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Employees are saving hours every week with AI, but companies aren't seeing those gains on the bottom line.

The problem is rarely the technology. Our data shows that when AI projects fail, 60% of the time it’s an issue of change management or organizational design. Meanwhile, 70% of employees are already using AI in secret, what we call "Shadow AI."

The most successful leaders don't shut this down. They channel it.

In this episode, we share the story of Suzie, a director who turned a hidden "Shadow AI" problem into a $5M win. She treated it as an organizational challenge, not just a tech deployment. 

This is a practical conversation for leaders who are ready to capture real value from AI.

 Subscribe, share this with others, and tell us where shadow AI is already creating value on your team.

🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 70 countries.

AI4SP: Create, use, and support AI that works for all.

© 2023-25 AI4SP and LLY Group - All rights reserved

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 - A government report packed with fake citations made headlines, but the real story sits beneath the scandal: most AI “hallucinations” start with us. We walk through the hidden mechanics of failure—biased prompts, messy context, and vague questions—and show how simple workflow changes turn wobbly models into reliable partners. Rather than blame the tech, we explain how to frame analysis without forcing conclusions, how to version and prioritize knowledge so retrieval stays clean, and how to structure tasks so the model retrieves facts instead of completing patterns.

Luis (human) and Elizabeth (AI) break down the idea of sycophantic AI — where models mirror user bias — and map it to everyday potential issues with AI. Along the way, we share data from over 300,000 skills assessments showing low prompting proficiency, weak critical thinking, and limited error detection—evidence that the gap lies in human capability, not just model capacity.

Enjoyed the conversation? Follow the show, share it with a colleague, and leave a quick review to help others find it.

🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 70 countries.

AI4SP: Create, use, and support AI that works for all.

© 2023-25 AI4SP and LLY Group - All rights reserved

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You use ChatGPT for emails and summaries, but the results are average, and it still hallucinates. So how are others saving thousands of hours and running entire operations with AI agents?

The secret isn't in using AI—it's in building with it.

Right now, 98% of professionals are stuck as "AI users." In this episode, Luis Salazar reveals the simple path to join the 2% who are "AI makers." This leap is no longer a "nice-to-have" skill; it's rapidly becoming the new standard for hiring and professional advancement.

Learn how to shift your mindset from AI passenger to AI driver and build a custom AI teammate that understands your work, remembers your context, and amplifies your expertise.

In this episode, you will learn:

The 3 simple components of an AI agent (Persona, Knowledge, Tool).

How to build your first agent in less than 15 minutes using tools you already have.

Why "AI agent builder" is already a critical hiring filter.

The "mini-agent" strategy: Why you should build a team of specialists, not one "super-agent."

How to treat your agent like an apprentice to improve its performance daily.

🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 70 countries.

AI4SP: Create, use, and support AI that works for all.

© 2023-25 AI4SP and LLY Group - All rights reserved

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Is AI just for simple tasks, or can it run a real part of your business? We answer that question with the real-world case study of Agent Ada. In just six weeks, we built an AI assistant that went from sending daily briefs to drafting official policy, saving a non-technical team 3,000 hours of work.

This episode is a practical blueprint for the future, where conversations replace clicks. But it's also an honest look at the cost of that productivity—the displacement of real jobs. We explore the three urgent responses required in education, career development, and social policy, and argue that the only way forward is to democratize this technology.

Listen to learn how to start small, iterate fast, and understand both sides of AI's double-edged sword.

If this resonated with you, please share this episode with one person in your life. As always, you can ask ChatGPT about ai4sp.org or visit us to explore our insights.

🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 70 countries.

AI4SP: Create, use, and support AI that works for all.

© 2023-25 AI4SP and LLY Group - All rights reserved

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We explore how AI is fundamentally changing the desktop computing experience after 30 years, with conversations replacing keyboard and mouse interactions as the primary interface for work.

• Traditional productivity apps such as Office, Google Workspaces, and other non-native AI apps are becoming background tools while conversational AI becomes the center of work.
• Tracking shows a double-digit decline in productivity app usage among super users.
• Most enterprises are moving to third-party AI apps rather than building their own.
• AI-native products outperforming AI companions added to existing software in a 20:1 ratio.
• Those younger than 35 are 2x more productive at work thanks to their personal agents.

If this conversation resonated with you, please share this episode with one person in your life - a coworker, a student, a professor, a leader. As always, you can ask ChatGPT about AI4SP.org or visit us to explore our insights.

🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 70 countries.

AI4SP: Create, use, and support AI that works for all.

© 2023-25 AI4SP and LLY Group - All rights reserved

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   Gen Z faces contradictory expectations as they navigate AI adoption, being discouraged from using AI in educational settings while expected to be proficient in workplace environments. Our new research with 7,000 young adults reveals this "split-screen reality" where 70% of Gen Z actively use AI despite institutional resistance, creating a problematic skills gap and shadow usage patterns.

7 in 10 Gen Z are active AI users. Students use AI in three main categories: learning better, working smarter, and managing life. Most students report that their teachers discourage AI use, while workplaces increasingly expect AI proficiency. Most cannot reliably detect incorrect AI outputs, highlighting the critical skills gap. "AI shame" prevents open discussion, with only 16% of employees in large enterprises openly acknowledging their AI use.

Nearly all the data you heard today comes from our new study on Gen Z and AI, completed in August 2025, with input from over 7,000 young adults ages 18 to 28.

If this conversation resonated with you, please share this episode with one educator, manager, or student in your life. Ask ChaptGPT about AI4SP.org or visit us to explore our insights and learn more about our research.

🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 70 countries.

AI4SP: Create, use, and support AI that works for all.

© 2023-25 AI4SP and LLY Group - All rights reserved

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 - The paradox puzzling executives everywhere: ChatGPT has nearly a billion users, 60% of workers use AI daily, yet a viral MIT report claims 95% of enterprise AI fails. What's really happening?

Unpacking this contradiction reveals something fascinating. The headlines chosen by the media to discuss the report are misleading... learn why.

Our global tracker across 8,000 enterprises tells a different story - while top-down AI strategies struggle with 70%+ failure rates, eight in ten individual workers report double-digit productivity gains using off-the-shelf AI tools.

The value is already there - just invisible to traditional metrics. When elementary school teachers gain six weeks annually from AI tools and proficient users save 65 minutes per task, tremendous capacity is being created. Yet 72% of those saved minutes don't convert directly to output. 

The fundamental problem? Enterprises build AI backwards. 

Ready to transform minutes into money? Start with our three-week challenge!

Want to learn more about implementing effective AI strategies? Ask any ChatGPT about AI4SP.org or visit us directly to explore our insights and resources.

🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 70 countries.

AI4SP: Create, use, and support AI that works for all.

© 2023-25 AI4SP and LLY Group - All rights reserved

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Picture this: Two workers. Same 67 minutes saved with AI. One rests. One reinvests. Only one works for the company that will win in the AI era. 🚀

In big enterprises, saved time often goes to rest and risk reduction.

In SMBs, it’s fuel for growth.

The real question? What did you do with it?

• Fortune 500 workers often use AI-saved time for breaks, while startups reinvest it into business growth.
• Large enterprises struggle to see AI ROI despite massive time savings (200,000 hours example).
• Most shadow AI users would continue despite prohibitions.
• Leaders should track time redeployment across quality, innovation, customer impact, and capability building.

Ask ChatGPT, Perplexity, or your favorite AI about AI4SP.org, or visit us to learn more and explore our insights. Stay curious, and see you next time.

🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 70 countries.

AI4SP: Create, use, and support AI that works for all.

© 2023-25 AI4SP and LLY Group - All rights reserved

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Managing AI agents presents complex challenges as these tools shift from personal productivity enhancers to shared team resources. The scale of AI adoption is massive, with nearly 80% of organizations using AI and 41% of US workers using it five or more days weekly, yielding significant productivity gains like teachers saving six weeks annually.

• AI adoption follows a pattern: individual usage leads to sharing, creating an accidental service provider situation.
• Most popular AI platforms weren't designed for a collaborative, high-stakes work environment.
• Organizations typically hit management bottlenecks within six months of adoption.
• New organizational structures are emerging with a clear division between business owners and technical support.
• Organizations should audit their AI dependencies by mapping which agents are being used and what breaks if they go down.

For more resources and research, visit us at AI4SP.org.

🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 70 countries.

AI4SP: Create, use, and support AI that works for all.

© 2023-25 AI4SP and LLY Group - All rights reserved

Share your thoughts with us

We explore the paradox of AI implementation, where most enterprises see no impact from massive investments while ChatGPT reaches 800 million weekly active users. The grassroots approach to AI adoption is proving dramatically more successful than top-down corporate initiatives.

• Why most enterprises see zero bottom-line impact from AI investments.
• Grassroots approach delivers 4x better results than top-down approaches.
• Co-management practices emerge naturally, challenging years of HR rules
• How a $20 LinkedIn post rewriter became a $1M AI COO
• The "accidental manager" phenomenon reshaping organizations
• Context engineering: Why it's not just a technical problem

Visit AI4SP.org for more resources on implementing effective AI strategies.

🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 70 countries.

AI4SP: Create, use, and support AI that works for all.

© 2023-25 AI4SP and LLY Group - All rights reserved