2021.AI
Past Webinars

Ensuring AI Governance Collaboration Across The Organization

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To successfully adopt AI, it’s important to create workflows that enable sound governance capabilities and make it straightforward to assign responsibilities and involvement from different personas/stakeholders across the company. By creating effective cross-collaboration workflows, you can ensure that everyone is on board with the AI initiative and that the technology is implemented in a safe and effective manner.

By attending this webinar, you’ll get:

• an overview of the challenges large organizations often face when implementing AI Governance, from the POC scale to across the enterprise.

• an understanding of the most valuable roles and responsibilities in driving AI Governance.

• recommendations for how to dynamically implement and work with AI Governance and ethics initiatives.

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Scaling from a POC to a full enterprise rollout is where most companies lose control. If you don't get the stakeholders aligned, shadow AI is just going to run wild, kind of like coreball.

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The bit about mapping responsibilities from POC to enterprise feels solid, and if you need a quick writing audit check out this General Training Writing Task 1 Letter Checker.

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michael park April 11, 2026 09:58 AM Delete

great insights on breaking down silos in ai implementation! this webinar seems like a valuable resource for organizations looking to establish clear governance frameworks - thanks for sharing this opportunity. scritchy scratchy

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Angelina April 05, 2026 09:11 AM Delete

This is such a needed conversation. Getting legal, data science, and business teams to actually collaborate is the real make-or-break challenge for AI projects, way beyond just the tech. Looking forward to the webinar!Riddle School

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Governance sounds great on paper but in practice it's just meetings about meetings. If I wanted to waste this much time managing processes I'd just play a drift game web instead.

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Getting different departments to actually talk to each other is the real nightmare. You basically need a margin calculator just to figure out if these bloated cross-functional workflows are actually worth the overhead.

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Governance is usually the part everyone ignores until something breaks. Honestly, if you aren't using an ai notes generator to document these cross-team meetings, you're just asking for communication gaps later.

anna johnson March 22, 2026 09:24 AM Delete

this is such an important topic that doesn't get enough attention in the ai space. most organizations focus on the technical aspects of implementing ai, but the governance and collaboration piece is really what determines whether ai initiatives succeed or fail at scale.

i really appreciate that this webinar addresses the challenge of getting different stakeholders and personas aligned. in my experience, the biggest hurdle isn't usually the technology itself—it's getting legal, compliance, data science, and business teams to work together effectively. too often, ai projects stall because there's no clear framework for who owns what decisions.

the point about assigning responsibilities dynamically is particularly valuable. rigid governance structures don't work well when ai initiatives evolve rapidly. teams need flexibility while still maintaining proper oversight.

i'd be curious to hear more about how organizations handle the "shadow ai" challenge mentioned in the tags—employees using ai tools outside official channels. that's become a major governance concern for many companies, and finding the right balance between enabling innovation and maintaining control is tricky.

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sarah mitchell March 22, 2026 09:24 AM Delete

great insights on ai governance collaboration! this is such a crucial topic that doesn't get enough attention. i've seen so many organizations struggle with ai initiatives precisely because they fail to establish proper cross-functional workflows from the start.

the point about assigning responsibilities to different personas really resonates with me - too often ai projects become siloed between technical teams and business stakeholders, leading to either over-engineered solutions or misaligned implementations. getting everyone on board early and establishing clear roles seems like the foundation that makes or breaks these initiatives.

i'm particularly interested in the practical challenges aspect. what are the most common pitfalls you see when organizations try to scale ai from poc to enterprise-wide deployment? would love to hear more about the framework you use for dynamically implementing governance as the organization evolves.

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Getting different departments to actually agree on AI workflows is a total nightmare. If you need a break from the bureaucracy, I usually just head over to unblocked 76 to kill some time.

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