Describe your career to date
I was an early data and analytics adopter, beginning with USAF mission readiness KPIs to modern, artificial intelligence (AI)-fueled client data insights. I have had an exciting career journey, watching the data management and analytics profession evolve over time. My teams and I have led strategic data transformation programs that created scaled capabilities like data quality as a service and data anonymization as a service that delivered outsized business value.
I have been a part of the Chief Data Officer cohort since the early days, and I am active in advancing women leaders in data and AI.
What challenges do you see for data in the year ahead that will have an impact on your clients and on the industry as a whole?
As a member of KPMG’s Data Citizens with Purpose, Women Leaders in Data and AI (WLDA@KPMG), and the Chief Data Officer and Information Quality (CDOIQ) Symposium initiatives, we activate data literacy through hands-on data and analytics philanthropy, speaker series, and data leadership content. We are bringing KPMG Trusted AI to our clients.
How are you developing the data literacy of a) your own organization and b) your clients?
We are building our foundational data capabilities following the KPMG Trusted AI principles and ethical pillars. Our data and analytics strategy focuses on client and auditor experience, while modernizing our data management and analytics capabilities to deliver trusted data and insights.
How are you preparing your organization and your clients for AI adoption and change management?
AI adoption requires understanding, ideation, and business value alignment. My team and I provide workshops, strategy sessions, podcasts, and tools to educate executive teams and CDAO teams to prioritize use cases based on data readiness, value, and cultural fortitude.
Aligning the data and AI strategy to the business strategy is a key ingredient to our change management framework that includes communication, incentives, skills, and community. Companies of all sizes are eager to become genAI-powered, and require governance, transparency, and trust.
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