Business of Tech: Daily 10-Minute IT Services Insights

MSP Radio
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Feb 7, 2026 • 35min

OpenAI Equity Move in MSPs, AI Adoption Challenges, and Tier 1 Job Impact—Interview with Seth Robinson

OpenAI’s direct investment and technical involvement with Thrive Holdings, specifically through its partnership with SHIELD Technology Partners, presents a new precedent for AI’s integration into the managed service provider (MSP) space. Unlike prior private equity roll-ups or traditional organic growth, this move involves embedding OpenAI's models and engineers directly within SHIELD’s platform, an entity that has rapidly acquired and integrated nine MSPs and executed two $100 million funding rounds. The arrangement is characterized by efforts to optimize MSP operations through proprietary AI automation, raising immediate questions around operational dependency and the shifting locus of software control.According to Seth Robinson, this approach signals OpenAI’s attempt to navigate both consumer and enterprise technology markets—a dynamic seen previously in mobility—and reflects the broader tension between individual AI use cases and deeply integrated stack solutions. The initiative may accelerate operational scale, but it also introduces new operational risks by centralizing key components of service delivery and support within a single AI-driven platform, potentially affecting vendor lock-in, data governance, and continuity of MSP business models.Parallel developments highlight new vendor integration strategies among MSP-focused software providers. One example is Lexfold’s AI documentation system, which, rather than integrating directly with core PSA and RMM tools, utilizes intermediary platforms such as Scalepad and Liongard for data access. Seth Robinson emphasizes that these alternative integration points may alter an MSP’s center of operational gravity and complexity management, underscoring the need to assess not just functional outcomes but also system dependencies and brittleness introduced by new integration paths.For MSPs and IT leaders, these trends underscore the necessity of rigorous due diligence in vendor relationships, clarity on operational dependencies, and attention to the long-term implications of AI-enabled automation. Management—not elimination—of complexity remains central, with the risk of oversimplification leading to commoditization and loss of differentiation. Moreover, advances in AI should prompt greater scrutiny about talent pipelines, upskilling strategies, and the potential risks of eroding early-career roles, which may impact long-term service quality and resilience. Careful evaluation of integration points, data integrity, and operational control is recommended to mitigate the practical and organizational risks emerging from these developments.  💼 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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Feb 6, 2026 • 15min

AI Fails to Deliver ROI for CEOs While Bot Traffic Surges and CISA Targets End-of-Life Devices

A PwC survey of over 4,400 CEOs across 105 countries found that 56% report artificial intelligence has not delivered meaningful revenue growth or cost savings in the past year. Only one in eight organizations saw both benefits. The core issue, as highlighted by Dave Sobel, lies in poor integration—largely due to data quality challenges and legacy systems—leaving many businesses stuck in what PwC terms “experimentation purgatory.” Despite significant investment, AI infrastructure is often failing to produce measurable returns.This lack of operational discipline is mirrored by the rising incident of AI bots, which now account for 1 out of every 50 website visits, a sixfold increase from earlier reports. AI is successfully extracting value from enterprise infrastructure through sophisticated scraping, as companies pay for tools that return little and simultaneously fund infrastructure serving AI bots. The operational cost and exposure from bot traffic and ineffective AI tool adoption highlight the disconnect between hype and practical benefit.Adjacent stories expand on the governance gap and evolving expectations around risk. The U.S. and China declined to sign a non-binding declaration on military AI, underlining global regulatory fragmentation. In contrast, the Cybersecurity and Infrastructure Security Agency (CISA) issued a binding directive for federal civilian agencies to remove unsupported devices within a year, signaling substantial operational risk from end-of-life technology. These regulatory movements are expected to drive similar risk accountability into the private sector, primarily through insurance requirements.For MSPs and IT service providers, the takeaway is not to chase AI-powered offerings but to prioritize readiness, control, and cost accountability. Vendor partner programs (Cisco and 1Password) reward lifecycle management and customer retention, not AI sales. The practical competitive advantage is operational honesty—delivering realistic assessments, proactive client interactions, and transparent guidance. Automation should fund genuine client relationship activities, not replace them. The focus should remain on safeguarding operational integrity, controlling technology risk, and building customer success capability.Four things to know today:00:00 PwC Survey Finds Most Business Leaders Still Waiting for AI Payoff05:00 Federal Agencies Ordered to Eliminate End-of-Life Devices Over Cyber Threats08:06 Cisco and 1Password Launch Partner Programs Focused on Customer Success10:52 Harvard Business Review Says Human Touch Remains Critical Advantage Over AIThis is the Business of Tech.   Supported by:  Small Biz Thought Community   💼 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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Feb 5, 2026 • 14min

OpenAI Enters Ads and Consulting; AI Deployment Shifts Liability and Costs for MSPs

The primary development centers on the shift toward smaller, task-specific AI models within enterprises and how this shift is primarily about transferring liability from AI vendors to operators. Dave Sobel notes that while narrower AI models are being marketed as safer and easier to govern, the reality is that they shift the burden of control, oversight, and risk directly onto the organizations deploying them. Hidden costs—particularly those related to data infrastructure, compliance, and ongoing governance—are substantial, often eclipsing the initial AI investment.Supporting data includes findings from a Salesforce survey indicating that CIOs allocate a median of 20% of their budgets to data and infrastructure management versus 5% to AI itself. Dave Sobel stresses that the real cost of an AI project can be significantly higher than client expectations, pointing out a 4:1 spending ratio between supporting infrastructure and the AI technology. This underscores the risk for MSPs who may fail to price in the operational and governance requirements appropriately, exposing themselves to financial and compliance liabilities.Adjacent stories address OpenAI’s strategic expansion into advertising and direct consulting, marking a move from pure technology platform to direct competitor for services revenue. OpenAI is creating an Ads Integrity Team to manage advertiser verification and reduce scam risk but acknowledges the challenges of maintaining effective controls at scale. In parallel, OpenAI is embedding engineers within client operations—mirroring other internal AI initiatives such as those at Shield and Entegris—and reinforcing a market divide. MSPs who build such capabilities internally capture margin, while others face lasting margin compression as purchasers of external solutions.The implications for MSPs and IT leaders are direct. Success depends less on which AI model is selected and more on the provider’s ability to establish rigorous governance, liability management, and ongoing operational control. The market is bifurcating: service providers who can build in-house AI platforms or attract strategic investment will retain efficiency as margin, while those relegated to purchasing third-party tools risk further erosion of profitability and competitive position. The decision to build or buy is becoming a business model risk, not just a procurement choice, and the opportunity to address it is narrowing.Three things to know today:00:00 Firms Shift to Task-Specific AI Models Amid Governance, Liability Concerns 04:35 OpenAI Launches Ads Integrity Team, Hires Hundreds as Services Push Begins08:34 MSP Market Splits as Integris, Shield Build Internal AI, Others Buy ToolsThis is the Business of Tech.   Supported by:  IT Service Provider University   💼 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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Feb 4, 2026 • 15min

CISA Ransomware Intelligence Lag, Azure TLS Cutoff, and Risks from AI Skills Marketplaces

The episode focuses on current security risks and limitations in industry intelligence, highlighting that CISA’s Known Exploited Vulnerabilities (KEV) catalog often lags by years in tagging vulnerabilities exploited by ransomware. One cited vulnerability sat in the catalog for 1,353 days before being flagged as ransomware-exploited, illustrating a significant delay in actionable intelligence. This gap raises concerns for MSPs whose patching priorities rely on outdated catalogs, potentially leading to a misalignment between compliance activities and actual threat vectors.Supporting this, Dave Sobel underscores how evolving threat models frequently bypass traditional vulnerability management. The recent compromise of OpenClaw’s skills marketplace, with a 12% malicious rate in submitted skills and basic post-facto reporting mechanisms, demonstrates that credential theft and malicious automation now present risks outside standard patch management. The core operational challenge for MSPs is not just software vulnerability but the governance of AI-enabled tools and uncontrolled marketplaces that can expose clients to breaches.Further contextualizing risk and automation, vendor launches include Lexful’s AI-native documentation for MSPs and Cavelo Flash’s agentless assessment tool. These offerings promise streamlined documentation and rapid risk assessment, but Dave Sobel notes their reliance on beta features, integration dependencies, and non-definitive compliance positions. Additionally, DocuSign’s release of AI-generated contract summaries raises questions about liability, as inaccurate summaries can mislead signers, and responsibility defaults to the end user rather than the vendor.The primary implication for MSPs and technology leaders is the need to inventory all AI-powered tools with access to client environments, actively govern marketplace adoption, and critically evaluate automation claims. Compliance-focused patching is no longer sufficient; operational oversight must prioritize credential management and identity governance over checklist-based approaches. Caution is advised before rapid migration to beta solutions or locking into long-term contracts, as both reduce flexibility and increase exposure to emerging, non-traditional attack surfaces.Three things to know today00:00 CISA's Ransomware Tags Arrive Years Late While AI Tools Steal Credentials Now05:53 IT Glue Founder Launches AI Documentation Platform Lexful for MSPs at Right of Boom09:52 Cavelo and DocuSign Launch AI Tools That Automate Assessments and Contract ReviewsThis is the Business of Tech.   Supported by: Small Biz Thoughts Community  💼 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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Feb 3, 2026 • 15min

AI Adoption Outpaces Trust, Microsoft Sets NTLM Deadline, Right to Repair Expands

The episode centers on the expanding adoption of artificial intelligence (AI) tools among workers alongside a notable decline in confidence. According to a Manpower Group study cited by Dave Sobel, AI confidence among workers decreased by 18% even as usage increased by 13% over the past year. This divergence highlights a governance and operational gap for MSPs, as enterprise clients confront both the potential and the risks of AI-enabled solutions, facing unresolved issues of output reliability, oversight, and liability when missteps occur.Supporting this trend, findings from the Stanford University Institute for Human-Centered Artificial Intelligence indicate that nearly 30% of AI chatbot users encountered harmful suggestions. While these statistics lack detailed breakdowns – such as which platforms or definitions of “harmful” – they shape widespread client perceptions and intensify scrutiny of AI guidance provided by IT service providers. Meanwhile, enterprise vendors like Zendesk report improved satisfaction rates from automated resolutions but emphasize the costly need to overhaul workflows and data management to effectively harness AI benefits.Additional focus is given to Microsoft’s scheduled deprecation of the NTLM authentication protocol, replaced by newer mechanisms that are not yet fully deployed or reliable. Dave Sobel notes that legacy systems depending on NTLM present tangible operational and legal risks for MSPs, as clients may face authentication failures or re-enable insecure protocols unless thoroughly audited. Elsewhere, the "right to repair" movement is gaining ground as the Environmental Protection Agency affirms farmers’ rights to repair their own equipment, with broader implications for IT hardware access and vendor-dependent service models.The confluence of these developments underscores the importance for MSPs and IT leaders to shift focus from product access and resale toward risk governance, lifecycle planning, and documenting client decisions—especially in AI, authentication methodologies, and hardware maintenance. Mitigating liability, clarifying accountability with clients, and tracking evolving vendor and regulatory actions are essential to maintain relevance and safeguard operations as service and product access models change. Three things to know today00:00 Workers Use More AI But Trust It Less, Creating New Service Risks03:44 Microsoft Plans NTLM Phase-Out Despite Unfinished Kerberos Replacement Technology06:32 Google, Adobe Launch AI Subscriptions While OpenAI Retires GPT-4o Next Month10:52 EPA Ruling Lets Farmers Repair Equipment, Pressures Tech Right-to-Repair LawsThis is the Business of Tech.   Supported by:   💼 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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Feb 2, 2026 • 16min

Small Business Optimism, Trillion-Dollar IT Services Projections, and Unmanaged AI Agent Risks

The episode centers on the structural shift in managed services driven by the adoption of autonomous AI agents and the resulting accountability challenges for IT service providers. According to Dave Sobel, 22% of employees in Token Security’s surveyed organizations are independently running AI agents such as OpenClaw with terminal and browser command capabilities, without formal IT oversight. This widespread shadow automation creates significant operational and security exposure, indicating unsanctioned user demand for advanced automation that IT has not provided. The core risk is not simply unauthorized technology use, but ineffective governance and lack of visibility into automation processes that can impact both client safety and provider liability.Context provided throughout the episode points to a disconnect between optimistic business sentiment and actionable IT spending. While the NFIB index reflects rising small business optimism and increased capital access, most technology-related investments appear to have already been made in prior periods. Only 19% of small businesses plan further equipment investments, suggesting limited near-term demand. Meanwhile, SBA workforce reductions signal longer loan processing times, affecting clients who depend on SBA-backed funding for technology projects—a concrete operational delay for MSPs whose services are linked to client capital expenditure timelines.Additional discussion focuses on evolving industry economics, notably a projected increase in the North American IT services market to $1.09 trillion by 2033, as reported by Research and Markets. However, Dave Sobel emphasizes that the majority of this growth is captured by hyperscalers and large integrators, not regional MSPs. Cooling wage inflation, detailed by Service Leadership, may present temporary margin opportunities but also introduces risk if MSPs respond with indiscriminate hiring rather than automation or upskilling strategies. The Shield Technology Partners investment, involving OpenAI’s embedded research in IT operations, signals rapid automation of rules-based workflows and reiterates the urgency of addressing task displacement and margin compression.For MSPs and IT service leaders, the practical takeaway is clear: unmanaged, employee-driven AI automation presents both risk exposure and a mapping of unmet service demand. Blocking shadow agents is a reactive measure—long-term resilience depends on developing agent governance frameworks, including permissioning, audit, and incident response protocols. With shrinking margins and increasing automation, providers must reevaluate operational models, prioritize revenue-per-employee, and focus on delivering accountable, sanctioned automation services rather than competing on basic labor cost or commodity support.Four things to know today00:00  NFIB Index Hits 99.5 as 64% Face Inflation and SBA Cuts Half Its Workforce04:44  IT Services Market Growth to $1.09T Coincides With Declining Wage Inflation08:01  Shield Secures Second $100M From OpenAI-Backed Thrive Holdings for AI Operations Platform11:21  Token Security Reports 22% Shadow IT Adoption of OpenClawThis is the Business of Tech.   Supported by: MSP Radio - Internal Ad   💼 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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Feb 2, 2026 • 12min

Mike Riggs Joins Empath: Moving from Founder-Led Vision to Formal Product Governance

The appointment of Mike Riggs as Chief Product Officer at Empath signifies the company's transition from founder-led intuition to formalized product governance. According to Wes Spencer, Empath reached over 500 MSP customers and now requires more disciplined processes as it moves from early-stage, high-velocity development to operational maturity. Mike Riggs described his role as systematizing elements that were previously managed informally—covering areas from design to engineering—and explicitly stated the intent to strengthen operational accountability for both the platform and its customers.This structural change follows recognition by the founders that their limited technical background required complementary leadership to scale effectively. Advisors highlighted that, while growth and partner engagement met expectations, scaling Empath’s platform now demands greater rigor and repeatable operational practices. Empath’s platform has evolved from being a convenience service to an operational dependency, with MSPs using it for training, team accountability, and embedded workflows. Mike Riggs emphasized the importance of refining user experience, onboarding processes, and support mechanisms as MSP reliance grows.A central theme discussed is the shift in Empath’s product category—from a basic learning management tool toward a broader learning, development, and accountability platform for MSPs. Features such as notification systems and visibility into required actions move the platform beyond content delivery into proactive management of personnel performance and compliance. This evolution brings Empath closer to intersecting with HR, policy, and managerial oversight, compelling the company to balance user engagement features with the need for reliable, auditable, and controlled change management.For MSPs and IT service providers, Empath’s shift has operational implications and risk factors. Increasing dependency on a single platform heightens the significance of product stability, disciplined rollout of new features, and clarity of governance. As platforms like Empath become more embedded in day-to-day operations, service providers must reassess processes for vendor risk management, accountability, and internal policy alignment. The move described is not an indicator of problems but of maturation—a transition that typically introduces both new safeguards and greater operational complexity.  💼 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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Feb 1, 2026 • 21min

Navigating AI Adoption and Governance for Small Businesses: Interview with David Espindola

The episode centers on practical approaches for Managed Service Providers (MSPs) and IT leaders assessing artificial intelligence (AI) adoption, with David Espindola detailing the crucial distinction between “maker,” “shaper,” and “taker” strategies. David Espindola emphasizes that organizations must intentionally decide their role in AI development and use—whether building proprietary systems, shaping solutions atop existing models, or simply consuming pre-built capabilities. This decision, he notes, is foundational for aligning risk tolerance, investment, and technical capacity with business goals, especially given the rapid pace and inherent uncertainty in AI’s evolution.Supporting this framework, David Espindola references insights from a Small Business Administration project, which found that most small businesses are struggling to define applicable use cases for AI and tend toward risk-avoidant stances despite external pressures to adopt the technology. He stresses that AI implementation should not be a solution in search of a problem; rather, an organization’s readiness, risk, investment capability, and specific industry context must determine its approach. Key recommendations include conducting readiness assessments, appointing internal AI champions, and starting with small, low-risk pilot projects to build internal understanding and governance processes before scaling.The discussion broadens to ethical and governance considerations, with both David Espindola and the host cautioning that responsible AI adoption is a business necessity rather than a compliance checkbox. They advocate for formal employee training, the establishment of clear usage policies, and strict controls over tool access to mitigate risks such as data leakage, hallucinated outputs, and misaligned communications. The emphasis is on building practical safeguards rather than pursuing AI for its own sake, reflecting a pragmatic, risk-managed approach tailored to each organization’s context.For MSPs and IT service providers, the practical takeaways are clear: pursuing AI adoption requires a methodical, risk-aware strategy focused on business relevance, operational governance, and targeted experimentation. The harms of rushed deployments, poor change management, or lack of internal education are underscored, with the implication that long-term value and reduced exposure are found in deliberate, well-governed adoption efforts. Readiness assessments, pilot programs, and robust policy frameworks emerge as the primary enablers of sustainable outcomes in this rapidly evolving landscape.  💼 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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Jan 31, 2026 • 49min

MSP Rollups, AI Investment, and Industry Consolidation Trends With Rich Freeman and Jessica Davis

The current wave of managed service provider (MSP) consolidation and rollups is being distinguished by the integration of advanced artificial intelligence (AI) expertise, particularly among entities such as SHIELD and Titan. As discussed by Rich Freeman and Jessica Davis, these newer rollups are acquiring not just MSPs but also Silicon Valley AI talent and developing proprietary AI-driven services, a marked shift from earlier private equity-backed consolidators. Rich Freeman highlighted SHIELD’s recent leadership hires from Palantir and direct collaboration agreements with OpenAI, signaling an intent to embed AI at the operational core rather than simply as a tool for optimization.The structure and access to data is central to these developments. As Rich Freeman elaborated, large rollups possess a scale-driven “AI flywheel” advantage: broader customer bases provide larger datasets, which in turn drive better AI performance, operational efficiency, and profitability. This concentration creates risks for smaller MSPs that lack equivalent data pools and resources for internal AI development. Jessica Davis noted that while tool vendors and platform companies such as ConnectWise and Kaseya are enhancing AI within their offerings, their efforts are not yet matching the focused investments of the largest rollups, and are simultaneously being pressured to accelerate innovation.Commercial and operational pressures are increasing throughout the MSP ecosystem. Jessica Davis cited indications of slowing managed services revenue growth projections (potentially below 10%), alongside potential cost-cutting or workforce reductions within large rollups as private equity owners seek AI-driven returns. Divergent rollup models are also emerging—with distinctions between platform centralization (e.g., retiring acquired brands) and decentralized, founder-friendly approaches (e.g., preserving local brands and founder involvement). Decisions around acquisition, platform engagement, and specialization are increasingly nuanced as founders and owners evaluate their options under new market dynamics.For MSPs and IT service leaders, these trends necessitate a measured response. The competitive risk posed by the AI-fueled scale of consolidated rollups underscores the importance of specialization, operational focus, and alignment with platform partners committed to democratizing AI resources. Community collaboration, best-practice sharing, and strategic use of vendor tools are positioned as potential mitigants to the structural disadvantages faced by smaller organizations. Governance, due diligence, and clear assessment of vendor or acquirer incentives should be prioritized, especially as service models and influencer dynamics continue to fragment. Remaining adaptable, resource-aware, and critically informed about the changing power landscape will be vital for sustainable operations.  💼 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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Jan 30, 2026 • 12min

Moltbot’s Security Flaws, Apple’s Supply Challenges, and Windows 11 Trust Issues Analyzed

The emergence of Moltbot, an open source AI agent designed to operate across various messaging platforms and automate tasks through local device execution, is creating new risk vectors for MSPs and IT providers. Functioning with admin-level access and connecting to services like OpenAI and Google, Moltbot’s deployment has raised direct concerns around authority delegation without sufficient governance. Security researchers identified hundreds of exposed Moltbot instances, often due to misconfiguration, increasing the possibility of breaches and unauthorized data access. The episode underscores that these agents, treated as productivity tools, actually represent operational infrastructure capable of independent action, with potential impacts on client trust and regulatory liability.Expert sources cited in the discussion, including Cisco and Hudson Rock, have labeled Moltbot a security risk due to its storage of sensitive information in plain text and broad access permissions. The narrative warns that vendors and providers may underestimate the risks by normalizing deployment before establishing proper controls. Once these agents are embedded into workflows, reversing their use becomes difficult due to client reliance on perceived efficiency. The lack of mature governance frameworks, as shown by studies from Drexel University, means that many organizations lack even basic oversight of these autonomous agents.Adjacent industry developments highlight additional layers of operational complexity. Apple posted a 16% revenue increase, led by iPhone demand, and acquired Q AI to deepen its ambient automation capabilities, while shifting defaults that providers cannot easily influence or control. Simultaneously, the Linux community’s succession planning and Microsoft’s ongoing struggles with Windows 11 reliability further demonstrate systemic issues around authority, trust, and transparency in technology ecosystems.The episode’s analysis signals clear expectations for MSPs and technology leaders: explicit approval protocols for AI agents are necessary, akin to traditional admin controls. Providers must proactively define governance boundaries, anticipate non-billable labor resulting from automation failures, and assess vendor behavior in terms of roadmap rigidity and escalation pathways. Teaching clients about authority in automated environments, not just managing installations, will reduce exposure and clarify accountability as agentic technologies become standard.Three things to know today00:00 Moltbot’s Rise Highlights How AI Agents Are Becoming High-Risk Operators Without Governance03:49 Record iPhone Sales and a $2 Billion AI Acquisition Signal Apple’s Long-Term Control Strategy06:04 Leadership Succession, Software Trust, and AI Agents Reveal a Shared Governance ProblemThis is the Business of Tech.   Supported by:  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/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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