A revolutionary study has uncovered unexpected truths about our growing relationships with AI chatbots, revealing complex patterns that challenge conventional wisdom about human-AI interactions.  

Listen in as Google NotebookLMs AI voice generated agents talk to this excellent piece of research.

TLDR:

• Nearly 1,000 participants exchanged over 300,000 messages with GPT-4 across nine different interaction conditions
• Using chatbots generally reduced feelings of loneliness but also led to less socialization with real people
• Longer daily usage consistently linked to negative outcomes including increased loneliness and emotional dependence

Diving deep into data from nearly 1,000 participants who exchanged over 300,000 messages with GPT-4, we explore the fascinating psychological effects of daily chatbot use. The results paint a nuanced picture: while AI interactions generally reduced feelings of loneliness, they simultaneously led to decreased real-world socializing. Most notably, longer daily usage consistently predicted negative outcomes across all interaction types – a finding that should give us pause as these technologies become increasingly embedded in our lives.

The study's most surprising revelation challenges our assumptions about voice versus text interactions. While voice-based chatbots initially seemed to produce better psychological outcomes, these benefits disappeared or even reversed with extended use. Meanwhile, text interactions showed higher emotional engagement and more supportive AI responses than their more human-sounding counterparts. Even more unexpectedly, using AI for practical, factual conversations – rather than personal ones – was linked to greater emotional dependence with prolonged use.

Four distinct interaction patterns emerged from the research, from "socially vulnerable" users who form emotional bonds with AI to "casual" users who maintain healthy boundaries. Your own characteristics – from pre-existing loneliness to how you perceive the AI – significantly influence which pattern you might fall into and what psychological effects you'll experience.

As we navigate this new frontier of digital relationships, these findings raise critical questions about responsible AI design and usage. How can we harness the benefits of these technologies while preserving genuine human connection? The balance we strike today may shape the future of our social wellbeing in an increasingly AI-integrated world.

What patterns do you recognize in your own AI interactions? Share your thoughts and join the conversation about finding healthy boundaries with our digital companions.

Link to research: How AI and Human Behaviors Shape Psychosocial Effects of Chatbot Use: A Longitudinal Randomized Controlled Study

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What happens when AI doesn't just respond to prompts but takes initiative, makes decisions, and collaborates with other AI agents to solve complex business problems? Simon Torrance, a global authority on business transformation with over three decades of experience, opens our eyes to the revolutionary world of agentic AI – and why it matters right now.

TLDR:

• AI with agency can make independent choices, take actions, and solve complex problems
• Agentic AI differs from automation by creating end-to-end solutions rather than just following processes
• Five key elements of an agent: LLM capability, persona, reasoning ability, memory, and action capability
• Leaders should understand the technology, develop a strategy, and identify high-value, low-risk areas to start
• Approximately 50% of knowledge worker roles will be disrupted by agentic AI
• Mental model shift: recognizing AI can do work we currently believe only humans can do

Forget what you thought you knew about automation. 

Agentic AI represents a fundamentally different capability: artificial intelligence with genuine agency that can act independently, reason through problems, and execute solutions without human intervention. 

As Simon explains, this technology allows organizations to create synthetic workforces that can dramatically expand operational capacity at a fraction of the cost of human teams.

The examples Simon shares are nothing short of remarkable. A team of 20 AI agents completing complex risk analysis in one hour that would take human consultants six weeks. Ten AI agents running an entire insurance operation – brainstorming on Slack, managing claims, ensuring compliance – and delivering higher customer satisfaction than human teams. These aren't future possibilities; they're happening now with technology that's already a year old.

For business leaders, the implications are profound. The strategic risk isn't just falling behind technologically – it's being outcompeted by rivals who triple their operational capacity while slashing costs. 

Simon makes a compelling case that we're approaching a watershed moment where AI capabilities will match or exceed human cognitive abilities in many domains within the next decade. This requires a fundamental shift in how we think about work, organizational structure, and competitive strategy.

Ready to explore how agentic AI could transform your organization? 

Then lets chat - ☎️ FREE introductory meeting: https://calendly.com/kierangilmurray/30min

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The educational landscape is rapidly evolving with AI tools, but what does the evidence actually tell us about ChatGPT's effectiveness in learning environments? Moving beyond the hype and confusion, we dive deep into a ground breaking meta-analysis that examined 51 different research studies conducted between 2022-2025.

Listen in as Google NotebookLMs voice generated podcast hosts explain.

TLDR:

• ChatGPT shows large positive impact on learning performance (effect size 0.867)
• Greatest impact on critical thinking occurs in STEM fields when ChatGPT acts as an intelligent tutor
• Effectiveness depends on thoughtful integration by educators
• Works best when designed to support deeper learning rather than providing quick answers

The results are striking. Students using ChatGPT showed significant improvements in learning performance with an effect size of 0.867 – considered large in educational research. The impact on learning perception and higher-order thinking skills was moderate but still consistently positive. When we examine where ChatGPT shines brightest, the patterns become clear: skills-based courses saw the strongest positive effects, while problem-based learning environments (effect size 1.113) created the ideal conditions for ChatGPT to enhance student performance.

Timing matters too. Performance benefits peak during 4-8 weeks of use, suggesting a sweet spot between the initial learning curve and potential over-reliance. Interestingly, positive attitudes toward learning continue to grow the longer students use ChatGPT. For developing critical thinking skills, STEM fields benefit most, especially when the AI functions as an intelligent tutor rather than a passive tool.

These findings have profound implications for how we think about AI integration in education. ChatGPT demonstrates effectiveness more than double that of traditional AI assessment tools previously studied, pointing to its versatility as both a learning assistant and potential tutoring companion. However, thoughtful implementation remains essential – the technology works best when deliberately structured to support deeper learning rather than simply providing quick answers.

How can educators and students leverage these insights? Consider strategic implementation in problem-solving contexts, especially for skills development and STEM subjects. Use ChatGPT as an interactive tutor rather than a passive reference tool when possible, and be mindful of optimal duration periods. Beyond the technology itself, these findings invite us to reconsider what uniquely human elements of education become even more crucial as AI tools continue to evolve.

Listening to this episode and want to try implementing these evidence-based strategies yourself? We'd love to hear about your experiences using AI in learning environments – share your thoughts and join the conversation!

Link to research: The effect of ChatGPT on students’ learning performance, learning perception, and higher-order thinking: insights from a meta-analysis 

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The promise of generative AI is tantalizing – better quality work, produced faster and with less effort. But what happens when that efficiency comes at the cost of something vital: our intrinsic motivation?

TLDR:

• AI-assisted work produces better quality outputs - longer, more analytical performance reviews and warmer, more personable emails
• When AI handles cognitive heavy lifting, we miss out on the satisfaction of solving problems ourselves
• People feel reduced ownership and control when AI generates content, leading to disengagement
• This motivation dip persists even when returning to non-AI tasks
• Organizations risk workforce disengagement, higher turnover, and potential skill stagnation
• Blend AI and human contributions rather than letting AI produce final outputs
• Design engaging solo tasks to counterbalance AI-assisted work
• Make AI collaboration transparent to maintain sense of partnership
• Rotate between AI-assisted and independent tasks throughout the workday
• Train employees to use AI mindfully, developing critical evaluation skills

Drawing on fascinating research involving over 3,500 participants, my AI agents (non human Google Notebook LM) dive into this compelling tension at the heart of workplace AI adoption. The data reveals a striking pattern: while AI collaboration significantly improves performance metrics (think more analytical performance reviews and warmer, more effective emails), it simultaneously triggers a roughly 20% drop in intrinsic motivation and a similar rise in feelings of boredom.

We explore the psychology behind this motivation decline, examining how AI can inadvertently hijack the cognitively demanding aspects of work – the very parts that often provide the greatest sense of accomplishment and ownership. When AI handles the heavy mental lifting, we lose those satisfying moments of wrestling with problems and finding solutions. This disengagement doesn't just affect AI-assisted tasks; it lingers even when we return to independent work.

For organizations embracing generative AI, these findings offer crucial guidance. Rather than avoiding this powerful technology, the research points to five specific strategies for thoughtful integration: blending AI and human contributions, designing engaging solo tasks, maintaining transparency about AI's role, rotating between AI-assisted and independent work, and training employees to use AI mindfully as partners rather than passively accepting its output.

Ready to harness AI's productivity benefits without sacrificing engagement? Listen now to discover how you can find the sweet spot where technology enhances rather than diminishes your sense of purpose and satisfaction at work.

Research: https://hbr.org/2025/05/research-gen-ai-makes-people-more-productive-and-less-motivated

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Ever feel buried under emails, alerts, and to-do lists that seem to have lives of their own? That productivity paradox—being frantically busy yet accomplishing little of real value—sits at the heart of our exploration into Agentic AI.

Google Notebook LMs agents tell the story for us. 

TLDR:

• Self-directed artificial intelligence learns your patterns and anticipates needs
• Reclaims significant time by handling email management and scheduling complexities
• Functions as an intelligent information filter, cutting through digital noise
• Creates personalized learning experiences that adapt to individual learning styles
• Serves as a creative collaborator for writing, design, music, and other creative pursuits
• Enhances health management through personalized monitoring and preventative insights 

Unlike traditional AI that passively waits for commands, Agentic AI functions as an autonomous collaborator. These self-directed systems understand context, reason independently, and take initiative toward achieving your goals without constant supervision. Through reinforcement learning and sophisticated language models, they develop the ability to adapt to new situations and devise creative solutions. The result? Technology that genuinely works for you rather than demanding perpetual management.

The practical applications are transformative across multiple domains. For productivity, imagine email agents that intelligently prioritize messages, schedulers that eliminate booking complexities, and systems that handle digital paperwork automatically—potentially reclaiming hours of your week for deep work. As information filters, these AI companions learn your preferences to deliver personalized content briefs rather than forcing you to wade through irrelevant noise, whether for news, research, or social connections.

The personalization extends further into education, where AI tutors analyze individual learning patterns and adjust delivery methods to match your specific style—visual, auditory, or kinesthetic. For creativity, they serve not as replacements but as digital muses, offering unexpected ideas or starting points while you maintain creative direction. In health and accessibility, the impact could be profound: from preventative health insights based on subtle biometric patterns to real-time assistive technologies that provide unprecedented independence for people with disabilities.

What would you do with a genuinely intelligent digital partner that understood your needs, preferences, and goals? How might it transform your productivity, learning, health, and home environment? The potential is extraordinary, but realizing it requires thoughtful implementation guided by strong ethical principles. Subscribe now to join our ongoing exploration of how emerging technologies can enhance human potential and create more fulfilling lives.

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The technological revolution is here, and it's powered by artificial intelligence. In this riveting conversation with AI expert Kieran Gilmourie, we explore the urgent need for businesses to embrace AI technologies before competitors leave them behind.

TLDR:

• AI is being rapidly adopted across all business sectors, company sizes, and government departments worldwide
• European companies need strong AI policies to compete globally and maintain knowledge economy advantages
• When using public AI models like ChatGPT, protect sensitive data by turning off training features and avoiding sharing confidential information
• No profession is entirely immune to AI disruption - from therapy to art, law to healthcare
• Technology should handle automatable tasks, freeing humans to focus on areas where they uniquely add value
• Continuous learning and adaptability are essential skills for thriving in an AI-powered workplace
• Rather than diminishing human connection, AI can enhance it by removing mundane tasks and expanding creative possibilities

"For the love of goodness, can every Irish business please grasp this as quick as they can?" Kieran urges, highlighting that companies across every sector and level are rapidly investing in AI capabilities. This isn't a wait-and-see scenario – organisations implementing AI are experiencing transformative improvements in productivity, creativity and competitive positioning.

We take a global perspective, examining how different regions approach AI adoption and regulation. While the US leads in investment and China follows closely, smaller nations like Saudi Arabia are making remarkable strides by integrating AI across government services and business operations. Europe's regulatory approach aims to balance innovation with necessary guardrails – what Kieran describes as maintaining "infinite pace and infinite patience" simultaneously.

The conversation turns practical with essential tips for using public AI models safely. From turning off training features to exercising discipline with sensitive information, Kieran provides actionable guidance for protecting intellectual property while still leveraging powerful tools like ChatGPT. He explains why effective prompting techniques dramatically improve AI outputs, comparing these systems to brilliant interns who need clear direction to deliver their best work.

Perhaps most thought-provoking is our exploration of AI's impact on traditional roles. Kieran challenges the notion that certain professions are immune to disruption, suggesting that continuous adaptation is the only sustainable strategy. "Concentrate on the bits that are uniquely you," he advises, urging listeners to embrace lifelong learning while allowing technology to handle automatable tasks.

Far from diminishing human creativity or connection, Kieran believes AI enhances our humanity by removing the mundane: "Let the technology take the robot out of us so that we can be the most human we have been in the last 50 or 70 years."

Ready to transform how your organisation leverages AI? Subscribe today and join the conversation about leadership in the age of artificial intelligence.

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The legal profession stands at the threshold of transformation as generative AI reshapes how lawyers work. But how do you harness this technology effectively? The secret lies in mastering prompt engineering—the art and science of crafting instructions that guide AI to produce valuable legal outputs.

TLDR:

• Generative AI represents an unprecedented shift in how lawyers work, with Microsoft's legal team reporting 32% faster task completion and 20% better accuracy
• Legal applications span contract review, dispute resolution, litigation support, M&A due diligence, regulatory compliance, and client communications
• Start experimenting with these techniques on your own work to discover practical applications and efficiency gains

Microsoft and the Singapore Academy of Law just released a 30+ page guide on using GenAI in legal practice.

 Our AI generated conversation dives deep into the recently published guide "Prompt Engineering for Lawyers," extracting actionable insights for legal professionals eager to leverage AI without getting bogged down in technical complexity. We explore the four fundamental pillars of effective prompting: crafting clear goals, providing rich context, setting explicit expectations, and referencing specific sources.

The potential benefits are substantial. Microsoft's legal team reported tasks completed 32% faster with 20% better accuracy when using AI tools properly. From contract review and litigation support to regulatory compliance and client communications, we walk through real-world examples of prompts tailored for different legal scenarios. Each example demonstrates how thoughtfully constructed instructions can yield powerful results across practice areas.

Yet we don't shy away from critical ethical considerations. The discussion emphasizes that AI serves as a co-pilot, not autopilot—the lawyer always bears ultimate responsibility for the work product. We address essential questions about client confidentiality, data security, and the importance of verification when working with AI-generated content.

Whether you're already experimenting with AI tools or just beginning to explore their potential, this episode provides a practical foundation for developing this increasingly essential legal skill. Start applying these prompt engineering techniques today and discover how they can elevate your practice while freeing you to focus on the strategic work that truly requires your expertise.

Read my top ten prompts for legal professionals - here

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The dizzying pace of AI development has sparked fierce debate about automation in the workplace, with headlines swinging between radical transformation and cautious scepticism. What's been missing is concrete, objective evidence about what AI agents can actually do in real professional settings.

TLDR:

• The Agent Company benchmark creates a simulated software company environment to test AI agents on realistic work tasks
• AI agents must navigate digital tools including GitLab, OwnCloud, Plane, and RocketChat while interacting with simulated colleagues
• Even the best-performing model (Claude 3.5 Sonnet) only achieved 24% full completion rate across all tasks
• Surprisingly, AI agents performed better on software engineering tasks than on seemingly simpler administrative or financial tasks
• Common failure modes include lack of common sense, poor social intelligence, and inability to navigate complex web interfaces
• Performance differences likely reflect biases in available training data, with coding having much more public data than administrative tasks
• The gap between open source and closed source models appears to be narrowing, suggesting wider future access to capable AI systems

The Agent Company benchmark offers that much-needed reality check. By creating a fully simulated software company environment with all the digital tools professionals use daily—code repositories, file sharing, project management systems, and communication platforms—researchers can now rigorously evaluate how AI agents perform on authentic workplace tasks.

The results are eye-opening. 

Even the best models achieved just 24% full completion across 175 tasks, with particularly poor performance in social interaction and navigating complex software interfaces. 

Counterintuitively, AI agents performed better on software engineering tasks than on seemingly simpler administrative or financial work—likely reflecting biases in available training data.

The specific failure patterns reveal fundamental limitations: agents struggle with basic common sense (not recognizing a Word document requires word processing software), social intelligence (missing obvious implied actions after conversations), and web navigation (getting stuck on routine pop-ups that humans dismiss without thinking). 

In one telling example, an agent unable to find a specific colleague attempted to rename another user to the desired name—a bizarre workaround that highlights flawed problem-solving approaches.

For anyone trying to separate AI hype from reality, this benchmark provides crucial context. While showing meaningful progress in automating certain professional tasks, it confirms that human adaptability, contextual understanding, and social navigation remain essential in the modern workplace.

Curious to explore the benchmark yourself? Visit theagentcompany.com or find the code repository on GitHub to join this important conversation about the future of work.

Research:  THEAGENTCOMPANY:  benchmarking llm agents on consequential real-world tasks 

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Ever felt like you're drowning in a sea of tasks while nothing truly gets done? Agentic AI is here to change that. Unlike conventional AI systems that simply respond to commands, these digital agents function as autonomous collaborators—understanding your needs, anticipating problems, and executing tasks independently within boundaries you set.

TLDR:

• Unlike regular LLMs that wait for prompts, agentic AI can function independently within defined boundaries
• Automating mundane tasks like email sorting and scheduling gives back hours for creative problem-solving
• AI agents can enhance creativity by offering inspiration and collaboration in writing, design, and music
• Responsible development focusing on ethics and privacy is essential for agentic AI to reach its full potential

Agentic AI represents a revolutionary approach to reclaiming your most precious resource: time. By handling mundane tasks like email management, scheduling, and data entry, these systems free up your mental bandwidth for creative problem-solving and strategic thinking. They function as personalized information filters, cutting through the noise to surface only what matters to you, turning information paralysis into focused clarity.

But the true power of agentic AI extends beyond productivity. These systems transform how we learn through personalized educational experiences that adapt to individual strengths and learning styles. They serve as creative partners, offering inspiration for writers, artists, and musicians without replacing human ingenuity. In healthcare, they provide proactive monitoring and personalized wellness recommendations, while accessibility features make technology more inclusive for people of all abilities. Even our living spaces become more responsive through smart home agents that learn our routines and preferences.

The future isn't about humans versus machines—it's about thoughtful collaboration that enhances our capabilities while respecting our autonomy. With careful guidance and a commitment to ethical principles, agentic AI can help us build richer, more intentional lives where technology truly serves human flourishing. Ready to experience what happens when AI works for you, not the other way around?

Read this chapter in full: Agentic AI: Your Personalized Power-Up for a Better Life

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The rise of AI agents marks one of the most significant technological shifts of our era. What once lived in science fiction has emerged as a powerful market force, reshaping customer interactions, internal processes, and business models across industries.

TLDR:

• The global AI market is projected to grow from $214.6 billion in 2024 to $1.3 trillion by 2030
• Key market trends include deeper personalization, integration with broader ecosystems, edge computing, and ethical considerations
• Google, Microsoft, Amazon, IBM and Pega lead the market with comprehensive solutions and ecosystem integration
• Future developments will feature enhanced personalization, edge computing capabilities, and more explainable AI systems

These sophisticated systems—from conversational assistants to autonomous decision-makers—represent the convergence of advances in machine learning, natural language processing, and cloud computing. They're fundamentally changing how organizations operate by automating previously human-dependent tasks with unprecedented intelligence and adaptability.

This comprehensive exploration takes you deep into the AI agent ecosystem, examining what these systems are and how they function. We break down the core technologies driving this revolution and showcase real-world applications that demonstrate their practical impact. From Google's Duplex making natural-sounding restaurant reservations to IBM Watson transforming healthcare diagnostics, these examples illustrate how AI agents are already embedded in our daily lives and business operations.

The competitive landscape reveals fascinating dynamics between tech giants like Google, Microsoft, and Amazon alongside innovative startups bringing specialized solutions to market. Regional differences highlight how European companies prioritize regulatory compliance while Asian markets accelerate consumer-facing AI adoption, and North American firms maintain their edge through strategic controls on critical technologies.

Looking ahead, we examine how enhanced personalization, edge computing capabilities, and integration with emerging technologies will define the next wave of AI agent evolution. The shift toward value-based pricing models and increased focus on explainable AI signal important changes in how these systems will be deployed and monetized.

For forward-thinking leaders, the message is clear: embracing AI agents requires both technological understanding and strategic vision. Organizations that align AI initiatives with broader business objectives while addressing ethical considerations will gain significant competitive advantages in this rapidly evolving landscape. The question isn't whether to adopt these technologies, but how to implement them in ways that drive genuine value while maintaining transparency and trust.

Full article: The Agentic AI Ecosystem: Market Trends and Future Outlook 

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