their behalf, which raises doubts about the value of services provided by MSPs. With prices for services escalating, clients are demanding higher-touch engagement and visibility into operations, creating a disconnect between automated backend activities and client expectations for tangible service.
Supporting this, hosts cited the difficulties in proving the value of proactive prevention, such as security incidents that did not occur, and noted that with further automation, particularly through AI, this challenge will intensify. Customers may question why they continue to pay elevated fees if tasks can be completed by AI or low-cost competitors, amplifying price pressure and the potential for misaligned perceptions of value. Examples included references to the current technology stack, where some tools cost more to integrate and operate—particularly with new AI workloads—than previous turnkey supplier models, often with increased operational complexity and support risks.
The episode addressed secondary risks stemming from overreliance on both small, unproven vendors and on large-scale automation. Hosts highlighted the volatility of new entrants in security and infrastructure, pointing out that many lack lifecycle support or robustness, making them unreliable partners for business-critical tasks. Recent events, such as the OpenAI boycott following its Department of Defense contract and operational disruptions at AI provider Claude, were used to illustrate instability among technology suppliers. The conversation also covered the risks of unchecked AI deployment, with examples from military and financial sectors where automation led to errors or was used to rationalize significant workforce reductions.
The practical implications for MSPs and IT service providers center on maintaining transparency with clients, reassessing vendor risk (particularly with AI and new software providers), and calibrating expectations for automation. The hosts recommended reinforcing client communication regarding the nature and value of services, conducting due diligence on technology partners, and aligning automation strategies with operational risk management frameworks. Emphasis was placed on the need for ongoing human oversight, especially where automated decisions could lead to adverse outcomes, and on approaching AI adoption as a phase for careful experimentation rather than wholesale business transformation.
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