Have you had to make any organizational changes to effectively scale your AI initiatives? If so, what did you do, or what are you considering?

Innovation & Emerging Trends Scalability

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SVP Digitalization R&D and Data Science in Manufacturing8 months ago

We have not made any organizational changes yet. Currently, we are running a corporate initiative to establish AI cases across the entire company (specific & broad cases). For this, we utilize the existing data & AI teams (AI platform, data foundation, data semantics, AI enablement, governance, etc.), supported by external partners. After the initiative, we might adjust the organization if requierd.

Director of IT in Educationa year ago

At this point, we haven't made any significant organizational changes. We've started by distributing AI tools like Copilot and ChatGPT-Edu among select faculty, students, and staff, encouraging them to become creators and innovators within their own roles. Our approach is to foster a culture where everyone can innovate within set parameters, without necessitating structural changes to the organization at this stage.

We've leveraged the enthusiasm for AI within our existing teams by forming volunteer groups, known as the AI Alliance. These groups are composed of individuals passionate about AI across various departments, focusing on learning and sharing AI knowledge internally. This strategy allows us to utilize internal resources without the immediate need for external hiring.

Director of Systems Operations in Healthcare and Biotecha year ago

Yes, our organization has established a dedicated AI development and analytics team, along with an AI Governance committee. This team is responsible for evaluating AI criteria and expanding our capabilities into areas like cybersecurity, ensuring our AI models are secure. We are also enhancing our cloud infrastructure to support these AI models and handle large data securely.

1 Reply

no titlea year ago

Unlike Rasheen, we don't have a dedicated team. Instead, any business unit or legal entity must submit AI-related requests to our AI governance team for evaluation. This process helps us centralize and control AI initiatives before moving forward.<br><br>

Global Digital Workplace Sr. Director, Global Technology & Security in Healthcare and Biotecha year ago

We have set up a comprehensive governance framework and introduced responsible AI practices. We've started hiring for new roles such as AI UX designers, AI architects, and training specialists to support our AI initiatives. Our approach integrates cybersecurity resources into AI, reflecting our commitment to secure and responsible AI deployment.

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How frequently do you grapple with the intricate task of harmonizing the metrics utilized to gauge the success of AI initiatives with the fundamental aspirations of your organization, bearing in mind the potential pitfalls of Goodhart's Law? -----Goodhart's Law, coined by economist Charles Goodhart, asserts that when a measure becomes a target, it ceases to be a good measure. This principle underscores the complexities of using metrics for evaluation, particularly in AI development.-----

Routinely - Aligning AI metrics with our organizational goals often proves to be a nuanced endeavor, fraught with challenges stemming from the principles elucidated by Goodhart's Law.31%

Occasionally - While I encounter periodic hurdles in aligning metrics with organizational objectives, the implications of Goodhart's Law are not always at the forefront of these challenges.47%

Rarely - The task of aligning AI metrics with organizational objectives is typically straightforward, with minimal consideration given to the potential distortions highlighted by Goodhart's Law.18%

Never - I have not encountered significant difficulties in aligning AI metrics with organizational goals, nor have I encountered issues related to Goodhart's Law.4%