Could you share personal insights or resources on what part of the business organization is standing up AI capability? Is it in Data, or Tech, or another part?
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VP, Distinguished Fellow, & Chief Architect in Healthcare and Biotech8 months ago
We have business based data science teams that work together with technology to implement AI capabilities. This allows us to dance at the leading edge of science AND scale quickly when something is yielding business value. CIO in Education4 months ago
Those business data science teams are functionally connected to IT or business area?
VP, Distinguished Fellow, & Chief Architect in Healthcare and Biotech4 months ago
The data science headcount sits in the business. They pair up with engineers from IT (data engineering, software engineering, platform engineering, etc.).
Global Intelligent Automation Manager in Healthcare and Biotech8 months ago
Using Automation and GenAI together solves:1. GenAI has a cost - Using automation for the big data pulls or system grabs etc. is cheaper than using tokens.
2. GenAI Hallucinations… Use Automation to pull, create, and normalize datasets to create Grounding.
3. GenAI is dangerous in users, employees, and especially outside customers or bad actors.
So use your automation platform to drive your LLM. Automation to prompt, to navigate, to move the outputs and control and monitor the data sources. All without user interaction.
Director of IT8 months ago
Multiple organizations are driving adoption of AI capabilities. For example, lines of business are pursuing AI solutions to their problems in collaboration with Legal, Technology, Privacy, and Data Governance, e.g. x-ray classification, while Technology is leading adoption of AI-enabled platforms and shared services, such as enhanced collaboration and communication capabilities. Governance and oversight of AI adoption is provided by a cross-functional committee with representatives from all major risk owners.CTO8 months ago
In our organization (Atalan Tech), our AI capability is core to our product and therefore it is developed as a collaboration between Product, Data, Science/Research and Engineering . We believe this cross-functional approach to be fairly standard and necessary to have a successfully leverage AI in our products and services. We are a health tech start-up focused on clinician wellbeing and retention. Director of HR4 months ago
Who is, and who should be are an interesting set of questions. When you think about the intersectionality of human and machine (AI) and what that means for the future of work, then the HR department should definitely be a big part of this conversation. But it seems they're not. It seems it sits often in the Automation/IT/Data space. Come on HR practitioners - it's time to take some of the reins here!