AI is only as reliable as the data it’s trained on, and that includes the worst parts of the internet. This episode unpacks how misinformation, bias, and human behavior show up in AI responses. It also reinforces why human oversight is critical in every AI-driven decision.

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AI doesn’t fail because of the technology. It fails because of broken relationships between business and IT. This episode explores why alignment, communication, and shared understanding are essential to building AI that actually works.

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Building your own AI sounds appealing until you understand what it truly requires. This episode breaks down the real investment in data, engineering talent, and architecture needed to make it work. It also challenges whether full control is worth the complexity and responsibility that comes with it.

Watch the full episode here: https://youtube.com/live/eijnXSAk8qw 

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The build versus buy decision becomes even more critical with AI, especially in regulated or high-risk environments. This episode explores how to evaluate vendors, when in-house development makes sense, and what it really means to own your AI systems. It also breaks down how use case, risk, and internal capability should drive the decision.

Watch the full episode here: https://youtube.com/live/eijnXSAk8qw 

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Not all data should be handed to AI, and knowing the difference is critical. This episode breaks down how to decide what AI can safely support versus what must remain protected to preserve competitive advantage. It also highlights the importance of human oversight and clear boundaries in AI adoption.

Watch the full episode here: https://youtube.com/live/eijnXSAk8qw 

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Copilot is rapidly becoming the default in many organizations, but is that because it is the best tool or simply the safest bet. This episode explores how familiarity, ecosystem lock-in, and perceived security are shaping AI adoption decisions. It also challenges whether “safe” technology choices actually drive real value.

Watch the full episode here: https://youtube.com/live/eijnXSAk8qw 

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Data quality is often assigned to one team, but in reality, it belongs to everyone who creates and uses it. This episode explores why shared ownership without structure leads to poor governance and inconsistent data. It also breaks down how organizations can create accountability without turning data into a free-for-all.

Watch the full episode here: https://youtube.com/live/eijnXSAk8qw 

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AI is only as effective as the data behind it. This episode explores why clean, consistent data matters more than complex architecture and how poor data quality limits AI’s ability to deliver value. It also breaks down the importance of shared ownership and strong governance to make AI actually work in practice.

Watch the full episode here: https://youtube.com/live/eijnXSAk8qw 

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Experimenting with AI is easy, but creating real value requires focus and intention. This episode explores why organizations need to commit to specific tools, align AI to clear business outcomes, and move beyond endless testing. It also breaks down how choosing the right platform can accelerate meaningful operational results.

Watch the full episode here: https://youtube.com/live/eijnXSAk8qw 

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KPIs are meant to guide decisions, but when data definitions are inconsistent, they can create confusion instead of clarity. This episode explores how misalignment between teams, poor communication, and unclear AI strategies can amplify problems across the organization. It also highlights how technology can make things worse when the business and IT are not operating in sync.

Watch the full episode here: https://youtube.com/live/hVY5T2MQbWw 

Connect with me on LinkedIn https://www.linkedin.com/in/kylercheatham/ 

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