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My Daily Podcast, The Business of Tech. 5 minutes of news and comments, asking “Why Do We Care?” for IT services companies

In 10 minutes daily, The Business of Tech delivers the latest IT services and MSP-focused news and commentary. Curated to stories that matter with commentary answering ‘Why Do We Care?’, channel veteran Dave Sobel brings you up to speed and provides resources to go deeper. With insights and analysis, this focused podcast focuses on the knowledge you need to be effective, profitable, and relevant.
The episode highlights a structural gap between projected AI-driven revenue in the channel and the concrete operational changes needed to capture measurable ROI. Industry surveys from Informa MSP 501, McKinsey, and PwC consistently show that while AI adoption rates among managed service providers (MSPs) are high, few organizations have restructured workflows or business models around AI. The focus remains on superficial activity tracking rather than genuine business transformation.
The MSP 501 survey found 57% of providers expect significant AI revenue growth, with 91% reporting some level of adoption. However, McKinsey’s analysis, as presented by IHL Group, shows only 11% of companies have comprehensively rebuilt processes around AI, with a minority of those realizing clear benefits. PwC’s CEO survey aligns, with over half of respondents seeing no substantive financial returns from AI unless it is extensively integrated beyond the user level.
Products like Insightful workforce analytics are now entering MSP portfolios, offering discounted access to AI usage tracking tools. Yet data from Visier and the OECD warn that monitoring software can promote superficial compliance—about half of workers admit to overstating AI usage, and most lack control over the data collected. The OECD also finds that this monitoring is often embedded in standard business software rather than dedicated AI platforms.
For MSPs, the risk is prioritizing activity measurement over outcome-based change. Vendors promote usage reports, but these often reward appearances rather than operational improvement. Meaningful results depend on redesigning workflows and measuring actual process improvements—not merely collecting tool usage statistics. Before offering AI usage metrics to clients, MSPs should validate the effectiveness of workflow changes internally to avoid incentivizing unproductive patterns.
00:00 Forecasting AI, Skipping The Redesign
04:06 When Usage Stands In For Results
06:56 The Usage Meter Hits Your Catalog
10:46 Why Do We Care?
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