AI Accelerator Podcast copertina

AI Accelerator Podcast

AI Accelerator Podcast

Di: Matt Zembruski
Ascolta gratuitamente

Offerte di stagione | 0,99 €/mese per i primi 3 mesi

A seguire 9,99 €/mese – si applicano condizioni. Puoi disdire mensilmente.

The AI Accelerator Podcast is for business leaders, executives, entrepreneurs, and innovators who want to move beyond AI theory and into real-world results.


Hosted by Matt Zembruski, each episode features candid conversations with industry experts, technology leaders, founders, and AI practitioners who are transforming organizations through artificial intelligence.


From enterprise AI strategy and automation to leadership, innovation, and emerging technologies, we explore what works, what doesn't, and what leaders need to know to stay ahead.


If you're looking to turn AI into a competitive advantage, drive meaningful business outcomes, and prepare your organization for the future, this podcast is your roadmap.


New episodes every week.

© 2026 AI Accelerator Podcast Economia Gestione e leadership Leadership
Episodi
  • AI-Powered Strategic Execution: Connecting Strategy to Results | Cliff Berg | AI Accelerator Podcast

    AI-Powered Strategic Execution: Connecting Strategy to Results | Cliff Berg | AI Accelerator Podcast
    Oct 20 2026
    How can organizations use AI to close the gap between business strategy and the work people actually do every day? In this episode of the AI Accelerator Podcast, Matt Zembruski speaks with Cliff Berg, managing partner of Agile 2 Academy, founder of the Agile 2 initiative, and architect of the Throughline AI strategic execution platform. With 30 years of experience studying how organizations operate, Cliff shares why traditional planning and task management can get in the way of agility, and how AI can help leaders connect strategy, goals, and execution. The conversation explores how AI agents become more effective when they understand an organization's intentions, why leaders should give teams problems to solve rather than simply assigning tasks, and how businesses can introduce AI while keeping humans involved in important decisions. In This Episode, Cliff Berg Discusses: Why organizational agility depends on leadership behavior, not just frameworksThe origins of Throughline and its AI-powered strategic execution platformConnecting strategy, planning, and daily workWhy solving problems can be more effective than assigning tasksLessons from SpaceX's approach to rapid experimentation and executionHow psychological safety develops when teams are empowered to try thingsWhy AI agents need access to organizational goals, intentions, and contextThe importance of human oversight in AI-powered workflowsHow AI can identify dependencies, delays, risks, and strategic misalignmentBuilding roadmaps around outcomes instead of excessive task trackingPractical ways to identify low-hanging fruit for AI adoptionUsing AI to review subcontract agreements and save timeHelping mid-market companies connect AI adoption to long-term business strategy Chapters 00:00 Introduction to the AI Accelerator Podcast 00:56 Meet Cliff Berg: Agile 2 and Throughline AI 02:28 Why Cliff Built an AI-Powered Execution Platform 03:45 Connecting Strategy, Planning, and Execution 04:51 Why Traditional Task Planning Can Get in the Way 05:46 The Problem-Centric Approach to Work 06:43 What Organizations Can Learn From SpaceX 08:02 Empowering Teams and Building Psychological Safety 09:54 Giving AI Agents the Context They Need 10:30 Understanding Organizational Intentions 11:56 Why Strategic Context Matters for AI Deployments 13:38 How Throughline Agents Understand and Prioritize Work 14:52 Keeping Humans in the Loop 15:45 Why AI Output Quality Matters More Than Speed 17:50 Connecting Strategy to Everyday Execution 18:28 Defining Mission, Vision, and Strategy 19:58 Building Flexible Roadmaps and Goals 21:37 Using AI to Identify Dependencies and Misalignment 22:20 Advice for Business Leaders Starting With AI 23:44 Finding Practical AI Use Cases 24:11 Automating Subcontract Reviews With AI 25:30 Moving From Quick Wins to Strategic AI Adoption 26:18 How to Connect With Cliff Berg 💬 Cliff Berg's Key Insights "The tools we have make it really hard to do all this." "What we need is a tool that actually creates this line of sight from strategy through planning and execution." "The behavioral norm there is to give people problems to solve, not tasks to do." "What we want is good output. We want aligned output." "The AI cannot say that's done." About Cliff Berg Cliff Berg is the managing partner of Agile 2 Academy, founder of the Agile 2 movement, and architect of the Throughline AI agent strategic execution platform. He has spent approximately 30 years studying how organizations operate and helping businesses improve agility, planning, and execution. Cliff previously co-founded Digital Focus, a technology company that grew from two people to 200 employees in five years before being acquired in 2006. In 2019, he launched the Agile 2 initiative and became the lead author of Agile 2: The Next Iteration of Agile, examining why conventional Agile approaches can fail to produce genuine organizational agility. Cliff has led more than 10 Agile and DevOps transformations, authored six books, and worked with executives and delivery teams to address organizational and technical challenges. His work combines software engineering, systems thinking, leadership, and AI to help organizations connect strategy with execution. Follow Cliff Berg Website: https://www.throughlineai.net LinkedIn: https://www.linkedin.com/in/cliffberg/ Follow Matt Zembruski Website: https://leadingaiagility.com LinkedIn: https://www.linkedin.com/in/mattzembruski/ Email: matt@leadingaiagility.com Phone / Text / WhatsApp: +1 978-618-5778
    Mostra di più Mostra meno
    27 min
  • AI-Native Transformation: The 5 Stages of Becoming Hyperadaptive | Melissa Reeve | AI Accelerator Podcast

    AI-Native Transformation: The 5 Stages of Becoming Hyperadaptive | Melissa Reeve | AI Accelerator Podcast
    Oct 13 2026
    What does it really take to become an AI-native organization?In this episode of the AI Accelerator Podcast, Matt Zembruski sits down with Melissa Reeve, creator of the Hyperadaptive Model and author of Hyperadaptive: Re-wiring the Enterprise to Become AI-Native, to explore how organizations can move beyond AI pilots and build the systems, governance, and human capabilities needed to continuously adapt.Drawing on 25 years of experience as an executive and Agile thought leader, including serving as the first VP of Marketing at Scaled Agile and co-founding the Agile Marketing Alliance, Melissa shares a practical, human-centered approach to enterprise AI transformation.The conversation explores the five stages of becoming AI-native, dynamic governance, AI Impact Hubs, the activation layer that can help organizations turn AI experiments into results, and why the companies succeeding with AI may be the ones that double down on what makes humans uniquely valuable.In This Episode, Melissa Reeve Discusses:The Hyperadaptive Model for AI transformationThe five stages of becoming an AI-native organizationWhy AI pilots often fail to translate into enterprise resultsThe importance of an organizational activation layerDynamic governance in an AI-powered enterpriseHow AI changes traditional organizational boundariesBuilding AI Impact Hubs across departmentsHow HR, Finance, and other functions may evolve alongside AIUpskilling and reskilling employees for AI-plus-human rolesLessons from Greenfield Savings Bank's AI transformationWhy AI adoption is more than a technology or licensing decisionHow leaders can identify pain points and match them with AI solutionsWhy successful AI organizations may need to double down on human capabilitiesRewiring traditional organizations to become more adaptiveChapters00:00 Introduction00:56 Meet Melissa Reeve, Creator of the Hyperadaptive Model01:18 The Five Stages of Becoming AI-Native02:02 Melissa's Journey From Japan and Toyota to Agile Transformation06:00 From Process Excellence to AI Transformation12:31 Breaking Organizational Silos With AI13:00 Building AI Impact Hubs13:24 Upskilling and Reskilling for an AI-Plus-Human Future21:29 Why AI Success Requires Doubling Down on What Makes Us Human26:20 A Real-World AI Transformation Story: Greenfield Savings Bank27:00 Moving From AI Technology to Human-Centered TransformationKey Learnings1. Becoming AI-native requires more than adding AI toolsMelissa's Hyperadaptive Model focuses on the organizational transformation required to become AI-native. The challenge isn't simply choosing an AI model or purchasing licenses. Organizations need to rethink how their processes, people, governance, and operating systems work together as AI becomes part of everyday work.2. AI transformation requires an activation layerOne of the central ideas discussed in the episode is the need for an activation layer between AI pilots and actual business results. Organizations can experiment with AI, run pilots, and demonstrate impressive technology. But without the systems and organizational mechanisms required to activate those capabilities, pilots can remain disconnected from meaningful outcomes.3. AI breaks down traditional organizational boundariesAI doesn't necessarily stay inside traditional departmental boxes. As Melissa explains, people increasingly need to work across what she calls their "adjacent competencies." Instead of thinking only about what HR does or what Finance does, organizations need to ask how AI is changing the work, roles, and capabilities within each function.4. AI Impact Hubs can help organizations manage this transitionMelissa describes the concept of AI Impact Hubs as a way to understand how AI and automation are affecting different parts of an organization.These hubs can examine questions such as:How is automation changing work within Finance?How are roles evolving?Can frontline employees be upskilled or reskilled?What new AI-plus-human roles could emerge?How can organizations support employees through the transition?This creates a more systematic approach to organizational adaptation.5. AI adoption should start with real pain pointsThe Greenfield Savings Bank example illustrates a practical approach to AI adoption. Rather than treating AI as simply a technology rollout, the CEO selected one or two people from each department to identify significant pain points and then match an AI solution to those problems. The shift was from focusing primarily on licensing and deploying technology to focusing on the people, problems, and outcomes that AI could actually improve.6. The future isn't only about AI doing moreA major theme of the conversation is that organizations succeeding with AI may be the ones that double down on what makes humans most valuable. As automation changes tasks and workflows, organizations need to think carefully about what humans should continue doing, what new capabilities employees need, and how people and AI can work ...
    Mostra di più Mostra meno
    31 min
  • AI, Revenue Growth & the Future of AI-Powered Companies | Andre Cuenin | AI Accelerator Podcast

    AI, Revenue Growth & the Future of AI-Powered Companies | Andre Cuenin | AI Accelerator Podcast
    Oct 6 2026
    How can companies move beyond using AI for productivity and start using it to fundamentally change how they operate, compete, and grow?In this episode of the AI Accelerator Podcast, Matt Zembruski sits down with Andre Cuenin, Chief Revenue Officer at SolarWinds, to explore how AI is changing enterprise workflows, customer preparation, data utilization, and the future of business.With more than 20 years of experience driving revenue at technology companies including Veracode, Rapid7, Cherwell Software, Stratavia, and CA, Andre brings a practical revenue and leadership perspective to the AI transformation happening across organizations.The conversation explores the difference between simply optimizing existing processes and using AI to create entirely new ways of solving business problems.In This Episode, Andre Cuenin Discusses:How AI can optimize existing business workflowsUsing AI to prepare for customer meetingsHow AI agents can connect information across CRM, finance, and support systemsThe importance of data breadth and quality when implementing AIWhy organizations need to think beyond individual employee productivityHow leaders should approach AI adoption and transformationThe difference between AI optimization and AI-driven opportunityWhy AI may represent one of the most significant technology shifts of our lifetimeHow companies can stay competitive as AI adoption acceleratesWhat separates organizations that successfully leverage AI from those that risk being left behindChapters00:00 Introduction01:03 Meet Andre Cuenin, CRO at SolarWinds01:15 What AI Is Really Doing to Jobs Today06:14 Applying AI to Optimize Existing Workflows06:37 Using an AI Agent to Prepare for Customer Meetings07:08 The Optimization Path for AI10:50 Connecting AI to the Breadth of Enterprise Data11:15 Data Quality and Building Better AI Workflows14:58 Andre's Recommendations for Business Leaders19:03 AI as a Major Technology Shift19:48 Two Types of Companies in the Future20:00 Optimization vs. New Business Opportunities21:00 Staying Competitive in an AI-Driven MarketKey Learnings1. Start with optimizationAndre describes one practical path for AI adoption as optimization: take something the organization already does and use AI to perform it more effectively and efficiently.2. AI agents can connect information across the organizationOne of the biggest opportunities comes from connecting AI to the information already distributed throughout an organization. Customer information may exist across multiple systems. An AI agent can help bring that information together so employees don't have to manually search through different platforms to understand the full customer story.3. Data breadth and quality matterConnecting an AI system to enterprise data is only part of the challenge. Organizations also need to consider whether the AI has access to the breadth of data that actually matters and how they can perform appropriate quality checks on that information. Better AI outcomes require organizations to think carefully about their underlying data.4. AI creates opportunities beyond optimizationAndre describes a distinction between using AI to do existing work better and using AI to solve problems in completely different ways. Optimization can make existing processes faster and more efficient. The larger opportunity may come from asking: What could we do differently if AI fundamentally changed how this problem was solved?5. AI could reshape competitive advantageAndre believes AI represents one of the most significant technology shifts many people will experience during their lifetime. For business leaders, the challenge is not simply understanding AI. It is figuring out how to leverage it while maintaining competitiveness.mAs AI adoption accelerates, companies that successfully integrate AI into both optimization and new opportunities may gain an advantage over organizations that fail to adapt.💬 Andre Cuenin's Key Insights"You do what you have done before, but more effectively, more efficiently.""A great example of doing something I did before, but much more effectively and efficiently.""How can I leverage it and also make sure I stay competitive?""There’s gonna be two types of companies in the future."About Andre CueninAndre Cuenin serves as Chief Revenue Officer at SolarWinds, where he oversees revenue generation relating to the company's observability, database, and service management solutions.He brings more than 20 years of experience driving revenue growth strategies at technology companies including Veracode, Rapid7, Cherwell Software, Stratavia, and CA.Throughout his career, Andre has focused on building cultures of trust, candor, teamwork, and sustainable customer outcomes. He holds a Bachelor of Computer Science from the University of Applied Sciences and Arts of Western Switzerland and an MBA from Strathclyde University in Glasgow.Follow Andre CueninWebsite: https://www.solarwinds.com/LinkedIn: https://www.linkedin.com/in/...
    Mostra di più Mostra meno
    21 min
adbl_web_anon_alc_button_suppression_t1
Ancora nessuna recensione