What’s Working (and What’s Not) in AI - 2025 Edition
As 2025 comes to a close, many organizations are realizing that AI success wasn’t driven by flashy tools or massive transformations—it was driven by people.
In this episode of The Conversation with Model Mind AI, Angela Schultz and Loren Horsager reflect on what actually worked in AI adoption over the past year. As tools like Microsoft Copilot improved and became more accessible, AI stopped being theoretical. Employees began experimenting, asking better questions, and finding small wins that created real momentum.
One of the biggest pitfalls discussed is the temptation to assign AI to a single expert. While appealing on the surface, this approach often limits adoption. Instead, the most successful organizations focused on raising AI literacy across teams—empowering people closest to the work to identify opportunities and drive change.
The conversation also reinforces why AI should not be treated like a traditional IT project. Large rollouts often failed, while fast prototypes and short experiments helped teams assess value quickly and avoid costly mistakes.
Through real client examples, Angela and Loren show how practical, tailored AI use cases delivered meaningful results—and why this people-first mindset sets the stage for 2026.
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What Actually Worked with AI in 2025-and What Didn’t
As AI tools rapidly evolved in 2025, many organizations found themselves caught between excitement and confusion. New capabilities appeared constantly, yet meaningful results didn’t always follow. In this conversation, Angela Schultz and Loren Horsager unpack what truly made a difference—and what consistently fell short.
Access Changed the Conversation
One of the biggest shifts in 2025 was access. As tools like Microsoft Copilot improved, employees across organizations were finally able to experiment with AI in their daily work. This moved conversations from theory to application.
AI Adoption Is About Raising the Floor
Rather than relying on a single AI expert, successful companies focused on bringing everyone along. Small wins shared across teams created momentum, confidence, and curiosity.
Why Traditional IT Rollouts Failed
Large, top-down AI initiatives often struggled. Treating AI like a standard IT project ignored how dynamic and contextual these tools are. Fast experiments proved far more effective.
Practical Wins Drove Real Value
From marketing workflows to CRM automation, the most impactful solutions were specific, practical, and built by people who understood the business.
Looking Ahead to 2026
As the episode closes, the focus turns to agents, memory, and deeper integrations. The tools will keep improving, but the lesson from 2025 is clear: people drive AI success.