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The landscape of enterprise technology partnerships is evolving rapidly, and IBM stands at the forefront of this transformation. Nick Otto, who leads IBM's strategic partnerships after 20 years with the company, shares a compelling vision of collaboration that transcends traditional vendor relationships.

TLDR:

• IBM's partnerships with AWS, Microsoft, Adobe, Salesforce, Palo Alto, SAP, and Samsung focus on combining strengths to address market needs

What does it mean to orchestrate billion-dollar partnerships in today's AI-driven world? Nick takes us behind the scenes of IBM's relationships with tech giants including AWS, Microsoft, Adobe, Salesforce, Oracle, SAP, and Samsung. These aren't mere business arrangements—they represent a fundamental shift in how enterprise technology providers create value together rather than competing head-to-head.

The conversation reveals IBM's unwavering commitment to openness and client choice. Beginning with the hybrid cloud narrative that followed their Red Hat acquisition, IBM has consistently championed the philosophy of letting clients run workloads wherever they choose. This same principle now extends into the realm of AI, where IBM has made its Granite LLM capabilities available across multiple cloud platforms.

Perhaps most fascinating is IBM's approach to the emerging field of agentic AI. Instead of creating isolated capabilities, they're fostering bi-directional collaboration between their agents and those of partners like Salesforce and Oracle. This integration-focused strategy recognizes the reality that most enterprises are building complex technology ecosystems rather than single-vendor environments.

The strategic importance of cloud marketplaces emerges as another key theme, with IBM significantly expanding its presence on AWS and Azure platforms. With 70 software offerings across 89 countries on AWS alone, and plans to enable resellers across 22 new countries soon, IBM is meeting clients where they increasingly prefer to purchase technology.

Looking forward to the next phase of partnership innovation? Nick outlines three focal areas: deeper technology integration, continued support for hybrid approaches, and more creative commercial constructs. The goal remains consistent—helping clients solve problems their way, with the technologies they choose, delivered how they want them.

🎙️ Tune in as I speak with Nick at IBM Think 2025: https://obvs.ly/kieran-gilmurray2

#Think2025 #IBMPartner IBM IBM Partner Plus

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Curious about what AI agents really are and how they're reshaping automation? This deep dive cuts through the jargon to deliver precisely what you need to know about these powerful systems built on large language models. Well listen to AI explain AI.

TLDR:

• Three key components make an AI agent: an LLM as its brain, tools to interact with the world, and guardrails to ensure appropriate behaviour
• AI agents excel where traditional rule-based systems fail: complex decision-making, overly complicated rules, and processing unstructured data
• Start building with the most capable model to prove your concept, then optimize later with smaller, faster, cheaper options if needed
• Tools come in three types: data tools for fetching information, action tools for doing things, and orchestration tools for calling other agents
• Clear instructions are vital - leverage existing SOPs, prompt the agent to break down tasks, and anticipate edge cases
• Begin with simple single-agent systems before moving to multi-agent approaches like the manager pattern or decentralized pattern
• Implement layered guardrails including relevance checks, safety classifiers, PII filters, moderation tools, and risk-based controls
• Human intervention remains critical, especially for high-risk actions or when the agent struggles with certain tasks

We explore how AI agents fundamentally differ from traditional software by independently accomplishing tasks through their LLM "brain," specialized tools, and carefully designed guardrails. Rather than just following rigid rules, these systems can reason through complex problems, adapt on the fly, and make nuanced judgment calls – like having tiny specialized workers available 24/7.

You'll discover the three key scenarios where AI agents truly shine: handling complex decisions requiring judgment, replacing brittle rule systems that have become maintenance nightmares, and processing mountains of unstructured data. We break down the building blocks of effective agent design, from choosing the right model to crafting clear instructions and implementing proper safety mechanisms.

The conversation moves from simple single-agent systems to sophisticated multi-agent architectures, explaining when to use manager patterns versus decentralized approaches. We emphasize the critical importance of layered safety measures – from privacy protections to content moderation – and the continuing role of human oversight, especially for high-risk actions.

Whether you're just exploring the concept or actively looking to implement AI agents in your organization, this episode provides the clear, practical understanding you need to evaluate their potential and approach their development responsibly. The future of work is changing – are you ready to rethink what automation can accomplish?

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The future of business technology isn't some distant horizon - it's unfolding right now in Boston at IBM Think 2025. 

Our latest AI generated episode cuts through the hype to deliver the essential insights from digital transformation strategist Kieran Gilmurray's perspective on why this conference demands attention.

TLDR:

• IBM Partner Plus Day offers exclusive networking opportunities and actionable insights for growth
• The IBM Partner Zone facilitates strategic alliances that provide lasting competitive advantages
• Agentic AI is positioned as a current reality rather than future technology
• IBM Watson X Orchestrate sessions will demonstrate how AI agents enhance business workflows
• Real-world demonstrations from brands like Ferrari, HP, and UFC showcase practical applications
• Diverse speakers include IBM CEO Arvind Krishna and former NZ Prime Minister Jacinda Ardern
• Global networking opportunities connect over 5,000 professionals from more than 90 countries

Partner Plus Day:  The best ecosystem in tech. New partnerships. Big ideas. We begin by exploring the unique value of IBM's Partner Plus Day, where exclusive networking transcends typical conference interactions to forge strategic alliances with lasting competitive advantages. These connections aren't merely transactional—they're transformational, with regional discussions bringing together local expertise and global vision to address market-specific challenges.

Agentic AI is here:  2025 is the year AI teammates go mainstream and start driving businesses.  The technological heart of the conference beats with agentic AI—not as theoretical potential but as present reality. Gilmurray boldly declares 2025 may be "the year of AI agents," marking a pivotal shift from last year's focus on language models to practical AI implementations that enhance business workflows today. Equally crucial is the emphasis on data quality governance as the foundation for superior decision-making, paired with automation and hybrid cloud strategies that enable genuine business scaling.

Main stage mindset shifts and tech in action:  Real-world implementations from brands like Ferrari, HP, and UFC offer tangible proof of technology's impact, while an unexpected speaker line-up featuring both tech leaders and global figures like former New Zealand Prime Minister Jacinda Ardern promises multidimensional perspectives on leadership in the digital age. With over 5,000 attendees from more than 90 countries, the networking potential extends far beyond business cards to strategic connections that could shape your organization's future direction.

IBM Think 2025 

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The digital landscape has fundamentally shifted. Generative AI has moved beyond the realm of science fiction and corporate boardrooms into our most intimate spaces, reshaping how we approach not just productivity but our emotional well-being, personal growth, and daily routines.

TLDR:

• Examining how the report captures authentic AI adoption through analysis of public online conversations
• Discussing the shift from technical to personal uses, with emotional well-being applications rising to prominence
• Exploring "therapy companionship" as the top-ranked use case, providing empathetic responses and virtual friendship
• Highlighting how AI helps with self-reflection, finding purpose, and boosting confidence
• Analyzing practical applications for life organization, health management, and travel planning
• Investigating AI's impact on personalized learning and making complex topics accessible
• Looking at creative and recreational uses like generating memes, recipes, and troubleshooting everyday problems
• Considering how these evolving uses blur the lines between human help and AI assistance

Mark Zell Sanders' groundbreaking 2025 Top 100 Gen AI Use Case Report offers unprecedented insight into this transformation, capturing authentic usage patterns through analysis of public online conversations. Unlike hypothetical projections, this research reveals how real people are integrating AI into their lives in ways both surprising and profound.

The findings reveal a dramatic shift toward deeply personal applications. Topping the list is "therapy companionship," with users seeking emotional support and empathetic responses from AI. People report building confidence, finding purpose, and even processing trauma through AI-assisted reflection. One user with cognitive challenges poignantly shared that AI "saved my sanity," highlighting its emerging role as assistive technology for fundamental human needs.

Practical applications continue evolving as well. New categories like "organize my life" and "healthier living" demonstrate AI's expanding presence in daily management, while learning applications leverage AI's infinite patience and judgment-free environment to make complex topics accessible. From generating personalized travel itineraries to troubleshooting car problems, AI is becoming our digital Swiss Army knife for everyday challenges.

What does this transition from novelty to necessity mean for our relationship with technology? As the boundaries between human support and AI assistance blur further, how might these tools reshape our understanding of connection, learning, and personal development? Explore these questions with us as we examine the surprising ways generative AI is quietly weaving itself into the fabric of modern life.

Listen now to discover how AI's most impactful applications may not be what tech giants predicted, but rather what everyday users have organically discovered through their own ingenuity and needs.

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The landscape of artificial intelligence has transformed dramatically. What once seemed like science fiction—AI creating content from scratch—has quietly woven itself into our everyday lives in ways both surprising and profound. 

TLDR:

• AI for therapy and companionship ranks as the #1 use case, with users seeking emotional support and empathetic responses

• People are using AI as a thinking partner for deep personal questions, finding purpose, and boosting confidence
• Life organization applications include personalized schedules, health plans, and travel itineraries
• Enhanced learning through AI offers personalized education with "infinite patience" and judgment-free explanations
• Creative uses range from generating memes and jokes to suggesting recipes based on available ingredients
• Technical assistance for everyday problems empowers users to fix everything from audio settings to car parts

Mark Zell Sanders' 2025 Top 100 Gen AI Use Case Report offers a fascinating window into this evolution, not through hypothetical scenarios but by examining authentic online conversations about how real people are actually using these tools. 

The methodology itself speaks volumes—curating public discussions from platforms like Reddit provides insights that traditional surveys simply miss, capturing the genuine, unfiltered ways AI is being incorporated into daily routines.

What emerges from this deep dive is a remarkable shift away from purely technical applications toward deeply personal ones. "Therapy companionship" now ranks as the #1 use case, with people seeking emotional support, empathetic responses, and virtual companionship from AI. 

One user with a brain injury credited AI with "saving my sanity" by helping manage family interactions, brain fog, and memory problems. Others use AI as a thinking partner for self-reflection, exploring values, and navigating life paths—some even reporting tangible life changes like returning to education after these AI-facilitated introspections.

The practical applications are equally fascinating. Users create detailed life organization systems, personalized health plans, and custom travel itineraries. They leverage AI for judgment-free learning experiences, recipe suggestions based on available ingredients, and troubleshooting everything from audio settings to car repairs. Each example illustrates how generative AI is becoming less a specialized tool and more an integrated companion across multiple dimensions of human experience.

As you listen to these diverse examples, consider how the line between human assistance and AI support might continue to blur in your own life. What new possibilities—or challenges—might this present? We'd love to hear about your experiences with generative AI as this remarkable technology continues its rapid evolution.

Report: The 2025 Top-100 Gen AI Use Case Report.pdf 

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Unlock the transformative potential of AI agents in this deep-dive exploration of how LLM-powered systems are redefining what's possible in automation. We cut through the jargon and hype to reveal exactly what sets AI agents apart from conventional software – their ability to independently reason, orchestrate complex workflows, and make nuanced decisions without constant human guidance.

Discover the three essential building blocks that power effective agents: the LLM "brain" that drives reasoning, the tools that enable real-world actions, and the carefully crafted guardrails that ensure safe, reliable operation. We examine exactly where these systems deliver breakthrough value – in complex decision-making scenarios, situations with brittle rule systems, and workflows drowning in unstructured data.

Whether you're exploring potential applications or planning implementation, we provide practical insights on model selection, tool integration, instruction design, and orchestration patterns. Learn why starting simple with single-agent approaches often yields better results, and when to consider more sophisticated multi-agent architectures. Plus, discover the critical importance of layered safety mechanisms and thoughtful human oversight in creating responsible, effective systems.

As these powerful agents become more integrated into our workflows, they're not just changing how automation works – they're transforming our fundamental understanding of what work itself means. Ready to navigate this paradigm shift? Subscribe now to stay ahead of the AI revolution reshaping business and technology.

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We stand at the threshold of a new era in artificial intelligence—one where AI isn't just following instructions but actively thinking, reasoning, and working autonomously alongside humans. In this eye-opening conversation with Kieran Gilmurray, one of the top 50 global thought leaders in generative AI, we explore how agentic AI is fundamentally reshaping how businesses operate and engage with customers.

TLDR:

• The evolution from RPA to intelligent automation to agentic AI that can think and reason
• Agentic AI creates digital avatars capable of emotionally intelligent customer interactions in 111 languages
• The concept of "one-person, billion-dollar company" enabled by teams of specialized digital workers
• Challenges with AI adoption include skill shortages and cultural resistance to technological change
• The critical importance of high-quality, structured data for effective AI implementation
• Generative Engine Optimization (GEO) as the next frontier beyond traditional SEO
• Businesses must prepare for "machine customers" as AI agents increasingly make buying decisions
• Technology should work for humans, not control them – maintaining human agency is essential

Kieran walks us through the evolution from basic automation to today's sophisticated AI agents that function as digital co-workers capable of handling complex, end-to-end processes. He paints a vivid picture of how these technologies are enabling "one-person, billion-dollar companies" through teams of specialized digital workers that can perform everything from customer service to financial operations with remarkable efficiency and emotional intelligence.

The conversation takes a fascinating turn when Kieran introduces Generative Engine Optimization (GEO)—a critical shift in digital strategy as consumers increasingly bypass traditional search engines in favor of AI interfaces. This requires businesses to completely rethink their approach to digital visibility, focusing on structured data and authoritative content that AI systems can easily incorporate into their responses.

Throughout our discussion, Kieran balances optimism about AI's potential to amplify human capabilities with practical advice about managing risks like deepfakes and data mismanagement. His perspective is refreshingly nuanced—acknowledging legitimate concerns while emphasizing how these technologies can free humans to focus on creative, fulfilling work rather than repetitive tasks.

Whether you're a business leader wondering how to implement AI responsibly, a marketer grappling with the changing landscape of digital visibility, or simply curious about how these technologies will shape our future, this conversation offers valuable insights into preparing for a world where humans and intelligent machines work together to achieve extraordinary results. As Kieran puts it, "We can have everything, and why shouldn't we aim for that?"

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When AI goes wrong, who pays the price? Our deep dive into recent research uncovers the troubling realities behind AI privacy breaches and ethical failures that affect millions of users worldwide.

TLDR:

• Research analyzed 202 incidents tagged as privacy or ethical concerns from major AI incident databases
• Four-stage framework covers the entire AI lifecycle: training, deployment, application, and societal impacts
• Nearly 40% of incidents involve non-consensual imagery, deepfakes, and impersonation
• Most incidents stem from organizational decisions rather than purely technical limitations
• Only 6% of incidents are self-reported by AI companies, while the public and victims report 38%
• Current governance systems show significant disconnect between actual harm and meaningful penalties
• Recommendations include standardized reporting, mandatory disclosures, and stronger enforcement
• Individual AI literacy becoming increasingly important to recognize and resist manipulation

Drawing from an analysis of over 200 documented AI incidents, we peel back the layers on how privacy violations occur throughout the entire AI lifecycle—from problematic data collection during training to deliberate safeguard bypassing during deployment. Most concerningly, nearly 40% of all incidents involve non-consensual deepfakes and digital impersonation, creating real-world harm that current governance systems struggle to address effectively.

The findings challenge common assumptions about AI incidents. While technical limitations play a role, the research reveals that organizational decisions and business practices are far more influential in causing privacy breaches than purely technical failures. Perhaps most troubling is the transparency gap: only 6% of incidents are self-reported by AI companies themselves, with victims and the general public being the primary whistleblowers.

We explore the consequences ranging from reputation damage to false accusations, financial loss, and even wrongful arrests due to AI misidentification. The research highlights a critical disconnect between the frequency of concrete harm and the application of meaningful penalties—suggesting current regulations lack adequate enforcement teeth.

For professionals and everyday users alike, understanding these patterns is crucial as AI becomes increasingly embedded in our daily lives. The episode offers practical insights into recognizing manipulation, protecting personal data, and joining the conversation about necessary governance reforms including standardized incident reporting and stronger accountability mechanisms.

What role should you play in demanding transparency from the companies whose algorithms increasingly shape your digital experience? Listen in and join the conversation about creating a more ethical AI future.

Research Study Link

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What happens when AI doesn't just create, but acts autonomously? Kieran Gilmurray, CEO of Kieran Gilmurray Company and Limited & Chief AI Innovator, takes us beyond generative AI into the realm of agentic systems that can plan, adapt, and operate with minimal human guidance.

TLDR:

• Generative AI creates content while agentic AI takes action and makes decisions autonomously
• Knowledge is becoming freely accessible, challenging the traditional model of hiring and training junior professionals
• Organizations face strategic choices between automating roles or augmenting human capabilities
• The human-technology partnership remains essential, with AI handling routine tasks while humans develop uniquely human skills
• Leaders must learn to manage hybrid teams comprising both human and digital labor
• Emotional intelligence, curiosity, and communication skills become increasingly valuable as technical tasks are automated
• Organizations need adaptive mindsets and structures to thrive in an environment where competitive advantages may last months rather than years
• The goal should be creating AI-native intelligent businesses with people at their core, not replacing humans

As knowledge becomes freely accessible through AI for mere dollars per month rather than years of training, organizations face profound questions about their workforce structures. 

• Do we still need junior staff when AI can perform their tasks? 
• How do we balance human and digital labor? 

Kieran shares a striking example of how a business professor compressed what would have been 12 weeks of team research into just 2.5 hours using a customized AI system, producing results the client couldn't believe weren't human-generated.

Despite these capabilities, Kieran emphasizes that the most successful approach isn't replacement but augmentation: "Great people plus great technology equals an even greater result." 

While AI handles routine tasks, humans should develop their uniquely valuable skills—emotional intelligence, curiosity, cognitive flexibility, and communication.  Leaders must learn to orchestrate hybrid teams of humans and digital workers, setting appropriate metrics and creating meaningful career paths in this new environment.

The most forward-thinking organizations will move beyond simply adding AI to existing processes and instead fundamentally reimagine how they deliver value. These "AI-native intelligent businesses" will combine intelligent processes, people, and technology to create frictionless experiences for customers. As technology becomes easier to copy and competitive advantages shrink from years to months, an organization's true edge will be its ability to build adaptive teams that combine human creativity with technological capabilities.

Ready to navigate this rapidly evolving landscape? 

Listen now to discover how you can thrive alongside AI rather than be replaced by it.

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Generative AI isn't merely accelerating workplace productivity—it's fundamentally reconstructing how value is created, expertise is defined, and organizations develop. My conversation with enterprise strategy expert Andreas Welsch reveals the profound shifts happening beneath the surface of today's AI revolution.

TLDR:

• 75-90% of C-level executives believe their companies approach AI strategically while only 33-50% of employees agree
• AI delivers up to 43% productivity gains and boosts work quality for 68% of users
• Employees can reach 60-80% expert-level performance in new tasks with AI assistance
• Less than 10% of companies have deployed Gen AI across five or more functions
• Successful AI scaling requires aligning with business strategy and measurable KPIs
• Viewing AI as a cybernetic teammate rather than just a tool changes how we implement governance
• The biggest risk for businesses is not adopting AI at all
• Start by auditing existing tech stack for AI features already available from vendors

We unpack the dangerous disconnect between C-suite confidence and workforce reality: while 75-90% of executives believe their AI approach is strategic, barely half their employees agree. Andreas exposes the critical misconception that "AI doesn't apply to our business," asserting instead that AI's relevance spans every function—the key lies in discovering where it creates meaningful value for your specific context.

The transformation extends beyond the impressive statistics (43% productivity gains, enhanced work quality for 68% of users) to something more fundamental: AI is democratizing expertise. Employees can now perform at near-expert levels in unfamiliar domains within days rather than the traditional "10,000 hours" of practice. This doesn't eliminate the need for deep expertise but fundamentally changes how we think about team composition and skill development.

Perhaps most fascinating is the conceptual shift from viewing AI as a tool to seeing it as a cybernetic teammate, particularly as agentic AI emerges. This perspective change demands new governance frameworks—Andreas suggests we might look to existing human resource practices rather than reinventing the wheel. The greatest risk for leaders isn't implementing AI poorly but failing to implement it at all, as competitors capture value and markets transform around them.

Ready to transform how your organization approaches AI? Discover practical strategies in Andreas Welsch's AI Leadership Handbook and learn how to align technology with your business strategy for measurable outcomes that drive real competitive advantage.

Links to Andreas content:

https://www.intelligence-briefing.com 

https://www.aileadershiphandbook.com 

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

Podcast: “What’s the BUZZ?—AI in Busine

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📕 Buy my book 'The A-Z of Generative AI - A Guide to Leveraging AI for Business' - The A-Z of Generative AI – Digital Book Kieran Gilmurray