AI Monetization Remains Out of Reach for Most MSPs, Say GTIA’s Carolyn April and CompTIA’s Seth Robinson

The central structural shift examined is the widening disconnect between the vendor-driven narrative of rapid AI monetization and the operational reality faced by MSPs, as exposed by recent research from GTIA and CompTIA. Despite pervasive messaging from technology vendors that AI features are ready for seamless integration and immediate profitability, survey data indicates that most MSPs remain in early adoption stages, lack tangible processes to operationalize AI, and are stymied by workforce and workflow constraints. Supporting evidence is drawn from CompTIA’s data showing that 70% of businesses are still in early AI adoption stages, and only 55% of MSPs expect to turn a profit on AI initiatives in the near term—up from 34%, but well below vendor promises. The majority of current AI activity remains at the individual user level rather than embedded in business-wide workflows, restricting quantifiable ROI and limiting the visibility of productivity gains. Both Speaker B and Speaker C emphasized that most MSPs do not yet have the organizational capability or maturity to move beyond experimentation to operational deployment and monetization. Related developments further illustrate this operational gap. Research cited by Speaker B highlights that only a subset of larger MSPs with more resources have been able to achieve early success with AI, while most are still grappling with process integration, pricing strategies, and talent acquisition. Both GTIA and CompTIA reports suggest that optimism among firms about AI’s potential is running ahead of genuine structural change, with workforce shortages, undefined internal governance, and difficulties in business model adaptation acting as durable barriers. Market sentiment remains positive, but actual organizational transition lags significantly, especially among smaller MSPs. Operationally, this environment introduces heightened risk for MSPs who overcommit on vendor promises without aligning internal processes, workforce strategy, and governance. Dependencies on vendor-supplied AI tools expose firms to pricing uncertainty and potential margin compression, especially as clients begin questioning the value proposition when human roles are replaced by automation. Without formalized internal AI governance and skill development, most MSPs face mounting challenges in demonstrating measurable ROI, adapting delivery models, and sustaining service margins. The implication for decision-makers is the need for prudent, phased adoption—prioritizing internal process maturity and realistic expectations over rapid adoption in response to vendor pressure. Supported by: CometBackUpTimeZest 💼 All Our SponsorsMSP Radio is supported by our partners: ABC Solutions · CometBackup · Guardz · HaloPSA · LogMeIn · Mailprotector · OpenText · Pax8 · Proofpoint · Rythmz · ScalePad · TimeZest · Transit AI · USecureSupporting the IT services community through insights, analysis, and transparency. 🚀 Join Business of Tech PlusGet exclusive access to investigative reports, vendor analysis, leadership briefings, and more.👉 https://businessof.tech/plus 🎧 Subscribe to the Business of TechWant the show on your favorite podcast app or prefer the written versions of each story?📲 https://www.businessof.tech/subscribe 📰 Story Links & SourcesLooking for the links from today’s stories?Every episode script — with full source links — is posted at:🌐 https://www.businessof.tech 🎙 Want to Be a Guest?Pitch your story or appear on Business of Tech: Daily 10-Minute IT Services Insights:💬 https://www.podmatch.com/hostdetailpreview/businessoftech 🔗 Follow Business of Tech LinkedIn: https://www.linkedin.com/company/28908079YouTube: https://youtube.com/mspradioBluesky: https://bsky.app/profile/businessof.techInstagram: https://www.instagram.com/mspradioTikTok: https://www.tiktok.com/@businessoftechFacebook: https://www.facebook.com/mspradionews Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.