The Robotics Revolution - AI-Powered Humanoid Robots in 2025 and Beyond 

In this episode of The Macro AI Podcast, hosts Gary and Scott dive into the transformative world of AI-driven humanoid robotics, exploring how these innovations are reshaping business and daily life. With the global robotics market hitting $16.5 billion in 2024, AI is enabling humanoids to move beyond factories into homes, tackling tasks from chores to eldercare. We unpack advancements like NVIDIA’s Isaac GR00T, which trains robots via virtual simulations, and real-world use cases, such as AgiBot’s humanoids folding T-shirts in Shanghai and Amazon’s warehouse automation. 

Globally, the US, China, and Europe lead the charge. Elon Musk claims Tesla’s Optimus will hit 10,000 units in 2025, scaling to millions by 2030 at $20,000 each, though experts question full autonomy. China’s $137 billion investment, including Shenzhen’s 10 billion yuan fund, drives companies like UBTECH, while Europe’s KUKA and Robotnik focus on sustainable designs. Japan, South Korea, and India also innovate, with the humanoid market projected to reach $13.25 billion by 2029. 

For consumers, humanoids like Tesla’s Optimus or UBTECH’s Walker will handle chores, eldercare, and tutoring by 2030, with costs dropping to $17,000. Challenges include safety, privacy, and cloud connectivity in air-gapped environments like mines, requiring edge AI solutions. Practical advice for leaders includes adopting cobots, leveraging RaaS, and training workforces to mitigate job displacement risks, with 20 million manufacturing jobs potentially automated by 2030. 

Our technical deep-dive explores AI integration—Analytical AI for navigation, Physical AI for training, and hardware like bionics-inspired grippers. We address cloud dependency issues for robots in remote settings and highlight tools like ROS 2 for developers. Looking ahead, humanoids could dominate homes by 2040, with Musk predicting 10 billion robots, though privacy and ethical concerns will drive regulations. 

Join us for actionable insights on leading in the AI era and preparing for a future where humanoids are as common as smartphones. Subscribe and share to stay ahead in the AI revolution! 

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About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

In this episode of The Macro AI Podcast, hosts Gary and Scott dive into the critical distinction between deterministic and probabilistic AI, offering practical insights for business leaders navigating the AI-driven landscape of 2025. Designed for executives and technical professionals alike, the episode explores how these AI approaches shape strategy, innovation, and global competitiveness. 

Gary and Scott kick off by defining the terms: deterministic AI delivers consistent, rule-based outputs, like a recipe yielding the same result every time, while probabilistic AI embraces uncertainty, using statistical models to adapt to complex, data-rich scenarios. Through real-world examples, they illustrate the impact: UPS leverages deterministic AI for reliable route optimization, while Amazon’s probabilistic recommendation engine drives $1 billion in annual sales. The hosts discuss trade-offs—deterministic systems ensure compliance and trust in industries like finance, while probabilistic models power innovation in marketing and fraud detection, as seen with JPMorgan Chase catching 70% more suspicious transactions. 

In a dedicated technical segment, Gary and Scott unpack the mechanics: deterministic AI uses fixed algorithms like minimax for chess, while probabilistic AI relies on neural networks and softmax functions, as in large language models. They highlight hybrid approaches, like Zeotap’s Customer Data Platform, blending both for precision and scalability. 

For business leaders, the episode offers actionable advice: align AI with use cases, invest in governance to mitigate risks, embrace hybrid models, and upskill teams to build a data-driven culture. Backed by 2025 insights from McKinsey, PwC, and MIT Sloan, this episode equips listeners to make smarter AI decisions. Tune in to learn how to balance predictability and innovation to transform your business in the AI era. 

Keywords: Deterministic AI, Probabilistic AI, business transformation, AI strategy, machine learning, hybrid AI, business leadership, innovation, 2025 AI trends. 

 Sources: 

• Gaine Technology, “Probabilistic and Deterministic Results in AI Systems” (2023) 
• Moveworks, “What is a Probabilistic Model?” 
• Stanford HAI, “AI Index Report 2025” 
• Zeotap, “Probabilistic vs. Deterministic Data” (2021) 
• PwC, “2025 AI Business Predictions” 
• Exploding Topics, “50 NEW Artificial Intelligence Statistics (May 2025)” 
• McKinsey, “The State of AI: How Organizations Are Rewiring to Capture Value” (2025) 
• MIT Sloan, “Leadership and AI Insights for 2025” 
• Medium, “Bridging the Probabilistic and Deterministic” (2025) 
• Capgemini, “The Evolution of Hybrid AI” (2024) 

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

The Macro AI Podcast, hosted by Scott and Gary, continues its exploration of artificial intelligence’s transformative potential in Episode 22, titled "AI’s Future of Work: Jobs, Skills, and UBI in 2030." Building on the success of Episode 11, the podcast’s most downloaded episode, this installment delves into the latest trends, predictions, and insights shaping the global workforce in the AI era. Recorded on May 19, 2025, the episode offers a comprehensive, forward-looking analysis of how AI is redefining work, creating new opportunities, and posing challenges across industries, cultures, and economies. With a runtime potentially exceeding 40 minutes, the episode balances technical depth, societal implications, and practical guidance, making it a must-listen for business leaders, students, and anyone curious about the future of work. 

Key Takeaways for Listeners 

• Workforce Dynamics: AI drives job polarization, with 40% growth in high-skill roles and 25% contraction in low-skill roles by 2030, necessitating reskilling and hybrid roles like AI-human collaboration specialists. 
• Sector Impacts: Healthcare, education, creative, and green sectors see job creation (e.g., 34 million in agriculture/aquaculture), but automation reduces routine roles, requiring adaptation. 
• Technical Drivers: Agentic and multi-modal AI, supported by 6G and edge computing, fuel innovation, creating roles like AI integration engineers (35% growth by 2030). 
• Societal Shifts: A potential 3.5-day workweek by 2040 and UBI/UHI debates highlight AI’s cultural impact, with mental health and digital divide concerns needing attention. 
• Education and Skills: Interdisciplinary education, AI literacy, and global skills (e.g., multilingual economists) are critical, with universities like MIT leading the way. 
• Leadership: Human-centric AI, reskilling, and sustainability drive success, while navigating regulatory and ethical challenges is essential. 
• Opportunities: AI startups, governance roles, and power infrastructure jobs (e.g., grid engineers) offer growth, supported by collaborative ecosystems. 

Relevance and Impact 

Episode 22 stands out for its comprehensive analysis, blending data-driven projections with real-world examples, like aquaculture’s AI-driven roles and Musk’s UHI controversy. Its focus on actionable advice—reskilling for leaders, interdisciplinary skills for students—makes it relevant for a broad audience. The episode’s engagement hooks, addressing questions like AI’s net job creation and education’s adaptation, spark curiosity and invite listener participation, ensuring it resonates in the ongoing AI discourse. 

#AIFutureOfWork, #UBI, #AIJobs, #Reskilling, #2030Workforce  

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

In Episode 22 of The Macro AI Podcast, hosts Gary and Scott dive into the rapidly evolving world of Conversational AI, joined by Kolin Koehl, Vice President of Product at Observe.AI. This San Francisco-based company is at the forefront of revolutionizing customer service through its innovative AI-powered Conversation Intelligence platform. This episode offers listeners a deep dive into how AI is reshaping customer experiences, the future of contact centers, and the exciting developments in the Conversational AI space. Whether you’re a business leader, tech enthusiast, or curious about the impact of AI on customer interactions, this episode is packed with insights that will leave you eager to learn more. 

Introduction: Setting the Stage for Conversational AI 

The episode kicks off with the signature sophisticated and forward-looking intro music, setting the tone for an engaging discussion. Hosts Gary and Scott warmly welcome their audience, expressing excitement about the topic of Conversational AI and its transformative potential. They introduce Kolin Koehl, a key figure at Observe.AI, and set the stage for a conversation that ties into previous episodes on Agentic AI and the broader impact of AI on customer experience (CX). With Observe.AI’s mission to enhance customer service through advanced AI, this episode promises to deliver actionable insights and forward-thinking perspectives. 

Guest Introduction: Kolin Koehl and Observe.AI 

Kolin Koehl takes the mic to share his professional journey and how it led him to Observe.AI. As Vice President of Product, Kolin brings a wealth of experience in product development and innovation in the AI space. He provides an overview of Observe.AI, a San Francisco-based company dedicated to transforming customer service through its Conversation Intelligence platform. The platform leverages advanced AI to analyze, optimize, and enhance customer interactions, enabling businesses to deliver exceptional experiences while streamlining operations. Kolin’s introduction sets the foundation for a deeper exploration of how Observe.AI is making waves in the AI-driven customer service landscape. 

The Future of Conversational AI 

Scott shifts the conversation to the future, asking Kolin where he sees Conversational AI heading. This segment explores emerging trends and innovations that are poised to redefine how businesses interact with customers. From advancements in natural language processing (NLP) to more intuitive and context-aware AI systems, Kolin shares his vision for a future where AI not only responds to customer queries but anticipates needs and personalizes interactions at scale. This forward-looking discussion is sure to captivate listeners interested in the next frontier of AI-driven customer experiences. 

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

The Macro AI Podcast: Scaling the Future: The Latest in Large Language Models 

Join hosts Gary and Scott on The Macro AI Podcast as they dive into the cutting-edge world of large language models (LLMs) for business leaders aiming to transform their organizations and compete globally. In this episode, we unpack the latest advancements in AI, focusing on parameter counts—a key benchmark for model capacity—and explore how top LLMs like ChatGPT 4.0, Claude 3.7, Grok 3, Llama 3.1 405B, Gemini 2.5 Pro, and Mistral Large 2 are driving innovation.  

Discover what each model excels at: ChatGPT 4.0 (200B parameters) offers versatile multimodal capabilities for customer service and analytics; Claude 3.7 (400B) ensures safety for regulated sectors like healthcare; Grok 3 (2.7T) powers R&D in pharmaceuticals; Llama 3.1 405B (405B) enables customizable, open-source solutions for logistics; Gemini 2.5 Pro (~200–400B) integrates vision and audio for retail; and Mistral Large 2 (123B) delivers cost-effective, GDPR-compliant processing.  

In a technical deep dive, Gary and Scott explain transformer architectures, Mixture-of-Experts designs, and training techniques like RLHF, balancing insights for tech leads and executives. Looking ahead, we explore speculative giants like China’s BaGuaLu (174T parameters, unverified) and ByteDance’s 5T-parameter model with novel “di-reasoning,” hinting at future breakthroughs in strategic planning and scientific discovery. 

With practical advice for leading in the AI era—aligning AI with business goals, budgeting for infrastructure, and fostering AI literacy—this episode equips leaders to harness LLMs for competitive advantage. Tune in for actionable insights and a glimpse into AI’s transformative future! 

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About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

The Macro AI Podcast: Digital Twins: Revolutionizing Business with Virtual Replicas 

 
Join hosts Gary and Scott as they explore digital twins—virtual replicas transforming industries worldwide. Learn how these dynamic models, powered by real-time data, AI, and IoT, drive efficiency, innovation, and sustainability in manufacturing, healthcare, urban planning, automotive, and more. From predictive maintenance to smart cities, discover practical applications and leadership strategies to leverage digital twins for competitive advantage. Dive into a technical deep dive on the tech stack—cloud platforms, AI models, and data pipelines—and hear answers to listener questions on ROI, skills, and security. With the market projected to hit $73.5B by 2027, this episode offers business leaders and tech enthusiasts actionable insights to lead in the AI era. Tune in for 35 minutes of cutting-edge AI solutions!  

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About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

The Macro AI Podcast: Episode 19 - AI and the Enterprise Threat Landscape 

Join hosts Gary Sloper and Scott Bryan in this engaging episode of The Macro AI Podcast as they explore how Artificial Intelligence is transforming the cybersecurity landscape for enterprises. Featuring special guest Ed Dunnahoe, VP of Innovation at Guidepoint Security—a trusted cybersecurity provider for over 40% of Fortune 500 companies—this episode dives into the evolving challenges and solutions in enterprise security driven by advancements in AI and machine learning. 

Kicking off the discussion, Ed shares his background and journey to his current role at Guidepoint Security, offering a glimpse into his expertise at the forefront of cybersecurity innovation. The conversation then shifts to key areas impacted by AI in the enterprise threat landscape. 

The hosts and Ed first tackle Governance, Risk, and Compliance (GRC), exploring how AI introduces new complexities and opportunities for ensuring regulatory adherence and managing risks in large organizations. Next, they discuss Application Security (AppSec), examining how AI tools have reshaped the practices of identifying and mitigating vulnerabilities in software applications, fundamentally altering the AppSec landscape. 

The episode also covers Incident Response, where Ed highlights the challenges IT teams face in responding to security incidents in an AI-driven world, drawing from real-world conversations with industry leaders. The discussion then turns to Identity Management, addressing the emerging challenges of securing identities as AI technologies introduce new vulnerabilities and authentication complexities. 

Finally, the episode delves into AI TRiSM tools (Trust, Risk, and Security Management), which are designed to ensure AI systems remain trustworthy, secure, and compliant with ethical and regulatory standards. Ed shares insights into the latest TRiSM tools and their role in helping enterprises navigate the risks associated with AI adoption. 

Wrapping up, Gary and Scott thank Ed for his invaluable insights and invite listeners to share the episode and connect on LinkedIn for more AI-driven discussions. Tune in to this episode for a high-level overview of how AI is reshaping enterprise cybersecurity and what businesses are doing to stay ahead of the evolving threat landscape. 

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About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

In this episode of The Macro AI Podcast, hosts Gary and Scott dive into the critical topic of bias in AI systems, offering business leaders worldwide practical insights to navigate the AI era. Designed for executives seeking to transform their organizations with cutting-edge AI solutions, this episode unpacks how bias emerges, its impact on business outcomes, and actionable steps to mitigate it. With a blend of strategic advice and technical depth, Gary and Scott ensure the content is accessible yet informative for both business and technical audiences. 

The episode begins by defining AI bias—when systems produce skewed outcomes due to flawed data, assumptions, or design. Bias isn’t just a technical glitch; it’s a business risk that can lead to inefficiencies, missed opportunities, and eroded trust. Real-world examples illustrate the stakes: a retailer’s AI overstocked urban stores while neglecting rural ones due to unrepresentative data, and a beverage company’s ad-targeting AI missed older customers by focusing on tech-savvy urbanites. These cases highlight how bias can sabotage operations and alienate markets, while proactive mitigation can unlock competitive advantages. 

Next, the hosts explore how bias infiltrates AI systems. Data bias arises from unrepresentative datasets, like a manufacturing AI overpredicting demand based on peak-season data. Design bias stems from narrow team perspectives, and model bias amplifies small data flaws, as seen in an e-commerce AI pushing high-margin products and alienating budget shoppers. These examples show how bias compounds, emphasizing the need for leaders to scrutinize data sources, team diversity, and testing rigor. 

In the Tech Deep Dive segment, Gary and Scott unpack the mechanics of bias for technical listeners. They explain how unbalanced datasets cause models to overfit to majority cases, using a coffee shop sales AI that overpredicted demand for urban locations as an example. Feature selection can also introduce bias, like a logistics AI misjudging rural delivery times by prioritizing distance over road conditions. Fairness audits and tools like SHAP help uncover these issues, ensuring robust model performance across scenarios. 

The episode wraps with practical mitigation strategies. Leaders should audit data for representativeness, diversify AI teams, test for fairness across use cases, ensure transparency in AI decisions, and engage stakeholders to understand real-world impacts. Examples include a hotel chain validating demand forecasts across property types and a manufacturer consulting plant managers to refine production AI. These steps transform bias from a liability into an opportunity for better, more inclusive systems. 

Gary and Scott close with a call to action: ask your AI team how they’re ensuring fairness. Resources like the World Economic Forum’s AI Governance Framework and Google’s Responsible AI Practices are recommended for deeper learning. Packed with insights, real-world cases, and actionable advice, this episode equips leaders to harness AI responsibly and competitively. 

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About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

In this episode of The Macro AI Podcast, hosts Gary and Scott explore Vibe Coding—an AI-powered shift in software development that’s slashing costs, speeding up innovation, and redefining the tech world. A must-listen for business leaders, this episode breaks down what Vibe Coding is, its massive potential, and how to leverage it effectively.  

• What’s Vibe Coding? 
  Imagine saying, “Create an app to track sales,” and watching AI write the code in seconds. With tools like Cursor and GitHub Copilot, Vibe Coding turns plain-language ideas into functional software—empowering everyone, from pro developers to total novices. It’s more than a tool; it’s a new creative frontier.  
• Why It’s a Big Deal 
  The impact is already here: 25% of Y Combinator’s Winter 2025 startups built 95% AI-generated codebases. Investors are all in—startups like Codeium and Cursor are hitting unicorn status. But there’s a catch: security risks and bugs, like those in recent SaaS breaches, mean it’s not foolproof yet.  
• How to Make It Work for You 
  Business leaders, take note—Vibe Coding means faster prototypes, cheaper builds, and teams free to focus on big ideas. Here’s how to nail it:  
• Secure It: Craft clear prompts for safer AI code, and use tools like Snyk for human oversight.  
• Debug Smart: Build one feature at a time, and use VS Code breakpoints to squash bugs early.  
• Upskill Fast: Train your team to vet AI code, merging human ingenuity with AI speed. 
• What’s Next? 
  Vibe Coding might soon become “vibe designing,” where intuitive interfaces birth software—unleashing a wave of creators. But as AI does more, security and reliability will be make-or-break. Start small, test boldly, and keep your edge. 

Dive into this episode for a practical, no-fluff look at how Vibe Coding can revolutionize your business—and what it takes to stay ahead.  

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About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Join hosts Gary and Scott as they explore a revolutionary AI solution: meeting delegates powered by Large Language Models (LLMs). Imagine an AI attending meetings for you, speaking in your voice, and advancing your goals while you focus on strategy. In this episode, we unpack how LLMs like GPT-4o, Claude 3.7, and xAI’s Grok 3 can transform workplace productivity and help businesses compete globally. 

Drawing on a groundbreaking Microsoft study, we reveal how AI delegates work: gathering your meeting objectives, engaging in real-time discussions, and using text-to-speech to mimic your voice. Real-world demos show delegates joining project scrums, sharing updates, and asking questions, with models like GPT-4o hitting 60% accuracy in responses. But challenges like transcription errors—think mistaking “Saanvi” for “Savvy”—and latency highlight areas for growth. 

For business leaders, AI delegates offer massive ROI: cutting meeting time, scaling your presence across time zones, and freeing teams for high-value work. Hear how Amtrak’s AI handles 20 million calls yearly and how a healthcare provider used LLMs to catch critical patient data. We also dive into technical details—transformers, self-attention, and retrieval-augmented generation—for tech enthusiasts, plus practical tips for implementation. 

Leading in the AI era means piloting delegates in low-stakes settings, setting clear data boundaries, and reskilling teams. Ethical considerations, like privacy and bias, are front and center, with a phased approach to ensure trust. Whether you’re a CEO in Singapore or a tech lead in São Paulo, this episode equips you to harness AI delegates for smarter collaboration. 

Tune in for actionable insights, real-world examples, and a glimpse into the future of work. Subscribe and share your thoughts 

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About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

In this episode of "The Macro AI Podcast," Gary and Scott guide business leaders through building a private AI system for manufacturing, hosted in a colocation facility, from ideation to launch. Discover how AI can transform operations—think predictive maintenance to cut downtime or real-time quality control to boost product consistency. We start with ideation, spotlighting use cases like GE’s Predix (30% cost savings) and Tesla’s AI vision in Gigafactories. Next, we dive into data prep, leveraging factory sensors and images, and explore colocation’s edge for secure, scalable processing. Model selection gets deep—CNNs for defect detection, RNNs for machine health, plus options like Transformers and pre-trained models from Hugging Face or TensorFlow Hub, alongside vendors like Siemens. Training’s unpacked too: source data from IoT or simulations, use GPUs in a colo for speed, and fine-tune for precision (aiming for 95% accuracy). Testing ensures reliability, integrating with systems like MindSphere, while launching scales from pilot to enterprise, as Toyota’s 15% cost cuts show. Costs? $1,000-$3,000 monthly per colo rack, with massive ROI potential—PwC pegs AI’s manufacturing value at $4 trillion by 2030. For leaders, it’s practical advice: start focused, tap teams, and partner smart. Tune in to lead in the AI era and compete globally! 

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About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Join Gary and Scott on The Macro AI Podcast as they explore Anthropic’s Model Context Protocol (MCP)—a game-changing open standard revolutionizing AI integration. In this episode, " How Model Context Protocol Powers AI Integration," we dive into how MCP connects AI systems to data and tools effortlessly, offering a competitive edge for businesses worldwide. Perfect for leaders seeking transformation and technologists craving practical solutions, we unpack MCP’s value with a real-world example: GlobeMart, a fictional global retail chain, uses MCP to optimize inventory. Facing a blizzard in Canada, GlobeMart’s AI links via MCP to its inventory database, weather APIs, and sales archives—triggering coat reorders for Toronto while redistributing excess stock from Spain, all in real-time. No custom coding, just one protocol delivering agility and cost savings. Gary and Scott break it down: MCP slashes integration chaos, letting AI tap live data from Slack, GitHub, or your CRM. For leaders, it’s about starting small—pilot MCP with a key system, proving the value, and scale globally. It’s open-source, backed by Microsoft and OpenAI (who added MCP support in March 2025), and poised to unify AI ecosystems. Technically, MCP’s client-server setup—think Claude Desktop or an IDE (a developer’s coding hub)—uses JSON-RPC to fetch data and act, like an agentic AI driving decisions. With version 0.2 updates (OAuth, streaming), it’s ready for enterprise action. From cost efficiency to global responsiveness, MCP is your strategic lever. Tune in for actionable insights and see why this could be AI’s TCP/IP moment. 

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About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

In this episode, Gary and Scott speak with Evan Siegel from eGain to discuss the Knowlege Management Platform (KMP) industry. 

Evan Siegel is eGain’s VP of business development and financial services, where he is developing the next generation of AI powered conversational guidance. Prior to eGain, Evan held various customer experience strategy and contact center leadership roles over 16 years at Wells Fargo, where he also established a financial health coaching team that was featured in the bank’s annual report, brand advertising campaign, and ABC’s Good Morning America. Evan is an active writer and speaker, with recent pieces published The Financial Brand, BAI Banking strategies and an appearance on Bain & Company’s Net Promoter Score Podcast. 

eGain is a company that provides AI-powered knowledge management software for customer engagement. eGain Corporation builds and sells AI knowledge SaaS (Software as a Service) products specifically designed for service and support functions. The company is headquartered in Sunnyvale, California. Wikipedia 

Their main product is a platform that unifies knowledge silos within enterprises and transforms content by orchestrating GenAI and experts. This helps businesses provide correct, consistent, and compliant answers to customers, agents, and employees. eGain 

eGain's platform is designed to automate customer engagement with innovative SaaS capabilities powered by AI and knowledge management. Their solutions include virtual assistance, self-service options, and modern agent desktop tools that aim to improve customer experience while reducing agent effort. 

Evan Siegel’s Contact information:  https://www.linkedin.com/in/evan-siegel-ab436845/ 

Link to eGain’s new self-provisioned AI Agent:   https://www.egain.com/ai-agent/ 

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About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

In Episode 12 of The Macro AI Podcast, hosts Gary and Scott explore how artificial intelligence (AI) is transforming global telecom networks, the foundation of our connected world. With the AI market in telecom projected to grow from $1.9 billion in 2024 to over $50 billion by 2034 (39% annual growth), telecoms are adapting to AI’s demands while unlocking new possibilities. This episode covers AI’s role in network infrastructure, enterprise strategies, and global connectivity, offering insights for IT leaders. 

Segment 1: The Big Picture 
AI is reshaping telecom with tools like machine learning, chatbots, and infrastructure upgrades. By 2030, AI-driven apps will drive two-thirds of network traffic, requiring a six-fold bandwidth increase. Telecoms use AI to cut downtime by 20% and enhance customer service. Globally, firms like Ooredoo in Qatar optimize wireless networks, while India’s digital boom highlights AI’s role in managing bandwidth. AI’s energy use and workforce shifts—toward strategic roles—require careful planning. 

Segment 2: Telecom Strategies 
Telecoms are investing in 5G, fiber optics, and edge computing to support AI. By 2027, 87% of data centers will need 800 Gbps per wavelength, with ultra-high fiber cables meeting demand. Edge computing powers real-time AI, like Verizon’s traffic analysis or AT&T’s factory automation. Network as a Service (NaaS) offers on-demand connectivity and security. Telecoms are becoming AI enablers, with Verizon using AI to prevent fiber cuts via geospatial analysis. 

Segment 3: Technical Dive 
Trans-oceanic fiber cables, carrying 99% of global data, face pressure from AI’s data needs, driving upgrades to terabit speeds. AI optimizes cable traffic, predicts issues, and boosts resilience against threats like cable cuts. Security is critical, with AI monitoring cyber and physical risks. Sustainability efforts use AI to reduce carbon footprints, aligning with ESG goals. 

Segment 4: Enterprise Impact 
AI-driven bandwidth demands will surge, with core bandwidth up over 50% in five years. By 2030, two-thirds of traffic will be AI-driven, fueled by innovations like AI inferencing. 6G, offering 1 Tbps speeds, will enable futuristic applications. CIOs must integrate network strategies into AI Centers of Excellence to prepare. 

Closing Takeaways 
AI is telecom’s biggest game-changer, accelerating rapidly. IT leaders must baseline network capacity, plan for growth, and address security. Gary and Scott stress network representation in AI strategy to stay ahead. 

Comcast AI Updates  https://www.fierce-network.com/broadband/comcast-says-it-can-do-ai-better-its-fiber-competitors?utm_medium=email&utm_source=nl&utm_campaign=FN-NL-FierceNetworkBroadband&oly_enc_id=5667B8099934F3J 

Verizon AI Updates  https://www.fierce-network.com/broadband/verizon-digs-how-prevent-fiber-cuts-happening 

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

In this episode, hosts Gary and Scott explore how artificial intelligence will transform the global workforce over the next 3, 5, 10 years, and beyond, offering actionable insights for business leaders. In the next three years, AI is poised to displace 5 million routine U.S. jobs while creating 7 million tech-driven roles, reshaping industries like manufacturing and retail through automation and augmentation. By 2030, deeper integration could see 300,000 logistics positions vanish and 50,000 legal roles decline, yet high-skill jobs may grow 35%, highlighting a polarized labor market. Looking to 2035, productivity gains might cut traditional work hours by 40%—60 million U.S. jobs’ worth—redefining work itself, with emerging roles in AI governance (up 200%) and human-centric fields enduring. 

For students entering college in 2025, the hosts advise embracing interdisciplinary skills—pairing technical expertise with human insights—targeting fields like healthcare innovation, where salaries could rise 50% by 2030. Adaptability, global awareness, and practical portfolios are key to thriving in this AI-driven era. Technologically, multi-modal AI and advanced hardware will drive these shifts, enabling real-time optimization and generative design by 2035. 

Leaders are urged to assess AI’s current impact, pilot high-return initiatives, and invest in reskilling, aligning technology with long-term value creation—such as sustainability efforts yielding 15% premiums. This episode blends strategic foresight, technical depth, and practical guidance, equipping listeners to navigate the AI revolution with confidence. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

In this episode of The Macro AI Podcast, hosts Gary and Scott dive into The Prompt Studio Edge: Winning with AI in 2025, exploring how prompt studios are revolutionizing enterprise AI. These powerful platforms help businesses create, manage, and optimize AI prompts—turning chaotic experimentation into structured, scalable success. For leaders seeking to compete globally, prompt studios offer a game-changing edge.  

Gary and Scott break it down: Prompt studios like PromptLayer provide visual registries, A/B testing, and usage analytics, letting teams—from marketing to IT—craft precise AI interactions without coding. Real-world wins shine through—think Telstra slashing customer follow-ups by 20% or Coles speeding app rollouts 6x faster. Prompt studios amplify these gains, refining prompts to boost ROI in customer support, content creation, and beyond.  

Technically, they’re built with Python and JavaScript, integrating seamlessly via APIs into your AI stack—pulling data from CRMs or ERPs and pushing optimized outputs. Security? Covered. With SOC 2 compliance, on-premise hosting, and real-time risk flagging, tools like PromptLayer keep sensitive data safe, meeting GDPR and HIPAA standards for regulated industries.  

The hosts spotlight market leaders—PromptLayer ($50/month Pro), Helicone (free to 100,000 requests), and Langsmith—plus free starters like Prompthub. Their advice? Start small—automate a report, measure results, then scale with confidence.  

Balancing business strategy and technical depth, Gary and Scott show how prompt studios deliver secure, measurable value—your ticket to leading in the AI era. Tune in for actionable insights to transform your business in 2025!  

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

In this Episode, your AI Guides Gary Sloper and Scott Bryan discuss the resurgence of Data Center Colocation powering AI environments.  This change is driven by the financials of sustained, high-volume AI OPEX, where the predictable, long-term costs of owned infrastructure become more attractive, especially to the C-Suite.  

Additionally, for those static AI requirements, intellectual propriety developments, security and tighter governance, enterprises have opted to add or expand their hybrid cloud model with colocation.  

 However, this hybrid approach doesn't represent a complete cancel of cloud GPUaaS, as many organizations maintain a strategic mix, using colocation for baseline workloads while leveraging cloud elasticity for peak demands and specialized tasks.

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

The Macro AI Podcast: Roboforming Revolution – AI and the Future of Metal Shaping 
Hosts: Gary and Scott | Date: March 21, 2025  

Join Gary and Scott as they explore roboforming, an AI-powered revolution transforming metal shaping in manufacturing. This episode dives into how robotic arms, guided by AI and data, create complex metal parts without traditional dies—delivering precision, flexibility, and efficiency. From automotive prototyping to aerospace repairs, roboforming cuts costs, speeds innovation, and reduces waste, making it a game-changer for business leaders worldwide.  

Discover real-world use cases: the U.S. Air Force shaping fuselage parts, luxury carmakers crafting unique panels, and construction firms building smart bridges. The hosts unpack the tech—AI feedback loops, 7-axis robots, and predictive analytics—showing how it scales from startups to global factories. Looking ahead, roboforming’s future shines bright: wider adoption by 2030, autonomous smart factories by 2035, and even lunar manufacturing by 2040.  

For leaders, it’s about agility, data-driven leverage, and talent elevation. With players like https://machinalabs.ai/ (backed by Lockheed Martin and NVIDIA) leading the charge, and giants like KUKA and ABB in the mix, roboforming is redefining competition. Plus, blockchain could track parts transparently, boosting ESG narratives. Tune in for practical insights, technical depth, and a bold vision of manufacturing’s AI-driven future.  

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Join Gary and Scott on The Macro AI Podcast for Architecting AI: Why Knowledge Management Platforms Matter. They break down Knowledge Management Platforms (KMPs)—smart hubs that turn chaotic enterprise data into organized, actionable knowledge. For leaders, KMPs cut the 20% of time workers waste searching for info (McKinsey), boosting efficiency. Zappos slashes support costs 20% with a KMP-powered chatbot, while Delta gets planes flying faster with instant maintenance logs. Scott highlights Toyota’s supply chain wins—spotting bottlenecks early, saving millions.  

The duo debates build vs. buy: third-party KMPs (Bloomfire, Confluence) win with seamless integrations (Salesforce, SAP), scalability, and security (encryption, 99.99% SLAs), outpacing in-house efforts. Gary and Scott then unpack the tech: NLP with BERT models powers semantic search, knowledge graphs (Neo4j) connect data, and ML (LSTMs) keeps it fresh—all in a stack with vector databases (Pinecone) and microservices (Kubernetes) for sub-50ms latency. Capital One’s Eno chatbot (80% automation) and Siemens’ downtime cuts (15%) show it in action.  

KMPs architect AI success—structuring data for faster training, linking silos for insights, and scaling globally, like Shopify’s merchant support. Gary and Scott wrap with a playbook: audit your data, pilot a KMP, and scale. Whether you’re a strategist or a techie, this episode builds the case for KMPs as your AI foundation. Subscribe for more! 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary and Scott explore the dynamic legal landscape of AI and machine learning, offering business leaders worldwide a roadmap to navigate compliance and innovation. This episode spans global regulations, U.S. federal shifts, and state-level actions—packed with practical strategies and tech insights.  

Global AI Legislation: 
Gary starts with the EU’s AI Act (2024-2027), a risk-based law banning mass surveillance AI while enforcing audits for high-risk systems like hiring tools—fines up to €35M or 7% of global turnover. Scott details its tech demands: SHAP for audits, LIME for transparency. The EU’s chaotic trilogue birthed a deal balancing startups like Mistral with big-tech scrutiny. China’s 2023 rules mandate ideological AI and watermarking ($14M fines), while South Korea, Switzerland, and the UAE diversify the race. Gary urges scalable governance; Scott flags audits and APIs.  

U.S. Federal Government and AI: 
Scott notes that there is no federal AI law—FTC’s Section 5 ($2M chatbot fine) and Title VII tackle bias instead. Gary unpacks Trump’s Jan 20, 2025, EO, axing NIST’s risk frameworks to boost dominance, tied to Project Stargate’s $500B data center push (OpenAI, xAI). Defense AI surges, but Biden’s safety EO is out. Congress stalls—NO FAKES Act passes, accountability lags. Scott warns of agency curveballs; Gary pushes self-regulation with SHAP to dodge scrutiny.  

U.S. State-Level AI Developments: 
Gary highlights Colorado’s 2026 AI Act ($20K fines) for high-risk AI fairness tests. Scott dives into California’s 2025 laws—SB 1047’s deepfake ban ($10M fines) uses ResNet for detection, AB 2013 demands LLM transparency. Illinois protects teachers, New York audits lending, and Massachusetts’ H. 4123 targets 10 exaFLOP giants like Colossus for safety (misinformation risks). Gary touts TensorFlow Fairness for bias sweeps; Scott stresses modular policies and Dioptra testbeds.  

Gary and Scott close with a call to agility—embed compliance, leverage tech, and lead amid lawmaking chaos. Join the global conversation at macroaipodcast.com!  

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

n this Macro AI Podcast episode, hosts Gary and Scott explore why clean data is key to AI success, offering practical tips for business leaders and tech details for enthusiasts. They cover real-world examples, the cleaning process, and trends like synthetic data, equipping listeners to implement effective strategies. 

Why Clean Data Matters 

Clean data underpins reliable AI. Gary and Scott share examples: a retailer mismanaging inventory due to inconsistent location data, or healthcare errors from duplicate records. Dirty data—missing or inconsistent—leads to poor AI predictions and financial losses. For tech listeners, they know how it disrupts machine learning, affecting loss functions and model convergence, making quality data essential. 

The Data Cleaning Process and Industry 

The hosts outline a five-phase cleaning process: analyzing data, defining rules, verifying, transforming, and integrating. Big data’s volume and variety complicate this, but tools like Cleanix (parallel processing) and HoloClean (probabilistic inference) help. The data cleaning industry—engineers, scientists, and firms—is critical, with 40-50% of data budgets spent here. Leaders are urged to prioritize governance for quality. 

HoloClean:  http://www.holoclean.io/

Synthetic Data and Conclusion 

Synthetic data is highlighted as a fix when real data is limited, like simulating sensor data for self-driving cars. The episode wraps up stressing clean data’s role in AI success, offering steps to achieve it—invest in tools, talent, and explore synthetic options—making it a must-listen for leveraging AI. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Ready to supercharge your business with AI that’s smarter, faster, and grounded in your data? In this episode of The Macro AI Podcast, hosts Gary and Scott unpack Retrieval-Augmented Generation (RAG)—a game-changing approach that combines real-time data retrieval with powerful AI generation. Perfect for business leaders, this episode dives into how RAG transforms industries, from manufacturing to insurance and legal, with practical examples like slashing customer service times and speeding up claims processing by 40%.  

Why does RAG outshine standalone AI models? Scott explains how it taps into your proprietary info—like a retailer’s latest HR policies—delivers up-to-date answers, and cuts through AI “hallucinations” with secure, permission-based access. Gary breaks down the tech: prepping data in vector databases, retrieving context with embeddings, and generating spot-on responses. He also shares expert tips on measuring RAG’s performance—think “faithfulness” scores and retrieval tweaks—to ensure it delivers ROI.  

But it’s not all smooth sailing. Scott highlights challenges like data quality, retrieval relevance, and security, offering solutions like role-based controls and encrypted databases. Looking ahead, RAG’s future sparkles with multimodal capabilities (audio, video, images), global language support, and personalization. Ready to start? Scott’s got your back with practical steps—start small, pilot with tools like LangChain, and scale smart.  

Tune in to discover how RAG can make your business AI-ready—accurate, current, and competitive. Subscribe and join Gary and Scott every episode as they guide you through the AI era! 

What is RAG - Marina Danilevsky, Senior Research Scientist @IBM

https://www.youtube.com/watch?v=T-D1OfcDW1M

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

In this third episode of The Macro AI Podcast, hosts Gary Sloper and Scott Bryan explore the strategic implementation of AI governance through Centers of Excellence (CoE), providing a roadmap for organizations of all sizes to effectively harness AI capabilities. 

What is an AI Center of Excellence? 

The hosts define an AI Center of Excellence as a centralized hub that drives all artificial intelligence initiatives within an organization. This nerve center connects technical implementation with business objectives, ensuring AI projects align with company goals whether they focus on revenue growth, efficiency improvements, or enhanced customer experiences. 

A successful CoE brings together diverse talent across the business.

Models for Different Organizations 

The podcast outlines various CoE structures to fit different organizational needs: 

• Formal CoE: Dedicated departments with full-time staff, independent budgets, and leadership - typical in Fortune 500 companies and tech giants 
• Virtual CoE: Cross-functional teams drawing expertise from existing departments without creating new structural units - ideal for mid-sized organizations 
• Hybrid CoE: Small core teams of AI specialists supported by part-time contributors from across the organization - balancing focus with flexibility 
• Lean AI Approach: Targeted implementation focusing on high-impact use cases, often leveraging external partners or cloud-based tools - suitable for smaller businesses and startups 

Building an Effective AI CoE 

The hosts provide a step-by-step approach to establishing an AI Center of Excellence: 

1. Define Vision and Objectives: Connect AI initiatives directly to measurable business outcomes and align with company mission 
2. Assemble the Right Team: Combine AI technical expertise with business acumen, scaling appropriately for organization size 
3. Build Secure Infrastructure: Establish cloud platforms, networks, and security tools to protect AI systems from threats 
4. Set Governance Guidelines: Create clear policies for AI development and usage that ensure fairness, transparency, and regulatory compliance 
5. Start Small, Prioritize Security: Test concepts with low-risk projects before scaling to enterprise-wide implementation 
6. Cultivate Collaboration: Train the broader organization on AI fundamentals and secure executive support 
7. Measure and Adapt: Track meaningful metrics and continuously evolve the approach as technology advances 

Leadership Through AI Transformation 

The episode addresses the human challenges of AI adoption: 

• Communication: 
• Leading by Example: 
• Addressing Fears: 
• Fostering Innovation: 
• Setting Realistic Expectations: 

Competitive Strategies 

The hosts emphasize the importance of positioning AI as a competitive necessity: 

• Highlighting how competitors are already leveraging AI advantages 
• Sharing concrete examples of successful AI implementations 
• Engaging teams in brainstorming sess

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Exploring the emergence of AI agents that can take autonomous action in the workplace 

In this second episode of The Macro AI Podcast, hosts Gary and Scott dive into the revolutionary concept of "Agentic AI" - autonomous systems that don't just assist humans but can independently take action, make decisions, and transform how businesses operate. 

What is Agentic AI? 

The hosts define Agentic AI as systems that can reason, make decisions, and act independently within predefined guidelines - contrasting with traditional AI that merely reacts to human commands. Like comparing a simple GPS (which tells you where to go) to a self-driving car (which handles the entire journey), Agentic AI doesn't just provide insights but acts on them. 

Beyond Traditional Automation 

The episode clearly distinguishes Agentic AI from conventional automation: 

• Traditional automation (like RPA) follows strict rules but falters with complexity 
• Agentic AI adapts to changing circumstances, learns over time, and handles unpredictability 

Key Technology Components 

The podcast breaks down the core technologies driving this revolution: 

• Natural Language Processing for Human Interaction 
• Machine Learning & Reinforcement Learning for improved decision-making 
• Knowledge Graphs for Context Awareness 
• API integrations with business software 
• Multi-agent collaboration where specialized AI agents work together 

Real-World Applications 

The hosts explore compelling examples across industries: 

Finance & Banking: 

• End-to-end invoice processing that can verify, route, and even communicate with vendors 
• Real-time fraud detection that prevents issues before they occur 

Healthcare: 

• Automated claims processing that verifies eligibility and medical codes instantly 
• Personalized patient support through AI health assistants 

Customer Service: 

• Support systems that categorize, diagnose, and resolve issues without human intervention 
• Proactive problem-solving instead of reactive support 

Retail & E-commerce: 

• Advanced AI shopping assistants that curate personalized selections 
• Predictive inventory management that forecasts demand and automates reordering 

Human Resources: 

• AI-powered recruitment that generates job descriptions, screens candidates, and schedules interviews 
• Automated onboarding and employee engagement monitoring 

Enterprise Platform Leaders 

The episode highlights how major platforms are implementing Agentic AI: 

Salesforce: 

• Einstein GPT and AI Agents transforming CRM into autonomous business assistants 
• Systems that monitor client interactions, suggest actions, automate proposals, and even negotiate contracts 

ServiceNow: 

• Now Assist and ServiceNow AI Agents are revolutionizing IT service management 
• Proactive issue detection and resolution before problems are even reported 
• Automated HR processes for leave requests, reviews, and benefits questions 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Welcome to the inaugural episode of The Macro AI Podcast! Hosts Gary Sloper and Scott Bryan introduce their new series dedicated to exploring the rapidly evolving world of artificial intelligence and its transformative impact on businesses globally. 

Podcast Mission 

The Macro AI Podcast aims to serve as your comprehensive guide through the AI revolution, offering practical insights for business leaders, technology enthusiasts, and anyone curious about AI's growing influence. The hosts plan to cut through the hype, focusing on tangible applications and real-world implications of AI technologies. 

What to Expect 

Future episodes will navigate the complex AI landscape, exploring: 

• How AI is reshaping business operations and competition across industries 
• The balance between automation and human workforce development 
• Industry-specific applications from manufacturing to healthcare 
• The practical implementation of AI tools in everyday business contexts 
• Global perspectives on AI adoption and regulation 
• Success stories and cautionary tales from real-world AI deployments 

Content Preview 

Listeners can anticipate discussions on timely topics such as: 

• Supply chain automation and optimization 
• AI's role in transforming customer experiences 
• Predictive analytics and maintenance in manufacturing 
• Ethical considerations including bias prevention and privacy concerns 
• The explosion of generative AI tools and their business applications 
• How to navigate AI implementation challenges 

…and much more. 

The hosts will examine both technological innovations and broader implications, including government regulation, international AI competition, and the changing nature of work in an AI-augmented world. 

Coming Up Next 

The next episode will focus on "Rise of the AI Agents," exploring how autonomous AI systems are beginning to transform business processes. 

Audience Value 

Whether you're a CEO looking to integrate AI into your business strategy, a tech professional staying current with innovations, or simply curious about where AI is taking us, The Macro AI Podcast promises valuable insights delivered in an accessible, engaging format. 

Subscribe now to join Gary and Scott on this journey through the AI frontier, with new episodes released regularly to keep you informed on this rapidly evolving technological landscape. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/