Podcast
Business of Tech: Daily 10-Minute IT Services Insights
Hosted by MSP Radio · EN
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.
128episodes
Episodes
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AI Governance Moves Center Stage: Why Audits and Policy Now Define MSP Risk
Apr 800:12:59Tap to summarizeThe episode identifies a structural shift in the evaluation and deployment of AI within organizations: decision-making is now driven by governance, control, and auditability rather than by features or capabilities of AI tools. This mechanism is anchored in the need for defendable practices amidst heightened scrutiny from institutions, regulators, and insurers. The change is observable in companies such as Anthropic and OpenAI, as well as in regulatory and procurement activities tracked by outlets like The New York Times and Business Insider, signaling that market adoption is tightly coupled to liability, enforcement, and institutional risk visibility. A primary area of evidence is cybersecurity, where state-sponsored attackers have leveraged AI to automate infiltration attempts, according to reporting on Anthropic’s disclosures concerning Chinese actors targeting dozens of companies and agencies. The same sources note that Anthropic’s AI identified over 500 previously unknown zero-day vulnerabilities in open-source software, demonstrating increased operational tempo and automation on both sides of the cybersecurity equation. In procurement, declining app download metrics for Claude, following its involvement in U.S. security policy narratives, showcase how reputational and geopolitical risk can quickly alter adoption patterns. Additional developments reinforce this trend. Machine learning conferences have systematically audited and penalized the use of AI-generated peer review, leading to hundreds of paper rejections and mass article retractions, according to Semaphore and Nature. On the hardware front, HP, AMD, and Intel are collaborating to address BitLocker vulnerabilities via an industry standard rather than proprietary features, illustrating how vendors are responding to systemic risk through structural controls and standards. Channelholic’s references to workforce limitations underscore that automation’s workload cannot be absorbed by labor alone. For MSPs and IT service providers, these developments mean the core value proposition shifts from offering AI tools to governing their use, ensuring full documentation, traceability, and defensibility. Failure to treat this as a governance issue leads to underpricing, overlooked controls, and transfer of liability for autonomously executed actions. Providers must now develop acceptable use policies, audit AI agent activity logs, and systematically vet vendors on audit trail, policy, and breach notification—otherwise risking exclusion from regulated deals and exposure to contractual and compliance penalties. 00:00 The Visibility Problem 03:45 Platform Lock-In 06:30 Governed or Liable 09:35 Why Do We Care? Supported by: CometBackUp and TimeZest 💼 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.
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AI Deployment Exposes Workflow Gaps—MSPs Face Increased Liability and Coordination Demands
Apr 700:13:06Tap to summarizeAutomation and AI are shifting the pricing and accountability models for managed service providers, with risk increasingly centered on governance, workflow coherence, and outcome measurement rather than tool deployment. Evidence from studies like Fixify, reports from ChannelLive, and real-world cases such as the City of Seattle’s pause on Microsoft Copilot rollout highlight that technology adoption is now gated less by access to solutions and more by readiness to govern, coordinate, and prove outcomes across fragmented processes. Automation exposes underlying coordination debt, moving the client focus from paying for labor time to demanding measurable outcomes and managed exceptions. Fixify’s analysis of more than 50,000 support tickets from 30+ organizations showed tickets with at least 75% automation saw average resolution in 4.4 hours versus roughly three days for non-automated tickets. Data cited from OpenAI found that 93% of London SMBs use AI tools, but readiness and uptake are highly uneven within the UK. In Seattle, more than 450 labor hours per week were reported saved during the Copilot pilot, yet adoption was paused due to concerns over data governance and accountability for errors, not tool capability. According to coverage in GeekWire and IT Pro, these dynamics are shifting buyer expectations and vendor liabilities. Supporting developments include security concerns outlined by Kaseya’s INKY report, which highlights the normalization of AI-generated phishing and changes in attack formats, forcing defenders to rethink detection and response. The operational surface of automation—where AI reshapes data, not just moves it—means standard controls and classic alerts are increasingly bypassed. Reports from Information Week and experts such as Dan Lorman emphasize that accountability for exceptions, shadow AI usage, and data exposure is shifting by default onto providers, whether or not contracts address these risks. These trends mean MSPs face direct operational and contract exposure: clients and auditors are demanding proof of how AI touches data, how exceptions are handled, and where logs and controls exist. Pricing based on seats or tickets is becoming harder to defend as automation compresses labor and raises expectations for accountability. Providers must reconsider SLAs, explicitly define automation boundaries, charge for governance activities, and move toward outcome-based pricing models if they want to avoid absorbing unpriced liability and operational complexity. 00:00 Automation Divide 04:27 Coordination Debt 06:01 Automation Liability 09:18 Why Do We Care? Supported by: JumpCloud HaloPSA 💼 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.
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Richard Luna: MSPs Risk Margin Erosion by Relying on Rented Stacks and App Reselling
Apr 600:26:40Tap to summarizeThe episode exposes a structural shift in the MSP sector toward increased commoditization and infrastructure dependence, with an industry trend favoring outsourced, app-focused service delivery over internal technical depth. Protected Harbor, led by Richard Luna, is presented as a counterpoint—running its own infrastructure and software, and prioritizing ownership of the technical stack rather than relying extensively on third-party platforms. Luna argues this industry-wide movement has created a market where low entry barriers and rented, commoditized solutions undermine differentiation and inflate operational risk. Central to the discussion is the declining emphasis on technical generalists within MSP organizations, replaced by hyper-specialization and a proliferation of app resale as a service model. Luna attributes industry-wide declines in service quality and net promoter scores (typically ranging from 30–38 for MSPs) to these trends, suggesting the loss of generalist skills erodes problem-solving capacity and increases reliance on external vendors for core functions. He states that running owned infrastructure and open-source tools allows for tighter cost controls, standardization, and faster response to operational events—a contrast to MSP models that outsource most functions. Supporting developments include a detailed critique of the risk dynamics associated with using hyperscale vendors for client-facing services. Luna distinguishes between utility-grade services like power, which can be outsourced without significantly affecting the customer relationship, and services closer to the client experience (e.g., remote access, help desk, data workflows) that, if outsourced, reduce both control and differentiation. Additional risk surfaces are highlighted with the integration of AI and automation, especially when MSPs use large public models that may ingest sensitive client data and create potential information leakage or competitive exposure. The operational implications for MSPs and IT leaders include heightened vendor dependency, expanding contract risk, and declining service quality when organizations prioritize app resale and specialization over in-house competency and direct infrastructure management. To mitigate these risks, the episode suggests MSPs should reassess which functions to control internally versus outsource, invest in developing technical generalists, and scrutinize the downstream effects of workflow automation and AI adoption—especially regarding client data privacy, model training, and real-time operational accountability. 💼 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.
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AI Moves MSPs From Tool Support to Operational Liability as Hybrid Platforms Expand
Apr 300:10:49Tap to summarizeThe episode highlights the increased operational complexity and governance burden resulting from the fragmented adoption of AI and hybrid, multi-platform environments in IT service delivery. Companies such as Proton (with Proton Workspace) and governance platforms like KiloClaw represent the expanding landscape of tools requiring oversight, while core productivity platforms continue to diversify. Research from Westcon-Comstor, Forrester, and Gartner, as reported by Dave Sobel, demonstrates that AI is not a turnkey solution but introduces a new operational surface area that must be actively managed. Channel Dive’s Westcon-Comstor survey of 500 MSP and cloud decision-makers found that almost a quarter see cloud migration and management as their main revenue opportunity, but over 30% identify cross-platform data management as the top challenge. Security and governance pressures follow closely. Forrester data shows only a marginal increase in prompt engineering proficiency, while most employees report that AI increases workloads rather than reducing them, indicating persistent process fragmentation and unclear roles. VentureBeat cited Intuit's observation that successful AI adoption is characterized not by autonomy, but by controlled execution where humans maintain accountability for judgment and exception handling. Supporting this, products like Proton Workspace are fragmenting the core productivity stack, and the emergence of “shadow AI” (where personal AI agents operate outside formal governance) is driving organizations to deploy governance tools such as KiloClaw. According to research cited from Front, 93% of companies are using AI in customer operations, yet 71% report significant AI-related issues in the past three months, indicating that poorly governed automation increases handoffs, exceptions, and escalations which often default to MSPs to resolve. For MSPs and IT service providers, these trends translate into an expanded responsibility for governing the automation and AI layers within client environments. When MSP contracts and service definitions fail to specify the scope of coordination, exception handling, and governance for AI and automation tools, the provider risks absorbing significant unmetered labor and liability. The episode emphasizes that governance tooling should be viewed as temporary infrastructure and not a core component of an MSP practice. Providers should audit client environments for AI exposure, review contract terms, and prepare to offer explicit, separately priced control layers as customer demand for governance outcomes increases. 00:00 Stack Fragmentation 02:56 Human-Bounded AI 04:25 Coordination Tax 07:18 Why Do We Care? Supported by: CometBackup HaloPSA 💼 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.
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AI Agents Shift MSP Accountability: Howard Cohen on Liability Beyond IT Infrastructure
Apr 200:34:52Tap to summarizeThe episode highlights a structural shift from MSPs managing infrastructure to supplying, designing, and maintaining AI-driven agents, raising new questions of accountability and operational risk. As AI agents evolve from assistive chatbots to supervised and potentially autonomous systems, the channel faces liability transfer, governance gaps, and an increased need for systems architecture competence. Companies referenced include Klarna, which serves as a cautionary tale for poor AI design, and vendors such as OpenAI, Anthropic, and Microsoft, all of whom are engaged in moving the market toward agent-based operations. The most consequential development detailed is the shifting liability for AI-driven outcomes: agent builders and MSPs become responsible for unintended actions, errors, or hallucinations produced by deployed agents. Clarifying accountability is necessary as incidents—such as email mishandling or unauthorized decisions by AI agents—do not absolve the MSP of responsibility. Recent discussions indicate few cases where foundational technology vendors are held liable; usually, the burden falls on those who deploy and support AI agents for clients. The episode cites Klarna’s experience as a failure of design thinking, emphasizing that the design of agents—beginning with the end in mind—is key to mitigating risk. Supporting developments include the segmentation of AI solutions across SMB, mid-market, and enterprise clients, with complexities scaling as MSPs attempt to transition from simple assistive AI to supervised and fully autonomous agents. The episode notes that fewer than 5% of deployed agents are fully automated, and security vendors are increasingly involved in AI governance, risk, and compliance (GRC) due to the importance of data governance in AI projects. Regulatory coverage and insurance gaps are recognized, with advice for MSPs to re-examine their E&O policies and move toward frameworks for AI trust and transparency. Operational implications for MSPs and IT service providers are concrete: providers must reconsider contract exposure, review insurance coverage, and invest in AI governance mechanisms such as agent oversight and auditing. Price-to-value methods are recommended over simplistic per-agent or per-hour billing, requiring sophisticated project scoping and market analysis. The episode underscores that MSPs cannot rely solely on vendor solutions for risk mitigation—service providers are ultimately accountable for AI outcomes delivered to clients, necessitating operational safeguards and human-in-the-loop design wherever possible. Supported by: ScalePadZero Networks 💼 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.
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Control Layer Becomes Essential: Clients Trust AI Outputs Less, MSPs Must Provide Audit Trails
Apr 100:11:48Tap to summarizeThe dominant structural shift highlighted is the movement of value from AI-driven features to the ownership and governance of the control plane—specifically, entities that set boundaries, maintain proof, and keep automated workflows within defined limits. This shift is evidenced by workforce polling from Quinnipiac University, business formation trends tracked by the Bank of America Institute and Census Bureau data, and product launches from vendors like TeamViewer and KnowBefore. These developments underscore a growing reliance on automation where traditional human oversight is minimized, and technology increasingly assumes direct control over work execution. The episode details workforce sentiment, citing a Quinnipiac University poll where only 15% of respondents expressed willingness to work for an AI boss, and 70% anticipated AI would reduce job opportunities. Bank of America Institute data notes a 15% year-over-year increase in high propensity businesses—those likely to launch—while businesses planning to hire have fallen by 4%. TeamViewer has introduced TIA Reporting, which generates dashboards via natural language prompts, reducing specialist requirements. KnowBefore’s ADA Orchestration automates security awareness scheduling and execution, reportedly shortening setup times from hours to seconds. These examples show how vendors are deploying AI tools that replace specific manual oversight with algorithmic management. Supporting developments reinforce the governance gap. According to a CIO Dive report, 96% of C-suite leaders expect productivity gains from AI, yet 77% of employees report increased workloads, signaling misalignment between leadership intent and actual outcomes. Tech Bullion reveals 60% of organizations have AI integrated in at least one core function, with 65% using generative AI regularly, but fewer than a quarter have operationalized ethical AI frameworks. The Verge covers enhancements to Anthropics’ tools that embed guardrails where organizational controls are lacking. Additional survey data from TechCrunch shows that usage of AI is growing while trust in its outputs remains weak; only 24% of respondents trust AI most of the time. Operationally, the implication is clear for MSPs and IT leaders: as organizations reduce human oversight and delegate more work to automation, the auditability, accountability, and control of automated workflows become direct contractual risk. Control layers—such as logging, exception handling, approval thresholds—must be productized and priced, not treated as informal advisory work. Liability for automation failures must be clearly assigned and managed through contractual terms, with automation incident response separated from standard support. Without enforceable governance and evidence of control, MSPs risk absorbing unpaid remediation work as clients expect both automation benefits and assurance of outcome. 00:00 Bossless Workforce 03:22 AI, No Guardrails 05:45 Govern or Absorb 08:41 Why Do We Care? Supported by: Nerdio HaloPSA 💼 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.
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Why Stack Complexity, Not Automation, Drives MSP Margin Volatility
Mar 3100:11:07Tap to summarizeMargin volatility driven by operational complexity and governance gaps is reshaping the economic landscape for MSPs and IT service providers. Evidence shows that the effectiveness of automation now depends less on deployment volume and more on whether it reduces complexity and enforces coherence across client environments, as highlighted by Speaker A referencing reports from TechCentral, Avik, and vendors such as VMware, Broadcom, Microsoft, and Apple. The key structural shift is that clients and technology vendors are consolidating platforms and workflows to restore operational clarity, which fundamentally alters how MSPs structure service offerings and pricing. The most consequential development cited is Broadcom’s transition of VMware users toward Cloud Foundation 9, with half of surveyed organizations (n=450 across 14 countries, each with 500+ employees) stating an intent to reduce their VMware footprint by 2028 in response to bundled offerings deemed too costly or complex, according to The Register. This reduction in adoption signals accelerated migration efforts, downsizing of virtual machine fleets, and movement toward alternative platforms, indicating margin pressure and uncertainty for MSPs supporting heterogeneous environments. Supporting developments reinforce this shift. Apple’s introduction of Apple Business—a unified platform encompassing device management, email, calendar, directory services, and marketing tools—demonstrates a move toward environments with fewer moving parts and less operational ambiguity. Microsoft’s Copilot Cowork for Microsoft 365 similarly embeds AI directly within core workflows, with enterprise guardrails and coherence at its center, rather than simply layering on new tools. Reports from Avik and Forrester underscore persistent gaps between leadership intent and frontline capability, especially around fragmented visibility and unaddressed governance requirements, amplifying the consequences of unmanaged complexity and AI misalignment . For MSPs and technology leaders, the operational takeaway is a need to prioritize the reduction of client environment complexity and establish explicit controls around AI and automation. Auditing fixed-fee agreements for AI work clauses, defining coverage for remediation and exception handling, and building enforceable governance layers are critical to avoid absorbing unpriced risk and free labor. Stack simplification is now paramount, since automation on top of complexity increases volatility and cost. Service contracts are trending toward bifurcation, with standardized platform offerings at lower rates and non-standard exception handling priced separately, shifting where profit and risk reside. 00:00 Consolidation Wave 03:08 Coherence Gap 04:59 Margin Leak 08:14 Why Do We Care? Supported by: ScalePad Zero Networks 💼 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.
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Howard Rubin: Why Tech Spending Benchmarks Often Mislead Operators
Mar 3000:20:12Tap to summarizeA persistent structural challenge highlighted in this episode is the disconnect between technology investment and demonstrable business outcomes, which fuels operational inefficiency and accountability gaps in technology spending. As articulated by technology economist Dr. Howard Rubin, a common industry tendency is to measure IT success based on technology adoption or budget size rather than objective business results. This pattern is not limited to large enterprises but affects small and mid-sized organizations, many of which feel compelled to maintain “current” technology without clear evidence of operational or financial return. Primary evidence centers on the inadequacy of current macroeconomic indicators—such as the Consumer Price Index (CPI) and Gross Domestic Product (GDP)—for assessing technology value and risk in smaller organizations. Dr. Rubin noted that official statistics and classic economic telemetry do not track the true inflation or productivity impact of technology stacks, particularly as hyperscalers invest trillions in infrastructure. The transcript highlights that price increases or capital recovery pressures in services like Microsoft Office or cloud platforms are likely to affect smaller organizations first, exacerbating operational risk and cost unpredictability. Supporting developments include analysis of flawed benchmarking practices, such as using IT spend as a fixed ratio to revenue or operating expense without examining enabling value or efficiency outcomes. Failure to contextualize technology investments can lead to counterproductive decisions, like arbitrary cost-cutting when IT as a percentage of expenses rises, ignoring possible operational savings or revenue lift driven by technology. Dr. Rubin advocates for pattern recognition and bespoke analysis over reliance on aggregated industry numbers, pointing out that mass market vendor investments and macroeconomic policy often obscure direct impacts at the SMB and MSP level. For MSPs and technology decision-makers, the operational implication is a heightened need to create internal technology inflation indices and track category-specific price pressures. Rather than relying on aggregate industry benchmarks or public economic data, service providers should establish tailored metrics to capture their own cost structures, labor pressures, and technology value. The discussion points toward the need for more deliberate accountability and ongoing evaluation—especially given that upstream price increases from hyperscalers and SaaS vendors are set to impact providers and their clients, with limited ability to negotiate at smaller scale. 💼 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.
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Draup Data Shows Cybersecurity Hiring Pressure Will Persist Into 2028 - Vijay Swaminathan
Mar 2700:21:13Tap to summarizeThe core structural shift highlighted involves a skills convergence and expanded role definition across technology and business functions. Draup’s Global Tech Talent Report and commentary by Vijay Swaminathan underscore the rising complexity and blending of job expectations, particularly as artificial intelligence (AI) and automation penetrate workflows. Companies are reorganizing hiring strategies and role definitions, prioritizing adaptable expertise over traditional IT job titles, and emphasizing domain specialization. Service providers are observing a move from specialized roles toward hybrid positions that demand broader understanding of business operations, compliance, security, and AI. The most consequential development is the persistent and intensifying shortage of cybersecurity professionals, as referenced in Draup’s report. According to Vijay Swaminathan, the gap between open cybersecurity positions and qualified candidates is projected to continue through at least 2028, driven by accelerated adoption of AI/ML, IoT, and cloud technologies. Job requirements have shifted, with a 25–30% increase in skill expectations for roles in engineering, security, and product management. This expansion of necessary competencies outpaces traditional training and hiring channels, further complicating workforce planning for the sector. Additional developments reinforce these structural stressors. The report asserts that 40% of current core tech skills will be partially obsolete by 2027 due to ongoing skill fusion and AI-enabled workflows, not just layoffs. Companies are also recruiting for new categories such as “builders,” “orchestrators,” and “synthesizers,” whose duties blend technical and business intelligence. Vijay Swaminathan points out an emerging need for deep domain expertise, process documentation, and AI governance, as evolving data collection and product experience initiatives redefine value creation across verticals like retail and hospitality. For MSPs, IT service providers, and technology leaders, these changes increase operational complexity and demand more investment in continuous upskilling, industry-specific hiring, and governance. Maintaining domain specialization and robust compliance documentation will become baseline requirements for winning and retaining business, but these add overhead and require strategic selection of verticals. The evolving tech stack and expansion of hybrid workflows drive greater dependency on creative, adaptable talent—exposing firms to increased risk if reskilling and governance fall behind the pace of automation and regulatory scrutiny. Supported by: NerdioHaloPSA 💼 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.
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How AI and Vendor Defaults Are Redefining MSP Liability: Brad Gross on Contract Risk
Mar 2600:42:21Tap to summarizeThe episode identifies risk allocation and governance gaps in managed service provider (MSP) contracts as the prevailing structural challenge driven by the rapid deployment of AI solutions and evolving vendor models. This shift is characterized by increased pressure from both upstream vendors—including Microsoft, Anthropic, and OpenAI—and end clients, who demand swift adoption of AI-enabled productivity features without corresponding updates to underlying agreements or clarity on responsibility. These market developments have introduced new liability exposures for MSPs, as legacy contract language is ill-suited for environments where MSPs rely on, or are required to implement, external or agentic technologies. The discussion details how aggressive marketing and client demand for AI solutions outpace both technical maturity and customer readiness for governance. According to Speaker B, this urgency often pressures MSPs to deploy AI features—such as automated recommendations for firewall settings or configuration changes—without comprehensive risk disclosure or client policy alignment. The transcript notes a pattern in which clients insist on operational changes based on AI system outputs, even when technical staff advise caution, resulting in disputes over responsibility when these interventions lead to adverse outcomes. The episode further highlights operational risk endemic to the shift toward consumption-based pricing and increasing default configurations set by upstream vendors. For instance, Microsoft’s move toward extended service term (EST) pricing and other consumption models are cited as drivers that transfer variable cost risk directly to MSP clients. The lack of customer engagement in quarterly business reviews and misalignment in expectations around true-up processes were presented as reinforcing issues, potentially leaving service providers solely accountable for the financial and operational impact of unexpected platform behavior or AI incidents. For MSP operators, the immediate operational implications include the necessity for explicit contract revisions, detailed service descriptions, and targeted AI-specific policies referenced at the quoting and onboarding stages. Providers are advised to distinguish clearly between services, tools, and outcomes within agreements and establish client buy-in through formal documentation and regular communication. Without disciplined governance procedures, written allocation of AI-related risks, and enforced business reviews, MSPs face elevated exposure to liability inherited from vendor defaults and unaddressed gaps in legacy contract frameworks. Supported by: RythmzABC Solutions, 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.
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