SUPPORTER CONTENT

Support independent content from MSP Radio

$12.00/month or $99.99/year

Business of Tech: Daily 10-Minute IT Services Insights

MSP Radio

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.

  1. Managed Services and AI Integration: Interview with Brian Harmison on Corsica Technologies’ Strategy

    15H AGO

    Managed Services and AI Integration: Interview with Brian Harmison on Corsica Technologies’ Strategy

    Corsica Technologies’ reported 105% year-over-year growth in managed services bookings stands out as the primary development, indicating heightened demand for flexible service models among businesses with existing IT functions. According to Brian Harmison, CEO of Corsica, this growth is attributed to the company’s focus on operational integration, automation, and data-centric managed services that supplement, rather than replace, in-house IT capabilities. The significance for MSPs is not the expansion itself, but the operational choices that enable sustained trust and differentiated engagement in a competitive landscape. Supporting details clarify Corsica’s operational strategy: instead of automating or deploying AI indiscriminately, Harmison emphasizes that automation and AI are only effective atop an already “operationally excellent” MSP framework. Practical deployments cited include user onboarding/offboarding workflows, which demand both internal process clarity and integration with client HR systems. The company positions data integration and workflow consulting as integral to MSP-client relationships, not as add-on projects. Corsica’s contracts reportedly reduce friction and avoid asset-tracking or incremental billing, seeking to foster longer-term trust over short-term revenue optimization.  The episode also addresses the implications of Corsica’s acquisition of Accountability IT. Harmison cites alignment in operating models and targeted capabilities—especially in Microsoft security and AI expertise—as central to the integration’s value, rather than generic synergies. He notes that continuity of client relationships and careful preservation of existing service structures were prioritized in the first 90 days, even at the expense of speed, to mitigate operational risk and maintain client trust. The discussion highlights the risk tradeoffs between scaling for broader capability and maintaining agility for specialized client needs. For MSPs and IT leaders, the takeaway is to focus on risk reduction through operational excellence and trusted client relationships. Embracing automation and AI is not a universal solution; process maturity and readiness in both the provider and customer are preconditions for any meaningful implementation. Acquisitions require careful cultural and operational integration, with an emphasis on continuity and incremental capability, rather than immediate consolidation or scale. The episode frames operational clarity and trust—not rapid expansion or technology adoption—as critical determinants of long-term viability and resilience in managed services.   💼 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/28908079 YouTube: https://youtube.com/mspradio Bluesky: https://bsky.app/profile/businessof.tech Instagram: https://www.instagram.com/mspradio TikTok: https://www.tiktok.com/@businessoftech Facebook: 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.

    23 min
  2. Deploying Agentic AI at Scale: Infrastructure, Reliability, and Risk with Ran Aroussi

    1D AGO

    Deploying Agentic AI at Scale: Infrastructure, Reliability, and Risk with Ran Aroussi

    Agentic AI is being deployed as production infrastructure in enterprise settings, but prevailing frameworks remain unreliable for mission-critical operations. Dave Sobel and Ron Aroussi from Muxie underscored that while AI agents are functional—especially in non-deterministic contexts like customer support—expectations of deterministic, workflow-based reliability are not met. The move from demonstration agents to production-scale tools brings heightened attention to issues of reliability, observability, and especially risk of vendor lock-in for Managed Service Providers (MSPs) and their clients. Operational deployment of AI agents currently gravitates toward roles with minimal operational risk, such as customer-facing chatbots or internal chief-of-staff assistants. Aroussi explained that while such agents can automate initial support tiers and internal daily briefings, their unpredictability and potential for error limit their use in processes demanding strict oversight and accountability. He identified two core use cases—external (customer support) and internal (personalized information management)—explicitly noting that agents are best positioned to augment rather than fully automate complex workflows at this stage. A critical risk for MSPs lies in attempting to retrofit existing software frameworks to support agents, which introduces integration complexity and increases the likelihood of operational failures. Purpose-built infrastructure for agentic AI offers better alignment between AI capabilities and production requirements, with Aroussi citing drastically reduced hallucination rates and improved oversight when using native tools. Open source is identified as a foundational element for AI development, but it incurs its own risks, particularly around third-party code quality and the long-term sustainability of community-driven projects. The practical implication for MSPs and IT service providers is clear: a cautious, incremental adoption approach focused on low-risk use cases, coupled with rigorous controls on agent permissions and robust audit trails, is essential. Decision-makers should avoid assuming agents operate with the reliability or accountability of traditional software, prioritize operational transparency, and ensure that responsibilities for agent actions are clearly defined and enforced at the implementation level. Vendor lock-in and software provenance remain significant governance concerns as agentic AI moves from experiment to infrastructure.   💼 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/28908079 YouTube: https://youtube.com/mspradio Bluesky: https://bsky.app/profile/businessof.tech Instagram: https://www.instagram.com/mspradio TikTok: https://www.tiktok.com/@businessoftech Facebook: 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.

    23 min
  3. Generative AI Drives Tech Spend Shift as Channel Margins Face Pressure

    4D AGO

    Generative AI Drives Tech Spend Shift as Channel Margins Face Pressure

    Global technology spending is projected to reach $5.6 trillion by 2026, with nearly two-thirds of this investment directed toward software and computer equipment, particularly servers, according to Forrester. Generative AI is cited as a primary driver of this increase, shifting the balance of power toward cloud providers such as AWS and Azure. This escalation has implications for operational margins and the position of IT service providers, as businesses increasingly migrate complex workloads to cloud infrastructure ecosystems. Supporting data shows a disconnect between tech employment trends and hiring activity. In January 2026, technology companies cut approximately 20,155 jobs, mainly in telecommunications, while job postings for tech positions rose by 13% compared to the prior month, based on CompTIA analysis. Dave Sobel interprets this as a shift away from permanent IT headcount to project-based, AI-focused engagements. This development places pressure on service providers, who must adapt to buyers reallocating spend from traditional staffing models to short-term, outcome-oriented contracts. Adjacent discussion covered two press releases: VirtuaCare launched a support offering for Windows-based MSPs needing Apple expertise, delivering an externally verifiable, Apple-certified service. In contrast, Miso announced a roadmap for an autonomous AI L1 technician but did not substantiate claims with deliverables or customer data. Dave Sobel emphasized the need for MSPs to demand piloting, outcome metrics, and auditable product maturity, warning against reliance on unproven AI solutions and highlighting the risk of outsourcing as only a temporary solution. The core implication for MSPs and IT providers is a need for tactical negotiation and operational risk management. Dave Sobel recommends using AI first to reduce internal labor costs before introducing it as a client offering, prioritizing outcome-based pricing and adjusting contracts to retain value from efficiency gains. Providers should avoid becoming displaced labor, rigorously test new technologies before adoption, and remain vigilant regarding vendor claims. The emphasis remains on capturing and defending margins through accountable operations and contract governance rather than chasing speculative innovation. Three things to know today 00:00 Tech Spending Hits $5.6T but MSPs Face Margin Squeeze Without AI Pricing Reset 05:31 VirtuaCare Ships Apple Support; Mizo Announces Roadmap—One's Testable Today 08:17 MSPs Must Capture AI Efficiency Value or Face Margin Compression This is the Business of Tech.    Supported by:  Small Biz Thought Community Check out Killing IT   💼 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/28908079 YouTube: https://youtube.com/mspradio Bluesky: https://bsky.app/profile/businessof.tech Instagram: https://www.instagram.com/mspradio TikTok: https://www.tiktok.com/@businessoftech Facebook: 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.

    15 min
  4. AI Operational Risk, Sovereign Cloud Mandates, and MSP Compliance Liabilities Examined

    5D AGO

    AI Operational Risk, Sovereign Cloud Mandates, and MSP Compliance Liabilities Examined

    Mid-market organizations are transitioning from pilot projects to operationalizing generative AI and agentic workflows, according to a TechEYE article and Tech Isle survey cited by Dave Sobel. This shift centers on outcome-driven automation but exposes providers to new liability concerns, mainly due to fragmented, unreliable data and shadow AI usage—employees employing unauthorized tools outside official controls. The primary risk is that MSPs may be blamed for incidents where contract boundaries and technical controls do not cover browser-based generative AI use, making forensic evidence and documented enforcement essential for defending accountability. Supporting data from Tech Isle found that over 5,000 companies are pursuing structured approaches to AI-enabled growth, but face persistent issues in data trust, governance, and user fatigue. Additionally, European investment in sovereign cloud infrastructure is projected to triple between 2025 and 2027, driven by regulatory demands and concerns about U.S. data sovereignty. MSPs managing split architectures—sovereign providers for regulated data and hyperscalers for everything else—encounter API mismatches, operational complexity, and margin pressure. The recommendation is to standardize policy enforcement, identity management, and residency mapping while prioritizing audit-ready reporting and exception handling. AI-driven cyberattacks have increased, with reports from Level Blue and Check Point Research highlighting a surge in both attack volume and sophistication. Only 53% of CISOs feel prepared for AI threats, despite 45% expecting to be impacted within a year. Browser-based generative AI use introduces visibility gaps, raising the risk of negligence claims when service providers cannot demonstrate governance or forensic readiness. Reauthorization of the Cybersecurity Information Sharing Act (CISA) underscores that voluntary data sharing is inadequate, with CIRCA now requiring mandatory 72-hour incident reporting for critical infrastructure. The key takeaways for MSPs and IT leaders are to proactively define AI coverage and governance in contracts, enforce acceptable use policies, and instrument monitoring to close visibility gaps. Providers who can deliver forensic-grade telemetry, managed compliance programs, and operational readiness for incident reporting will be better positioned to defend against penalties, retain higher-value accounts, and offer meaningful differentiation. These structural challenges—fragmented control planes, increased compliance costs, and permanent risk friction—necessitate a strategic shift toward governance-led service models. Three things to know today 00:00 Midmarket Shifts to Agentic AI as Europe Triples Sovereign Cloud Spending by 2027 06:08 Most Security Chiefs Say They're Not Ready for AI-Powered Cyberattacks Coming This Year 09:46 CISA 2015 Reauthorized Through 2026; CIRCIA Mandates Expose Voluntary Sharing Failure   This is the Business of Tech.    Supported by:  TimeZest   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/28908079 YouTube: https://youtube.com/mspradio Bluesky: https://bsky.app/profile/businessof.tech Instagram: https://www.instagram.com/mspradio TikTok: https://www.tiktok.com/@businessoftech Facebook: 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.

    14 min
  5. AI Raises Workloads and Burnout: HBR Study, Medical Risk, and New Governance for MSPs

    6D AGO

    AI Raises Workloads and Burnout: HBR Study, Medical Risk, and New Governance for MSPs

    Artificial intelligence (AI) is intensifying workloads rather than alleviating them, leading to increased burnout and declining decision quality, according to findings published in the Harvard Business Review and cited by Dave Sobel. The episode underscores that AI lowers the cost of producing outputs such as drafts and summaries but raises throughput targets and introduces new verification burdens. Economic gains from AI remain concentrated where capital and skilled labor already exist, while negative impacts—like displacement and wage pressure—are felt locally. These dynamics highlight the need for robust governance, particularly for managed service providers (MSPs) who deploy AI solutions. Supporting studies referenced include the International AI Safety Report, which details heightened uncertainty around AI development and its risks, as well as research from Oxford documenting the unreliability of AI chatbots in real-world medical decision-making. Experts warn that rapid automation without corresponding improvements in control systems creates structural constraints, making traditional software governance frameworks inadequate for unpredictable AI behaviors. Without proactive measures, these gaps risk exacerbating economic inequality and liability in regulated environments. Additional developments include OpenAI’s release of upgraded agent features—such as GPT-5.2, improved context retention, managed shell containers, and a new skills standard—presented as operational enhancements but raising concerns about black-box context handling, auditability, and dependency risk. T-Mobile’s AI-powered live translation service offers greater convenience but eliminates audit trails, shifting compliance risk to customers and prohibiting independent verification. Quark Cyber’s launch of an internal cyber risk score introduces further complexity, as the scoring methodology is embedded within a financial product structure and lacks transparent validation. For MSPs and IT service leaders, the key takeaway is to treat new AI features and risk metrics as tools with significant tradeoffs. AI deployments should focus on governance layers that include workload caps, quality gates, and measurable outcomes rather than simply accelerating productivity. New features should be used for low-stakes workflows and carefully avoided in high-risk or regulated contexts unless auditable controls and deterministic checkpoints are established. Vendor-managed risk scores and warranties require independent validation before being positioned as client-facing truth standards. Four things to know today 00:00 Harvard, Oxford Studies Find AI Raises Workload, Delivers Inadequate Medical Advice 05:01 OpenAI Updates Deep Research and Adds New Agent Runtime Capabilities 07:33 T-Mobile Tests Real-Time Call Translation Built Into Its Network 09:17 Cork Cyber Rolls Out New Risk Score for Managed Service Providers This is the Business of Tech.    Supported by:  ScalePad  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/28908079 YouTube: https://youtube.com/mspradio Bluesky: https://bsky.app/profile/businessof.tech Instagram: https://www.instagram.com/mspradio TikTok: https://www.tiktok.com/@businessoftech Facebook: 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.

    14 min
  6. OpenAI Introduces ChatGPT Ads and Enterprise Agent Platform; Anthropic Releases Opus 4.6

    FEB 10

    OpenAI Introduces ChatGPT Ads and Enterprise Agent Platform; Anthropic Releases Opus 4.6

    OpenAI’s twin initiatives to monetize ChatGPT’s free tier through ads and launch the Frontier enterprise agent platform represent a shift in the AI provider’s business model, with substantial implications for compliance and operational governance. Free and low-cost ChatGPT users will now see sponsored links unless they opt to reduce daily usage; only customers paying $20 or more per month retain an ad-free experience. OpenAI is concurrently marketing Frontier to enterprise clients such as HP, Intuit, and Uber, offering AI agent orchestration and deploying a team of consultants to support custom AI applications. The company projects enterprise revenue will constitute 50% of its income by year-end, up from 40% the prior month. Operating in both the consumer funnel and the enterprise layer, OpenAI combines top-of-funnel data monetization with vertical integration of services. The ad-supported free tier raises compliance concerns, as user interactions become subject to additional data collection and monetization. For organizations, this means enforcement decisions around whether and how employees may use free AI tools in regulated or sensitive environments. The more consequential development, however, is the introduction of enterprise agent orchestration through Frontier, where questions persist regarding liability, governance, production stability, and how organizations are protected from errors committed by autonomous agents. Related market movements include Anthropic’s release of Claude Opus 4.6—which enables multi-agent collaboration with context windows up to 1 million tokens—and Microsoft’s planned shift for Windows to a signed-by-default trust model. Anthropic’s enhancements to agent functionality remain constrained by key gaps, such as conflict arbitration mechanisms, rollback procedures, and documented cost models, and the expanded context remains limited to beta testers. Microsoft’s strategy to enforce signed apps by default mirrors iOS’s approach to application trust, but its operational viability depends on how override mechanisms are managed by both users and IT administrators. Additional developments in backup, asset management, and AI governance (as seen with NinjaOne, JumpCloud, and Zoom) reflect a general trend towards increased integration and platform consolidation, though with ongoing gaps in security and compliance as AI adoption accelerates. The practical takeaway for MSPs and IT service leaders is the need to re-evaluate policies around free AI tool usage, invest in governance and auditability for enterprise AI, and prepare operational systems for stricter software trust and exception management requirements. Structural changes in software security and AI orchestration are transferring costs and risks from incident response to ongoing policy enforcement and exception handling. Those offering AI services should prioritize model-agnostic governance and avoid reliance on a single vendor’s automation layer, as vertical integration by platform providers is reducing the defensibility of narrow service offerings. Four things to know today: 00:00 OpenAI Adds Ads to Free ChatGPT; Launches Frontier Platform for Enterprise Agents 04:07 Anthropic Ships Opus 4.6 Agent Teams; Model Found 500 Zero-Days in Testing 06:43 Microsoft Announces Signed-App-Only Mode for Windows 11; Phased Rollout Planned 10:19 NinjaOne Adds Asset Management; Zoom Launches AI Workspace Tool; JumpCloud Opens VC Arm This is the Business of Tech.    Supported by:  CometBackup  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/28908079 YouTube: https://youtube.com/mspradio Bluesky: https://bsky.app/profile/businessof.tech Instagram: https://www.instagram.com/mspradio TikTok: https://www.tiktok.com/@businessoftech Facebook: 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.

    15 min
  7. IT Spending Rises but Channel Share Falls; AI Arms Race and Shrinking Jobs Impact MSPs

    FEB 9

    IT Spending Rises but Channel Share Falls; AI Arms Race and Shrinking Jobs Impact MSPs

    IT spending continues to expand, with North America projected to lead a 12.6% increase to $2.6 trillion, primarily due to hyperscaler investments in AI infrastructure. However, the proportion of technology spending funneled through channel partners is declining, now at 61% compared to over 70% four years ago, according to a survey by Omnia. This shift signals that while the market is growing, traditional margin and resale opportunities for MSPs are narrowing as vendors redirect a larger share of revenue direct while still relying on partners for implementation, support, and customer operations. Data from Salesforce underscores a near-universal trend toward partner involvement in sales, with 94% of surveyed global salespeople leveraging partners to close deals and 90% using tools to manage relationships. Despite this, Dave Sobel clarifies the distinction between involvement and compensation, highlighting that partner influence on deals does not guarantee economic participation at previous levels. These dynamics reinforce that MSPs must adapt to a reality where their role in the value chain is being separated into influence and execution, with the middle tier facing increasing pressure. Additional analysis draws attention to labor market changes and technology commoditization. U.S. job openings have fallen to their lowest point in over five years, undermining MSP growth strategies dependent on seat expansion. Simultaneously, the AI market is fragmenting at the application layer—with Google's Gemini app, Grok, and OpenAI's ChatGPT shifting market shares rapidly—while hyperscalers like Alphabet (Google) commit unprecedented capital expenditures, fueling an infrastructure arms race even as front-end AI tools become more interchangeable. The practical implication for MSPs and IT service providers is increased pressure to re-evaluate business models, operationalize AI offerings, and focus on defensible, productized services. Reliance on a single vendor or seat-based growth forecasts presents heightened risk. Successful adaptation will require a shift toward managed services around AI operations, governance, and productivity—emphasizing accountability, optionality, and measurable ROI—rather than assuming historic revenue models will persist. Three things to know today: 00:00 Partners Essential to Sales but Losing Economic Share, Survey Shows 05:44 US Job Market Shows Low Hiring, Low Firing Despite Falling Openings        08:00 Alphabet Plans $180B AI Capex as Gemini Hits 750M Users This 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/28908079 YouTube: https://youtube.com/mspradio Bluesky: https://bsky.app/profile/businessof.tech Instagram: https://www.instagram.com/mspradio TikTok: https://www.tiktok.com/@businessoftech Facebook: 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.

    13 min
  8. Why AI Pilots Stall: Data, Complexity, and the Build vs. Buy Debate With Ashwin Mehta

    FEB 8

    Why AI Pilots Stall: Data, Complexity, and the Build vs. Buy Debate With Ashwin Mehta

    AI pilot programs are consistently failing to deliver measurable business value, with a primary cause identified as a lack of clearly defined problem statements guiding these initiatives. Ashwin Mehta, an AI strategist with experience leading enterprise transformations, emphasized that many organizations initiate AI pilots without specific objectives, resulting in projects that struggle to demonstrate impact or justify further investment. This lack of focus often leads to stalled initiatives, rather than progress into scalable production environments. The discussion outlined how mid-market and small businesses typically implement AI by acquiring SaaS tools with embedded AI features, rather than building bespoke solutions. Ashwin Mehta observed that while “build versus buy” considerations have shifted as orchestration and database platforms become more accessible, custom development still brings additional risk, skill requirements, and long-term maintenance burden. Even as technical barriers decrease, organizations are cautioned to weigh lifecycle costs and operational support needs before pursuing custom builds. Data management was highlighted as a recurrent challenge, both from an organizational readiness perspective and regarding regulatory risk. Ashwin Mehta underscored the importance of establishing a single source of truth for business-critical data and classifying information by its regulatory sensitivity. Without such data discipline, adoption of AI tools—especially in regulated sectors—becomes a source of uncertainty, with organizations defaulting to restrictive or prohibitive AI policies due to inadequate risk visibility. For MSPs and technology leaders, the operational implications are clear: pilots without rigorous scoping and problem definition are unlikely to progress, and sustainable AI adoption requires purposeful data governance and clear frameworks for project prioritization. With the complexity of AI implementations extending beyond technical issues to include cost volatility, compliance, change management, and skills gaps, providers must approach each initiative with a structured, risk-aware mindset and ensure ongoing oversight as both technology and regulatory landscapes evolve. Sponsored 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/28908079 YouTube: https://youtube.com/mspradio Bluesky: https://bsky.app/profile/businessof.tech Instagram: https://www.instagram.com/mspradio TikTok: https://www.tiktok.com/@businessoftech Facebook: 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.

    24 min

Trailers

4.9
out of 5
87 Ratings

About

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.

You Might Also Like