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Business of Tech: Daily 10-Minute IT Services Insights: Daily Summaries Delivered
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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.
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- Today12 min
The Real AI Risk for MSPs: Who Verifies the Output When Clients Don’t Ask?
The core structural shift highlighted in this episode is the commoditization of AI model platforms and concurrent consolidation at the vendor and platform layer, forcing Managed Service Providers (MSPs) to move their value proposition above reselling models to orchestrating, governing, and verifying AI outputs. The discussion references the rising concentration and valuation of platforms such as NinjaOne—a founder-led, profitable RMM platform with a $12.3 billion valuation and 70% year-over-year growth—and Pax8 building business toolkits that draw more operational functions onto their rails. At the same time, major AI developers like OpenAI are entering the channel more directly by launching partner programs aimed at MSPs and consultants. The most consequential development is the confirmed shift from reselling AI models to managing their outputs and risks. Glean surveyed 6,000 digital workers and found that while AI delivers approximately 11 hours of weekly time savings, nearly 6.4 hours are reclaimed by “bot sitting”—the human intervention required to supply context, verify, and correct AI outputs. This hidden labor raises a risk scenario: two-thirds of workers admit to releasing unchecked AI outputs, and Ivanti found that only 42% of IT environments actually have a named owner for each AI agent, despite 85% claiming so—a 43-point gap in accountability. Asana and Deloitte further reinforce the issue, reporting frequent cost overruns and unmanaged autonomous AI deployments among enterprise and SMB environments. Supporting developments underscore this governance and accountability gap. TechCrunch cited that ChatGPT’s AI market share has dropped below 50% as the field becomes more interchangeable and less differentiated by underlying model. Vendors such as Anthropic and OpenAI, recognizing model commoditization, are seeking revenue through high-volume partner channels, blurring the lines between vendor and channel competitor. According to Asana, more than 80% of UK IT leaders encountered unplanned AI costs, and over half reported business harm from autonomous AI actions, shifting operational and liability risks squarely onto MSPs and IT service providers. Operationally, these trends compel MSPs to take explicit ownership of the orchestration and governance layer, rather than relying on tool reselling. The transcript advises mapping every AI-driven decision or output that reaches client endpoints and identifying who verifies these outputs before customer exposure. Failing to address these governance blanks does not avoid work but shifts it to unbilled, post-incident cleanup, often with financial, legal, or compliance consequences. Effective MSPs will need to price, document, and regularly review their verification, orchestration, and risk assumption, positioning these as standalone, billable services to manage risk and maintain margin as AI platforms commoditize and vendor dependencies rise. 00:00 Bigger Platforms, Unwatched AI 03:44 The Vendor Walks Into the Channel 05:56 Govern It or Absorb It 08:52 Why Do We Care? Supported by: ScalePad Sign up for the SMB Online Conference: www.smbonlineconference.com 💼 All Our SponsorsSupport the vendors who support the show:👉 https://businessof.tech/sponsors/ 🚀 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
- Yesterday11 min
Government AI Shutdown Exposes Hidden Vendor Dependencies for MSPs
A pronounced infrastructure dependence on third-party AI models has emerged across the MSP ecosystem, largely due to the rapid adoption and integration of AI-powered features within vendor products. This structural shift is increasingly opaque, as providers are sold features rather than transparent access to underlying models, leaving MSPs exposed to changes in technologies and policies enacted upstream by vendors or regulators. The episode highlights how this dependency extends to delivery teams and end clients, with operational continuity tightly linked to decisions and actions outside the MSP’s direct control. The most consequential development referenced is Anthropic’s release and rapid withdrawal of its Fable 5 AI model following a directive from the U.S. Commerce Department, which ordered a cutoff of model access to foreign nationals within 72 hours of public launch. According to published benchmarks, Fable 5 surpassed GPT 5.5 in performance, but the government-mandated suspension exposed how quickly model access can be rescinded. The policy move immediately impacted any MSP or client with offshore or nearshore staff relying on AI features invisibly powered by that model. Further supporting the central theme, companies such as PAX8, Enforcer, and CloudRadio are embedding AI capabilities into platforms used by MSPs to manage Microsoft 365 environments, automate ticketing, and support scalable client operations. In parallel, vendors like Proofpoint are integrating compliance solutions directly with AI model APIs, further entwining risk management tools with the same core AI infrastructures. A Netrio survey cited in the episode found that while 82% of mid-market IT leaders have AI in production, only 26% report organization-wide governance, highlighting an accountability and visibility gap. Operationally, MSPs face heightened contract and vendor risk. Most lack an accurate inventory of which AI models underpin their services and how rapidly these dependencies can be affected by regulatory directives or vendor shifts. The discussion underscores the need for explicit procurement protocols, delivery mapping, and outage runbooks that account for opaque model dependencies. As clients seek greater transparency and contractual assurances regarding model use and continuity, MSPs who anticipate and document these dependencies may be positioned to reduce exposure and establish clearer accountability. 00:00 Switched Off 03:19 Painted Over 05:20 Govern or Absorb 08:41 Why Do We Care? Supported by: Pax8 Sign up for the SMB Online Conference: www.smbonlineconference.com 💼 All Our SponsorsSupport the vendors who support the show:👉 https://businessof.tech/sponsors/ 🚀 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 Hoste
- 2 days ago33 min
Atera’s AI Shift: Gil Pekelman on Accountability and Risk in Autonomous IT for MSPs
The episode highlights a structural shift from automation that suggests actions to automation that executes actions autonomously, thereby transferring substantial operational risk and accountability to technology vendors and their AI-driven platforms. This transition is exemplified by Atera's deployment of their autonomous AI agent, Robin, which is positioned to handle a significant proportion of Tier 1 and complex Tier 2 IT tickets for managed service providers (MSPs). The company’s commercial strategy, including performance guarantees, signals an increased expectation that AI can assume core IT operational responsibilities that were traditionally reserved for human engineers. Atera has introduced a policy wherein Robin is guaranteed to autonomously close at least 50% of all Tier 1 and complex Tier 2 tickets within 90 days of onboarding, or fees are waived. According to Atera, this commitment is supported by a backend analysis of MSP tickets and live demonstrations using historical data. The company asserts that Robin’s mean time to repair is approximately 120 seconds, that onboarding is managed collaboratively, and that the rollout is more akin to hiring and training a human engineer than a standard software deployment. This approach is backed by patent filings and a business model integrating AI as the foundation rather than an add-on. The episode further examines the implications of mandatory AI bundling in Atera’s redefined RMM and PSA platform offering. The company has faced pushback from segments of the MSP community dissatisfied with bundled AI services and associated pricing changes, particularly from those wishing to maintain control over their technology stack. Atera responds by describing a re-conceptualization of their platform as inherently AI-driven, distinguishing between “platform AI” and the autonomous Robin agent, and clarifying that preexisting AI users would not incur additional costs. There is also discussion around the impact of automation on human roles and the need for new approaches to training and accountability, particularly for junior staff. For MSPs and IT service providers, these developments signal an increase in infrastructure dependency on vendor-managed AI agents, as well as new layers of contract risk linked to performance guarantees and platform integration. The operational reality described involves a significant reduction in required headcount, a shift in staff responsibilities from routine incident response to higher-order business and security tasks, and the necessity for designated internal management of AI tools. There remain unresolved concerns about skill degradation and the long-term risks of over-automation, including the narrower pathways through which junior personnel may acquire foundational experience. Sponsored by: ScalePad https://scalepad.com/dave/ Nerdio https://nerdio.co/MSP-Radio Sign up for the SMB Online Conference: www.smbonlineconference.com 💼 All Our SponsorsSupport the vendors who support the show:👉 https://businessof.tech/sponsors/ 🚀 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: <a href="https://ww
- 5 days ago12 min
New AI Governance Tools Are Table Stakes—Positioning, Not Stack, Drives MSP Growth
Vendors supplying AI-driven technologies are experiencing sustained margin pressure from high operational costs and underwhelming business-level returns, leading to the rapid creation of new product categories that are pushed into the MSP channel. Companies such as Atomic Work, Silverfort, and Guards are releasing governance tools for managing AI agents, while Connect Secure is offering patch management products targeted at MSPs. These launches are not indicators of competitive differentiation, but of structural cost challenges being passed from vendors to their partners. Business media reports and internal industry data reveal that while individual productivity from AI implementations increases—for example, by accelerating engineer output—the promised business-level gains in productivity, revenue, and profit have not materialized to the extent vendors projected. According to analysis cited by Dave Sobel, high operational costs are forcing large firms like Microsoft, Google, Amazon, and Uber to restrict or cap AI usage internally, reflecting an industry-wide retreat from premium pricing models due to an unclear return on investment at the organizational level. Additional developments reinforce this margin-driven shift. The federal Cybersecurity and Infrastructure Security Agency (CISA) has mandated 72-hour patching of high-risk vulnerabilities, underscoring heightened compliance requirements. Simultaneously, vendors are accelerating the rollout of governance, identity, and patch velocity tools. However, a study analyzing over 13,000 US MSPs found that those surpassing $1 million in revenue are distinguished by market positioning, online visibility, and business maturity, not by the breadth or novelty of their toolsets. For operators, the implication is clear: stacking up new vendor products is now a baseline requirement rather than a path to competitive advantage. Firms that rely solely on vendor frameworks and toolsets risk absorbing more complexity without improving margin or differentiation. Practical separation will come from owning the "judgment layer"—defining, governing, and pricing how AI functions within client environments—rather than reselling tools. Positioning, documented governance, and clear operational standards will be more defensible than investing exclusively in vendor-driven offerings. 00:00 Manufactured Urgency 03:58 The Cost Confession 06:09 Out-Buy vs. Out-Position 08:35 Why Do We Care? Supported by: Nerdio Sign up for the SMB Online Conference: www.smbonlineconference.com 💼 All Our SponsorsSupport the vendors who support the show:👉 https://businessof.tech/sponsors/ 🚀 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, a
- 6 days ago31 min
Abraham Garver: Why Private Equity Rollups Push Smaller MSPs Into New Market Niches
Vendor channel consolidation continues to restructure the MSP landscape, with private equity-backed rollups driving both market concentration at the top and increased deal volume. This episode centers on the sale of Worksighted, a 25-year-old, $27 million revenue MSP with strong vertical focus in healthcare and construction, to Thrive in a 35-day close. The structural mechanism at play is an increasing market segmentation where larger MSPs systematically acquire or merge with similarly sized providers, often leaving a gap for smaller operators as larger entities move upmarket. Primary evidence for this consolidation includes direct transaction data and workflow. According to Abraham Garver, his team handled 132 vetted buyer candidates for Worksighted, resulting in eight competitive offers after 76 signed NDAs. Thrive, having completed 27 MSP acquisitions, was able to accelerate the deal's timeline due to deep experience and preparation by both buyer and seller. The trend is further supported by Q2 market updates indicating 22 U.S. MSPs likely to come to market in 2026 and over 120 M&A transactions in Q1 alone, as reported by Drake Star. Related developments highlight the bifurcation of deal opportunities by provider size and the associated liquidity for MSPs. Private equity buyers increasingly favor acquisitions with a minimum of $3 million in revenue and $500,000 in EBITDA, while smaller MSPs are more commonly left to pursue peer-to-peer mergers or organic growth strategies. The episode also addresses the operational pitfalls of optimizing solely for high recurring revenue percentages, with evidence suggesting buyers offer premiums for organic growth and new client acquisition rather than rigid recurring revenue thresholds. For operators, these dynamics generate clear tradeoffs and risks. Larger MSPs face the challenge of integrating acquired firms and potentially divesting smaller clients who do not meet their revised minimums. Smaller MSPs may find opportunity by acquiring divested clients or targeting niche segments that fall beneath larger consolidators’ thresholds. For all providers, the importance of thorough preparation, clean financials, and strategic clarity on post-transaction roles emerges as a key safeguard against value loss and disruption. Rigid adherence to target metrics not grounded in buyer behavior—such as focusing excessively on monthly recurring revenue—carries the risk of reduced flexibility and diminished exit prospects. Sponsored by:ScalePad ABCS Sloutions LLC 💼 All Our SponsorsSupport the vendors who support the show:👉 https://businessof.tech/sponsors/ 🚀 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.
- 1 weeks ago13 min
Pressure to Adopt AI Forces MSPs to Absorb Risks Designed by Platform Vendors
Platform vendors are transferring liability and delivery responsibility for AI services onto MSPs by building structured AI practice frameworks, training programs, and service delivery methodologies. This approach is motivated by mounting economic pressures on vendors, as seen with large-scale infrastructure investments and the need for sustainable revenue models. PAX8, Ingram Micro Cloud, ConnectWise, and others are formalizing AI partner programs that enroll MSPs to deliver vendor-defined services, while shifting operational complexity and accountability downstream. The episode highlights PAX8’s Managed Intelligence initiative, aimed at helping small and midsize MSPs deliver AI services to SMB clients with minimal prior expertise. PAX8 cites its own research, which notes that 62% of SMBs view AI as essential for competitiveness and 74% plan to increase AI spending in the coming year. The economics of AI scaling are underscored by data on projected data center buildout costs—up to $15 trillion by 2030 and requiring $1.75 trillion annually just to maintain. OpenAI’s public offering, with an $850 billion valuation and $180 billion in funding, is attributed to the need for capital that private markets can no longer supply, prompting vendors to leverage channel partners for both revenue generation and market validation. Supporting developments include expanded programs at the distribution and platform levels: a PAX8-Nocdoc partnership providing managed NOC/SOC services for smaller MSPs, Ingram Micro Cloud’s collaboration with PartnerStack to formalize AI service delivery infrastructure, and ConnectWise’s introduction of an AI-native platform for predictive and autonomous IT operations. Research from Omnia and the IBM Institute for Business Value indicates underutilization of vendor market development funds and widespread deployment of AI frameworks despite only 11% of tech leaders feeling prepared—demonstrating the gap between vendor offerings and operational readiness. The implications for MSPs are significant. By enrolling in these vendor-driven AI programs, providers take on delivery risk, contractual accountability, and potential liability for AI outcomes they did not design. The structural split is clear: MSPs can either create and govern their own AI methodologies—pricing accountability as a service—or become vehicles for vendor frameworks, absorbing complexity without full compensation or control. Practical recommendations include updating service agreements for AI-related risks, building internal governance around AI deployments, and not allowing vendor or community consensus to substitute for explicit accountability for outcomes. 00:00 Channel AI Shift 03:59 Enrollment, Not Enablement 06:55 Methodology vs. Liability 10:01 Why Do We Care? Supported by: Zero Networks CometBackup 💼 All Our SponsorsSupport the vendors who support the show:👉 https://businessof.tech/sponsors/ 🚀 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
- 1 weeks ago13 min
ConnectWise Abandons ASIO: AI-Driven Platforms Shift Risk and Governance to MSPs
The episode identifies a growing governance gap as a central structural issue for MSPs and IT service providers, driven by rapid AI adoption through subscription-based tools and platforms. Rather than being introduced as controlled, IT-led initiatives, AI services are entering organizations piecemeal—often through end users and business units—undermining established accountability and management practices. This dynamic is exemplified by ConnectWise’s dismantling of its ASIO platform in favor of a new AI-native operating layer designed to unify PSA, RMM, security, and automation functions, and by clients independently layering on AI-powered tools without centralized oversight or cost control. A primary example of ungoverned risk involves unsustainable AI cost exposure. According to Axios and TechCrunch, an enterprise amassed around $500 million in a single month on Anthropic’s Claude due to unlimited, unmonitored usage. Freshworks’ survey of over 12,000 IT professionals quantifies the industry’s operational friction, finding mid-market companies waste about 25% of AI budgets on complexity, for a total of $16 billion in annual waste. Despite 89% of respondents planning to increase AI spend, only 15% have actively integrated these tools into daily workflows—revealing widespread governance lag behind adoption. Supporting developments highlight the breadth and persistence of this governance deficit. Organizations such as the Linux Foundation have responded by forming the Tokenomics Foundation to standardize AI cost tracking. Meanwhile, AI tool adoption is occurring outside IT, leading to agent sprawl, unclear permissions, and cost scaling linked to agent behavior rather than headcount. Roll-up strategies in adjacent sectors—such as Thrive Holdings’ $1 billion commitment to consolidate accounting firms under an AI operational platform—demonstrate capital’s move toward operationally governed, AI-enabled service models, suggesting a parallel risk for IT providers. For MSPs and IT leaders, these trends underscore the urgency of operationalizing AI governance as a billable, contractual service rather than an informal or embedded support task. Risks include absorbing liability for unmanaged AI usage, exacerbated operational complexity, and relinquishing margin to platform or capital entrants. Practical steps involve conducting AI tool audits, inventorying agent access and spend, instituting usage controls, and reframing account segmentation around governance and liability exposure. MSPs who define, price, and contract for governance can mitigate inherited risk and avoid being displaced by vendors or capital-backed consolidators. 00:00 ConnectWise Rebuilds 03:59 Ungoverned Agents 06:06 Roll-Up Warning 09:38 Why Do We Care? Supported by: Moovila ScalePad 💼 All Our SponsorsSupport the vendors who support the show:👉 https://businessof.tech/sponsors/ 🚀 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/mspradioTik
- 1 weeks ago21 min
Michael Privat: Data Weakness, Not AI Tools, Derails Enterprise AI Investments
A central structural mechanism highlighted in this episode is the exposure and amplification of technical and organizational weaknesses by enterprise AI initiatives, particularly as organizations pursue rapid AI adoption without adequate investment in data and process fundamentals. The episode draws on findings from an MIT Media Lab report, which found that 95% of enterprise AI pilots had no measurable impact on profit and loss, despite $30–40 billion in investment. Michael Privat, representing the healthcare technology firm Availability, discusses the consequences for organizations that apply “thin” AI overlays on top of unaddressed legacy data infrastructure and processes. The most consequential data point centers on AI’s amplifying effect. According to the MIT Media Lab report cited by Michael Privat, 74–75% of companies expect revenue growth from AI, but only 20% are realizing gains. The root cause identified is not AI itself, but foundational failures: organizations use pilots as procurement exercises rather than outcome-driven initiatives and neglect to address data consistency and process integrity. Pilot projects, in many cases, simply accelerate the visibility and scale of existing dysfunctions rather than creating new value. Further evidence is provided through discussion of operational methodologies and organizational approaches. Michael Privat details a shift from pre-AI process benchmarks, such as DORA metrics focused on predictability and velocity, toward new models that account for AI’s speed and amplification risks. He points to increasing investments in engineering capacity—in particular, tripling headcount in India—while emphasizing that efficiency gains from AI only materialize where discipline, standardization, and solid engineering “plumbing” is already in place. Both the need for audit trails and rigorous governance, especially in regulated sectors like healthcare, are flagged as structural safety requirements rather than optional layers. Operationally, the implications for MSPs and IT leaders include the risk of exposing latent deficiencies when implementing AI-driven offerings, particularly when layering automation and analytics atop fragmented or inconsistent infrastructure. Key areas of impact are the need for robust governance frameworks—especially with agentic AI, where dynamic system behaviors require ongoing accountability and auditability—and the risk that AI investments made without process and data “spring cleaning” can actually accelerate failure modes. For IT service providers, the material risks are in unexamined process debt, tool misalignment, and the temptation to prioritize velocity over resilience, ultimately increasing operational and contractual exposure. Supported by:NerdioScalePad 💼 All Our SponsorsSupport the vendors who support the show:👉 https://businessof.tech/sponsors/ 🚀 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 compa
About Business of Tech: Daily 10-Minute IT Services Insights
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.
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