Rupali Kumbhani has a blunt read on where AI stands right now: we've spent two years proving AI works, and almost nobody's asked what happens once everyone has it. Same tools. Same models. Same vendors. So where's the advantage?

Rupali Kumbhani, a global transformation and innovation executive and C-suite advisor, joins Jackie Domanus to talk through what actually separates companies once the technology stops being the differentiator. She breaks transformation into four parts: technology, people, data, and process, and argues leadership is the only real variable left. She explains why one AI model should never be the one grading another AI model's output, using a story from her board role at Consequence Forum, where she chose to keep AI off the organization's artists' voices entirely to protect their authenticity. Jackie shares why she stepped away from AI completely to write her conversation card deck by hand, and how that led her to a simple rule: AI is not your customer.

They also get into the ”100% human” branding question, why token pricing won't stay this high, and what Rupali tells young professionals who think AI is coming for their job.

Listeners walk away with a clearer answer to a specific question: if the tools are the same, what isn't?

CHAPTERS

[00:00] Introduction and welcome[02:30] The AI sameness thesis[04:02] Are the AI models actually different[08:10] Data privacy and proprietary information[10:28] Best practices for early-stage AI strategy[12:52] Avoiding AI slop and keeping human judgment[17:23] Why AI isn't your customer[20:05] What good AI governance looks like at scale[23:47] Generational differences in AI adoption[28:54] When clients just relay what their AI said[30:02] Who the best leaders will be in the AI age[31:15] How to build these skills[33:46] Can a company market itself as ”100% human”[42:19] Predictions for where AI is headed[43:26] Is the current AI pricing sustainable[44:18] AI's impact in healthcare[46:10] Closing advice: fear, adaptability, curiosity