Vendors are rewriting the rules on MSPs faster than anyone can track — pricing, partner programs, liability, and now AI. Business of Tech is the daily MSP news briefing that tells you what changed and what it means for your business.
Every weekday, channel veteran Dave Sobel picks the MSP and IT services news that actually moves your margins, contracts, and risk, and answers the one question that matters: Why do we care? No vendor cheerleading and no press-release rewrites — independent analysis for managed service providers, IT services leaders, and the vendors who sell to them.
Short daily episodes keep you current in about 15 minutes. Longer interviews go deep with MSP owners, investors, analysts, and channel executives on where the managed services market is heading.
What this MSP podcast covers:
• AI for MSPs — AI pricing and consumption billing, AI liability and governance, and AI agents in the service desk
• MSP pricing and profitability — per-user vs. usage-based pricing, margins, service agreements, and vendor rebates
• MSP M&A and private equity — acquisitions, roll-ups, valuations, and what consolidation means for independent MSPs
• MSP vendors and partner programs — Microsoft, Kaseya, ConnectWise, N-able, Pax8, and how channel programs shift risk onto providers
• MSP cybersecurity and liability — cyber insurance, compliance, regulation, and the security-stack decisions that expose a managed service provider
• MSP operations — automation, PSA and RMM, hiring, and the operational maturity that separates growing MSPs from stalled ones
Questions we answer:
• How should an MSP price AI services when vendors move to consumption billing?
• Who carries the liability when AI acts inside a client environment?
• What does private equity consolidation mean for MSP valuations?
• Which vendor partner program changes quietly cut MSP margins?
• What do insurers and regulators now expect from managed service providers?
Business of Tech is produced by MSP Radio, the independent media company for the managed services and IT channel community. Hosted by Dave Sobel, MSP industry analyst and longtime channel veteran. Written versions of every episode, with full source links, at businessof.tech.
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Détails sur Business of Tech: Daily MSP News & IT Services Analysis, podcast de MSP Radio, Dave Sobel, Managed Service Provider (MSP) Industry Analyst
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MSP contracts: Why renewal timing now determines your leverage
Épisode 2097
mardi 10 novembre 2026 • Durée 13:18
The key market dynamic is the decline of feature differentiation among MSP software platforms, driven by AI making new features inexpensive and quick to replicate. This has led incumbent vendors to focus on securing long-term customer commitments, while challengers enter with lower prices and more integrated offerings. Market power now increasingly concentrates at renewal, where MSPs can negotiate flexibility rather than feature sets.
Omdia reported the global RMM and PSA market reached $600 million in Q2, up 15.6% year-over-year. NinjaOne grew its market share to 20%—matching ConnectWise—after a 53% increase in RMM revenue, while Kaseya fell to 18.8%. Flamingo is offering an integrated platform with AI agents at $1 per device, claiming hundreds of MSPs in use and thousands on a waitlist. Meanwhile, N-able’s growth slowed with reduced full-year outlooks, citing customers seeking lower prices or shifting to competitors.
Supporting developments show vendors embedding previously premium AI features into standard packages and pressing MSPs toward long-term contracts with price adjustments. Studies indicate clients now prioritize evidence of security and recovery capability over purchasing more tools, but few MSPs currently provide the attestation and documentation insurers demand.
For MSPs and IT leaders, contract flexibility, data portability, and renewal timing have become higher risk factors than feature lists. Operational planning should emphasize short-term contracts, clarity on exit options, and readiness to provide recovery evidence—reducing lock-in just as pricing pressure and functional parity increase.
About Business of Tech: The daily MSP news and analysis podcast for managed service providers and IT services leaders. Host Dave Sobel covers AI for MSPs, MSP pricing and profitability, MSP M&A and private equity, vendor partner programs, MSP cybersecurity and liability, and MSP operations — and answers the question every story raises: Why do we care? Produced by MSP Radio.
The episode highlights a fundamental shift towards automation and agentic workflows in IT service delivery, as described by Slide and its leadership. This shift is exemplified by the move from traditional, manual “what” work in IT and software engineering to task automation at a machine or agentic level. Slide’s adoption of internally developed SaaS backup for Microsoft 365 and accelerated product roadmaps—enabled by recent AI advancements—reflects this industry-wide movement toward leveraging technology for operational speed and efficiency.
The most consequential development discussed centers on the patent litigation between Slide and Kaseya/Datto. According to public records and statements from Slide, Kaseya and Datto expanded their infringement claims to cover 16 patents, now adding three more, and are seeking an injunction against Slide’s BCDR platform. Slide, led by interim CEO Austin McChord, maintains that it did not infringe on patents or misuse trade secrets, asserting confidence in its legal position and product differentiation. Slide has not filed any patents of its own as of now. The litigation brings uncertainty for MSP partners, as Kaseya’s complaint includes claims that customer usage may also constitute infringement.
Supporting developments include leadership changes at Slide, with Michael Fass stepping down and no direct link to the ongoing litigation, as confirmed by Slide. The episode also details Slide’s rapid internal technology adoption, with AI-driven acceleration of development cycles, reorganization of development teams, and an emphasis on reducing human synchronization bottlenecks. Internally, Slide is measuring engineering progress through deliverable output and reduction in support tickets rather than traditional process metrics, reflecting a shift in operational accountability.
For MSPs and IT service providers, the practical implications include growing exposure to supplier legal disputes and potential contract risk, especially where customer usage is implicated in ongoing litigation. The move toward automation introduces new governance challenges as responsibilities shift from manual to machine-driven processes. Leaders should closely monitor vendor claims about agentic technology readiness, manage costs as AI tools are not always cost-effective at current scale, and ensure safeguards are in place when outsourcing operational tasks to automated systems. Ongoing adaptation will be required as both legal environments and technology capabilities continue to change rapidly.Supported by:
MSP operations: AI value only comes after internal process rebuilds
Épisode 2095
vendredi 6 novembre 2026 • Durée 12:36
The core structural shift identified is the widening gap between increased AI spending by MSPs and measurable business value. According to TD SYNNEX’s global survey of over 1,500 technology resellers, two-thirds are accelerating AI investment, but only one in five derives meaningful revenue. The value of AI does not come from buying licenses but from rebuilding specific processes—something most MSPs have yet to achieve at scale.
A key development is consolidation-driven investment: Lyra Technology Group, backed by Evergreen, is embedding over 50 AI engineers within its MSP portfolio by 2027. This enables rapid in-house process redesign and service innovation, a tactic most independent MSPs cannot financially match. Lyra's approach leverages access to permanent capital to fund upfront engineering efforts before client revenue materializes.
Supporting evidence confirms that few AI pilots reach production—only 13% according to TD SYNNEX—and that discussions within MSP circles remain subdued, with most usage limited to simple applications like email drafting. Practical success stories, such as custom tools that significantly cut internal processing hours, required extensive internal investment and experimentation rather than simple license acquisition.
For MSPs and IT service providers, these trends shift accountability and risk to the operator. Simply selling AI seats or access does not result in demonstrated value or renewal justification. Sustainable advantage depends on successfully implementing and documenting AI-driven process changes internally before offering them as client solutions. This raises the bar for governance, internal investment, and credibility in AI-related projects.
AI agents: how MSPs define value beyond vendor features — Howard Cohen, Agentic MSP
Épisode 2094
jeudi 5 novembre 2026 • Durée 45:44
A structural gap persists between the promotion of AI solutions and their demonstrable, value-based adoption within the managed services sector, resulting in unclear accountability and risk of misaligned incentives. Vendors such as Microsoft and Anthropic push seat-based AI sales (e.g., Copilot, LLM services), but few MSP-led case studies exist to verify real client impact. Most reported usage centers on basic, assistive functions—despite a marked increase in AI discussion among MSP communities.
The most notable finding is the disparity between AI licenses sold and those actively used, with implementation typically limited to automation of simple tasks such as email drafting or meeting summaries. According to analysis and peer reporting, meaningful MSP-led successes are rare, and nearly all documented results reflect either vendor-supplied examples or internal, non-client MSP automation initiatives.
Further supporting evidence highlights concerns around increased reliance on external vendors, lack of outcome measurement standards, and rising operational complexity. MSPs are experimenting with replacing SaaS tools by building their own AI-driven solutions, yet unresolved legal responsibility—especially for autonomous agents—and evolving security threats complicate adoption. Vendors have accelerated AI feature rollouts and moved to consumption-based models, heightening the risk that features are resold without ensuring measurable client value or manageable costs.
Practical implications for MSPs include the need for stronger governance, proactive risk management, and clearly demonstrating value delivered, rather than focusing on license volume. As manufacturers prioritize consumption models, managed services providers face contract risk and potential liability if promised outcomes are not met. Strategic focus should be on internal testing, outcome-based measurement, and identifying small process improvements that directly benefit clients and can be shown to reduce cost or improve efficiency.
MSP contracts: Free AI agents bring new liability unless agreements change
Épisode 2093
mercredi 4 novembre 2026 • Durée 14:19
The episode highlights a structural shift in which MSPs face increased contractual and operational risk as vendors embed AI agents in managed IT tools by default, often without explicit customer agreements or added cost. This practice blurs accountability for AI-driven actions and outcomes. Key examples include MSP360 and Omnissa, which have activated AI agents to automate support and administrative functions across their platforms without requiring provider or customer sign-off.
MSP360’s MCP server connects its backup platform to Claude and ChatGPT, allowing agents to diagnose and remediate issues at no extra charge. Omnissa offers AI agents for tasks like vulnerability management and application testing. Data from ActivTrak and a UC Berkeley study suggest that AI adoption correlates with longer work hours and increased task switching, raising doubts about whether productivity gains translate into business value.
Related developments—such as Reddit and Warcraft Logs restricting or monetizing previously free access—underscore that free features can be withdrawn or repurposed by vendors at any time. Legal analysis from Mayor Brown and operational feedback by Ignacio Lopez (WorkSmart.ai) indicate that responsibility for errors or failures by AI agents remains with the MSP, and most client agreements currently lack clear AI governance language.
For MSPs, these trends elevate the need for precise contract terms, audit-ready documentation, and transparent client communication regarding agent scope and accountability. Without such rigor, risk shifts onto the MSP by default. As vendors standardize tooling, only well-defined agreements offer meaningful differentiation or protection in service renewals and dispute scenarios.
AI for MSPs: Vendors profit from activity, not resolved tickets
Épisode 2092
mardi 3 novembre 2026 • Durée 13:56
A structural margin pressure is emerging as AI manufacturers bill MSPs for agent activity, while MSPs are paid by clients for resolved outcomes. Companies like ConnectWise and Super IT charge based on volumes of AI-driven attempts (agent activity, token usage), creating a financial disconnect—since MSP contracts tie revenue to tickets actually solved and kept closed, not the process steps taken.
ConnectWise introduced an RMM agent that automates diagnostics and ticket triage within its platform. Company-supplied data claims substantial efficiency gains: for one partner, 99% of over 7,000 tickets were evaluated in 30 days, but these metrics center on activity and hours "handed back," not the net number of tickets resolved. Shield Technology Partners’ analysis of its Forge platform found that higher pass rates from advanced models like GPT-6 increased the per-ticket cost, and that calculations often did not include the human review and correction required by agents’ errors.
Further developments reinforce this trend. Super IT’s North America plans charge for AI agent activity levels, and Cloudera’s industry survey found only 27% of enterprises can accurately measure AI spend, with just 23% reporting net-positive value. Vendor-reported metrics prioritize activity and recurring revenue, not actual outcome delivery—leaving MSPs to bear the impact of unresolved tickets on their margins.
The operational consequence is that MSPs must track the actual cost per resolved ticket—including failed agent attempts and human verification—to accurately set pricing models and protect profitability. Not accounting for this hidden cost can erode margins and obscure the real impact of automation initiatives. Accurate governance relies on updating pricing models and operational processes to reflect the full scope of AI-related costs and investments.
AI for MSPs: Liability is landing on operators, not software vendors — Bernhard Kirchner, SynData Labs
Épisode 2091
lundi 2 novembre 2026 • Durée 23:26
The episode centers on a structural shift in technology risk management: liability for AI decisions is increasingly transferring downstream from technology vendors to MSPs and their clients. Insurers are moving to exclude generative AI from standard liability policies, while California regulators have mandated new automated decision-making rules with specific risk assessment and audit requirements for certain businesses operating above defined thresholds. Product licensing from major AI manufacturers such as OpenAI and Anthropic continues to disclaim liability, relying instead on "as is" terms that put post-deployment legal exposure on service providers and end users.
The most consequential development discussed is the combination of insurance market adaptation and new regulatory mandates. Insurers are segmenting their approach: some explicitly exclude AI coverage via policy riders, others remain silent (neither excluding nor affirming coverage), and a minority price for AI-related risks. According to Bernhard Kirchner, silent coverage offers limited protection and will not shield MSPs from liability unless operators can demonstrate robust risk assessment and control activities. Simultaneously, under California regulations effective January 1, MSPs supporting clients above $26.25 million in California sales or with over 100,000 California clients are obligated to generate and retain evidence-based AI risk assessments, updating these every three years or upon substantive change.
Several supporting developments reinforce this liability transfer and governance gap. ISO has released optional generative AI exclusions for general liability, and specific carriers, such as Berkley, have implemented absolute exclusions across multiple product lines. Kirchner notes that the lack of clarity in many insurance contracts creates further exposure, as legal precedents—including the Air Canada chatbot case—suggest that courts treat AI as an agent of the business deploying it, not a standalone legal entity. Evidence and documentation requirements, including technical evaluations and governance records, are beginning to emerge as practical minimums for qualifying for any future AI coverage.
The implications for MSPs and IT service providers are a marked increase in contractual, regulatory, and operational responsibility related to managing AI risk. MSPs working with affected clients must closely audit their customer footprint, update risk documentation, and explicitly clarify risk allocation in contracts and master service agreements. Lacking proactive compliance or documented controls, both MSPs and clients risk significant uninsured exposure, with limited recourse to recover from AI failures. Operational safeguards—such as periodic self-assessment, updated evidence retention, and clear assignment of liability—are emerging as necessary components for both competitive differentiation and risk management.Supported by:
MSP Cybersecurity: Faster Patching Won’t Win This Race
Épisode 2090
vendredi 30 octobre 2026 • Durée 12:24
The episode identifies a structural shift: traditional patching is no longer sufficient protection as the act of releasing a patch now informs and accelerates attackers, particularly with the use of AI. When vendors publish fixes, attackers can promptly identify and exploit not-yet-patched systems at scale. Companies and data sources underlying this shift include OpenAI, Microsoft, CISA, and the Verizon 2026 Data Breach Investigations Report.
The most consequential development is Verizon’s finding that vulnerability exploitation now leads breach causes at 31%, overtaking credential theft and phishing. The percentage of fully remediated exploited flaws has declined to 26%, and the average time to fix has increased. Notably, 263,000 servers in the U.S. still run unsupported PHP, and coordinated AI-driven attacks have reduced attacker dwell time to hours in real-world incidents like the ConnectWise breach.
Vendor responses illustrate the risk landscape. N-able has launched AI-assisted patching to speed remediation and scale endpoint management, but its patching platform was itself compromised. Industry observers such as Krugman and Thompson foresee a move away from open internet-facing systems toward closed or gated platforms, accepting slower workflows as a tradeoff for reduced exposure.
For MSPs and IT service providers, the implication is clear: the key operational metric is not patching speed or compliance, but minimizing clients’ internet-exposed assets. Providers should classify all client-facing resources, move critical services into platforms with pre-release patching or behind access controls, and focus quarterly reporting on reducing the attackable surface. Patching remains a backstop, but accountability shifts to exposure reduction as both attackers and defenders automate.
MSP AI agents: Who owns risk and billing as vendors go autonomous?
Épisode 2089
jeudi 29 octobre 2026 • Durée 35:35
The episode highlights the increasing shift of operational risk and accountability to MSPs as AI-powered agents become integrated into client environments through white-label and usage-based models. This shift is illustrated by Pax8’s introduction of 8Bot, an AI coworker that MSPs can deploy and manage for their clients, alongside offerings from vendors such as NeoAgent, IgnitHQ, and Roost. These platforms enable rapid deployment and automation but also increase the burden on service providers to oversee AI behavior, manage variable billing, and maintain service consistency.
Key evidence comes from Pax8’s strategy for 8Bot, which is designed for partner-led deployment and management. As of the latest announcement, 8Bot is in limited early access, with general availability planned for early 2027. Its pricing model has not yet been fully announced. Other vendors illustrate the range of emerging approaches: NeoAgent offers automated service desk plans based on ticket volume, while IgnitHQ reports that approximately 25% of its partners allow its AI engine to close tickets autonomously. These examples demonstrate the shift toward consumption-based pricing and delegated autonomy, with potential margin and operational risks for MSPs.
Secondary developments reinforce this trend. Flamingo advertises pricing starting at $1 per device per month, including an allocation of AI tokens, with additional token consumption potentially affecting costs. Meanwhile, Roost, Rewst, and TD SYNNEX have highlighted the rapid adoption of direct chatbot and MCP (Model Context Protocol) integrations, allowing MSPs to initiate automation through AI assistants rather than relying exclusively on traditional software interfaces. Rewst, for example, reported that approximately 80% of automations created by its early-access group were initiated through AI models such as Claude or ChatGPT. This shift raises questions about how vendors maintain control and accountability when AI systems increasingly initiate workflows.
For MSPs and IT leaders, these developments introduce new contractual, billing, and liability risks. Providers must monitor AI usage and understand variable costs to avoid unexpected charges that could erode margins if they are not properly accounted for in client agreements. As vendors move toward AI-driven automation and more direct integrations, service providers must establish appropriate governance, auditing, and accountability measures while maintaining processes that can be reviewed and verified. Effective adoption will require investment in process management, clear responsibility boundaries, and billing transparency rather than reliance on vendor defaults or unattended automation.Supported by:
MSP Hiring: AI Took the Apprenticeship
Épisode 2088
mercredi 28 octobre 2026 • Durée 13:44
The episode documents a structural shift in the managed IT services sector: automation and AI are displacing both entry-level and advanced technical work, eroding the traditional skills ladder within MSP operations. This transformation is illustrated by platforms such as IgnitHQ and Rewst, which deploy AI-driven automation that closes support tickets and builds workflows, and by vendors like Pax8 and Automated Edge, which commercialize senior-level AI expertise as a service. Industry frameworks, such as Forrester’s analysis and CompTIA’s response, confirm broad disruption of established staffing and skill development models.
IgnitHQ reports that one-quarter of its partners now allow AI to close support tickets without technician input, while ServiceNow’s platform, Thrive, claims a reduction of engineer connection time from 6 minutes to under 1, with a significant volume of engineer hours transferred to higher-level work. Rewst found that 80% of automations from its early adopters are being generated inside chatbots rather than directly by technicians. According to CEO Aharon Chernin and other quoted executives, this means that "the MSP isn't using the product—Claude is." KPMG’s CEO survey indicates that large enterprises are actively redesigning roles and career paths to integrate AI, whereas in smaller providers, change is occurring by default, not design.
Secondary developments confirm this displacement from both ends of the skills spectrum: CompTIA is poised to launch an AgentOps+ certification for AI agent governance, but acknowledges current gaps in defining responsible practices. Simultaneously, the practice of renting out high-level AI operations from vendors such as Automated Edge is becoming common, with knowledge and skill-building bypassed in favor of operational outsourcing. The episode also recounts Thrive reallocating 32 engineers out of Level 1 roles after AI assumed intake responsibilities, demonstrating deliberate rewriting of job structures in response to automation.
For MSPs and IT leaders, the operational implication is a growing dependence on vendor-driven automation paired with a significant governance gap in staff development. Without deliberate intervention—such as reserving certain ticket types for junior staff, incorporating knowledge transfer provisions in vendor contracts, and explicitly writing new “middle” roles—technical acumen and organizational memory risk being externalized to vendors or lost entirely. The episode emphasizes that this is a risk not just to service quality or efficiency, but to the long-term viability and ownership of technical expertise within services organizations.
About Business of Tech: The daily MSP news and analysis podcast for managed service providers and IT services leaders. Host Dave Sobel covers AI for MSPs, MSP pricing and profitability, MSP M&A and private equity, vendor partner programs, MSP cybersecurity and liability, and MSP operations — and answers the question every story raises: Why do we care? Produced by MSP Radio.
About Business of Tech: The daily MSP news and analysis podcast for managed service providers and IT services leaders. Host Dave Sobel covers AI for MSPs, MSP pricing and profitability, MSP M&A and private equity, vendor partner programs, MSP cybersecurity and liability, and MSP operations — and answers the question every story raises: Why do we care? Produced by MSP Radio.
About Business of Tech: The daily MSP news and analysis podcast for managed service providers and IT services leaders. Host Dave Sobel covers AI for MSPs, MSP pricing and profitability, MSP M&A and private equity, vendor partner programs, MSP cybersecurity and liability, and MSP operations — and answers the question every story raises: Why do we care? Produced by MSP Radio.
About Business of Tech: The daily MSP news and analysis podcast for managed service providers and IT services leaders. Host Dave Sobel covers AI for MSPs, MSP pricing and profitability, MSP M&A and private equity, vendor partner programs, MSP cybersecurity and liability, and MSP operations — and answers the question every story raises: Why do we care? Produced by MSP Radio.
About Business of Tech: The daily MSP news and analysis podcast for managed service providers and IT services leaders. Host Dave Sobel covers AI for MSPs, MSP pricing and profitability, MSP M&A and private equity, vendor partner programs, MSP cybersecurity and liability, and MSP operations — and answers the question every story raises: Why do we care? Produced by MSP Radio.
About Business of Tech: The daily MSP news and analysis podcast for managed service providers and IT services leaders. Host Dave Sobel covers AI for MSPs, MSP pricing and profitability, MSP M&A and private equity, vendor partner programs, MSP cybersecurity and liability, and MSP operations — and answers the question every story raises: Why do we care? Produced by MSP Radio.
About Business of Tech: The daily MSP news and analysis podcast for managed service providers and IT services leaders. Host Dave Sobel covers AI for MSPs, MSP pricing and profitability, MSP M&A and private equity, vendor partner programs, MSP cybersecurity and liability, and MSP operations — and answers the question every story raises: Why do we care? Produced by MSP Radio.
About Business of Tech: The daily MSP news and analysis podcast for managed service providers and IT services leaders. Host Dave Sobel covers AI for MSPs, MSP pricing and profitability, MSP M&A and private equity, vendor partner programs, MSP cybersecurity and liability, and MSP operations — and answers the question every story raises: Why do we care? Produced by MSP Radio.
About Business of Tech: The daily MSP news and analysis podcast for managed service providers and IT services leaders. Host Dave Sobel covers AI for MSPs, MSP pricing and profitability, MSP M&A and private equity, vendor partner programs, MSP cybersecurity and liability, and MSP operations — and answers the question every story raises: Why do we care? Produced by MSP Radio.
