Almost everyone is investing in AI and automation. Far fewer have made it stick.
75% of executives admit their AI strategy is "more for show" than real guidance. In audit only 25% of internal auditors actively use AI while 50% are still stuck piloting. This panel gets honest about why adoption stalls, and what actually moves it.
Arpit Shah, Head of Audit Data, AI and Technology Solutions at DTCC, led his department's journey - from first experiments to embedded, everyday analytics use. He'll share what actually shifted daily practice.
Jamie Crossman-Smith, Founder & Principal of BlochAI, has spent 20 years inside financial-services risk and audit - Deloitte, Lloyds Banking Group, Grant Thornton, with clients including the Bank of England, Citigroup, and Barclays. He's seen the adoption gap play out across dozens of regulated firms, and built his practice around what separates the ones that stick from the roughly 95% of AI projects that get scrapped.
What you'll walk away with:
Why adoption stalls on skills, trust, and data - not the model
How to work with imperfect data instead of waiting for perfect
How governance can give people confidence to adopt, instead of acting as the brake
What separates the projects that stick from the ones that get scrapped
A concrete move you can make next quarter, not just the case for change
Moderated by Knime's Corey Weisinger, bring your questions for the panel.
75% of executives admit their AI strategy is "more for show" than real guidance. In audit only 25% of internal auditors actively use AI while 50% are still stuck piloting. This panel gets honest about why adoption stalls, and what actually moves it.
Arpit Shah, Head of Audit Data, AI and Technology Solutions at DTCC, led his department's journey - from first experiments to embedded, everyday analytics use. He'll share what actually shifted daily practice.
Jamie Crossman-Smith, Founder & Principal of BlochAI, has spent 20 years inside financial-services risk and audit - Deloitte, Lloyds Banking Group, Grant Thornton, with clients including the Bank of England, Citigroup, and Barclays. He's seen the adoption gap play out across dozens of regulated firms, and built his practice around what separates the ones that stick from the roughly 95% of AI projects that get scrapped.
What you'll walk away with:
Why adoption stalls on skills, trust, and data - not the model
How to work with imperfect data instead of waiting for perfect
How governance can give people confidence to adopt, instead of acting as the brake
What separates the projects that stick from the ones that get scrapped
A concrete move you can make next quarter, not just the case for change
Moderated by Knime's Corey Weisinger, bring your questions for the panel.