Techsplainers by IBM

IBM
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Introducing the Techsplainers by IBM podcast, your new podcast for quick, powerful takes on today’s most important AI and tech topics. Each episode brings you bite-sized learning designed to fit your day, whether you’re driving, exercising, or just curious for something new. This is just the beginning. Tune in every weekday at 6 AM ET for fresh insights, new voices, and smarter learning. Visit podcast page: https://www.ibm.com/think/podcasts/techsplainers

  1. قبل يوم واحد

    What is zero trust?

    This episode of Techsplainers explores zero trust, the broader security framework that ties together the week’s discussions of least privilege, just-in-time access, continuous authentication and risk-based authentication. Instead of relying on a traditional network perimeter, zero trust applies security policies to each individual connection between users, devices, applications and data. The episode explains why zero trust has become so important in modern IT environments and breaks down the core principles shared across most zero trust models. It also walks through the five pillars commonly used to structure zero trust implementations: identity, devices, networks, applications and workloads, and data. Find more information at https://www.ibm.com/think/topics/zero-trust Find more episodes: https://www.ibm.biz/techsplainers-podcast Narrated by Dan Nosowitz

    What is zero trust?

  2. قبل يومين

    Guide to risk-based authentication

    This episode of Techsplainers explores risk-based authentication (RBA), a security approach that adjusts authentication requirements based on the risk level of a login or access request. Building on the week’s discussion of the principle of least privilege, just-in-time access and continuous authentication, the episode explains how organizations use RBA to decide how much proof of identity to require before granting access in the first place. The discussion breaks down how RBA works, the importance of logging, and how RBA works with continuous authentication and adaptive authentication in a layered trust model. Find more information at https://www.ibm.com/think/topics/risk-based-authentication Find more episodes: https://www.ibm.biz/techsplainers-podcast Narrated by Dan Nosowitz

    Guide to risk-based authentication

  3. قبل ٣ أيام

    Guide to continuous authentication

    This episode of Techsplainers explores continuous authentication, a security approach that keeps verifying a user’s identity throughout an active session instead of relying on a single login check. The discussion contrasts continuous authentication with traditional one-time authentication models and explains why that older “front-door only” approach leaves gaps for session hijacking, insider threats and the abuse of valid credentials. It walks through how continuous authentication works in practice, including behavioral biometrics, adaptive risk scoring and contextual signals. It also clarifies the difference between continuous authentication and adaptive authentication, showing how the two can work together as a layered trust model. Finally, the episode examines why continuous authentication is increasingly important for nonhuman identities such as service accounts, machine identities and AI agents. Find more information at: https://www.ibm.com/think/topics/continuous-authentication Find more episodes: https://www.ibm.biz/techsplainers-podcast Narrated by Dan Nosowitz

    Guide to continuous authentication

  4. قبل ٤ أيام

    What is just-in-time access?

    This episode of Techsplainers explores just-in-time access, an identity security model that grants users temporary permissions only when they need them and removes that access automatically when the task is complete. Building on the principle of least privilege, the episode explains why time matters just as much as scope when controlling access to sensitive systems. The discussion looks at the risks created by standing privileges, including how stolen credentials can give attackers ongoing access to critical environments and make lateral movement easier. It breaks down the typical JIT workflow and compares three common implementation models: broker-and-remove, ephemeral accounts and temporary elevation. Along the way, listeners learn how JIT fits into broader identity security practices like privileged access management, zero trust, and zero standing privileges. The episode also examines why JIT is increasingly important for nonhuman identities and AI agents, which often operate at higher speed and scale than human users. Find more information at https://www.ibm.com/think/topics/just-in-time-access Find more episodes: https://www.ibm.biz/techsplainers-podcast Narrated by Dan Nosowitz

    What is just-in-time access?

  5. قبل ٥ أيام

    What is the principle of least privilege (PoLP)?

    This episode of Techsplainers introduces the principle of least privilege, a core cybersecurity concept that limits users, applications and machine identities to only the access they need, only for as long as they need it. The episode explains how least privilege fits within identity and access management, reducing the blast radius of compromised credentials while ensuring that legitimate users have the access they need when they need it. The discussion also explores why least privilege has become more urgent as nonhuman identities like service accounts and AI agents multiply across modern environments. Finally, it looks at the operational side of enforcement, including privileged access management, identity governance and different access control models. Find more information at https://www.ibm.com/think/topics/principle-of-least-privilege Find more episodes: https://www.ibm.biz/techsplainers-podcast Narrated by Dan Nosowitz

    What is the principle of least privilege (PoLP)?

  6. ١١ سبتمبر

    AI in customer relationship management (CRM)

    This episode of Techsplainers explores how artificial intelligence is changing customer relationship management by helping organizations organize customer data, automate business processes and create more timely, relevant interactions across sales, marketing and service. It explains how AI moves CRM beyond recordkeeping and into prediction, personalization and operational insight. The episode looks at the rise of AI in CRM, tracing the shift from early database-style systems to modern platforms that use machine learning, natural language processing and generative AI to interpret customer behavior at scale. It covers the benefits most specific to AI-powered CRM, including predictive analytics, lead scoring, sentiment analysis, marketing personalization, workflow automation and the ability to manage unstructured data such as emails, transcripts and support notes. It also highlights practical use cases across business intelligence, customer service, sales optimization, customer service, sales optimization, process improvement and data management, while addressing the importance of accurate data, privacy and customer trust. As the final episode in the week’s series on improving customer experience with AI, it brings the focus inward to the systems that help connect every stage of the customer relationship. Find more information at https://www.ibm.com/think/topics/ai-crm Find more episodes: https://www.ibm.biz/techsplainers-podcast Narrated by Amanda Downie

    AI in customer relationship management (CRM)

  7. ١٠ سبتمبر

    Better customer service with AI agents

    This episode of Techsplainers explores how AI agents are changing customer service by moving beyond simple question answering into autonomous, goal-oriented support. It explains what makes AI agents different from standard chatbots and assistants, including their ability to retain memory, reason across multiple steps, use external tools and take action within connected systems. The episode follows how these agentic systems work in real customer service environments, from handling customer queries and retrieving knowledge base content to managing order tracking, identifying sentiment, summarizing conversations and automating administrative tasks. It also looks at how networks of specialized agents can work together across workflows to speed up service resolution and improve continuity across channels. Along the way, the discussion connects AI agents to the broader customer experience themes explored earlier in the week, including onboarding, response time and personalized support. Real-world examples such as Camping World and Avid Solutions show how agentic systems can improve engagement, reduce delays and streamline customer-facing operations. The episode also highlights four best practices for deployment: aligning agents with service strategy, equipping them with the right data and tools, integrating them into enterprise systems and helping human teams build the skills to work effectively alongside them. Find more information at https://www.ibm.com/think/topics/ai-agents-in-customer-service Find more episodes: https://www.ibm.biz/techsplainers-podcast Narrated by Amanda Downie

    Better customer service with AI agents

  8. ٩ سبتمبر

    Accelerating customer service response time with AI

    This episode of Techsplainers explores how artificial intelligence helps companies accelerate customer service response times across chat, email, social platforms and support portals. It explains why first response time is such an important measure of the support experience and how delayed replies can quickly affect customer trust, satisfaction and retention. The episode looks at both traditional and AI-enabled approaches to faster service, from knowledge bases and service level agreements to chatbots, automated first replies and intelligent self-service. It also examines how AI can classify incoming requests, detect customer intent, route tickets to the right team, assist agents with suggested responses and summarize conversations during handoffs. As the discussion moves into more advanced use cases, it covers workflow automation and agentic AI systems that can complete service tasks across multiple tools, reducing the time between a customer request and actual resolution. Along the way, the episode highlights the broader business benefits of AI-supported response acceleration, including improved availability, stronger customer satisfaction, increased support capacity, more consistent service and lower operational costs. Find more information at https://www.ibm.com/think/insights/accelerate-customer-service-response-time-ai Find more episodes: https://www.ibm.biz/techsplainers-podcast Narrated by Amanda Downie

    Accelerating customer service response time with AI
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Introducing the Techsplainers by IBM podcast, your new podcast for quick, powerful takes on today’s most important AI and tech topics. Each episode brings you bite-sized learning designed to fit your day, whether you’re driving, exercising, or just curious for something new. This is just the beginning. Tune in every weekday at 6 AM ET for fresh insights, new voices, and smarter learning. Visit podcast page: https://www.ibm.com/think/podcasts/techsplainers

المعلومات

  • صناع العمل
    IBM
  • سنوات النشاط
    ٢٠٢٥ - ٢٠٢٦
  • الحلقات
    ٢٢٦
  • التقييم
    ملائم
  • حقوق النشر
    © ibm2026
  • موقع البرنامج على الويب
    Techsplainers by IBM