Topic
12 facts from 1 episode, in date order. These are what speakers said on the shows, each linked to the moment it was said. They aren't independently verified.
2025
In McKinsey's annual CFO surveys, the share of respondents reporting AI investment in their finance function was 24% in 2023, 50% in 2024 and 65% in 2025, according to Davide Grande.
“In 2023, 24% of our participants said yes. In 2024, it was 50%, in 2025, 65%.”
2025
Davide Grande said that the share of surveyed CFOs actively using AI in finance rather than piloting it rose from 6% in 2024 to 51% in 2025.
“In 2024, 6% were active user, in 2025, 51%. So seven times increase in finance department.”
2030
Davide Grande cited McKinsey Global Institute modelling that digital technology activities are about 11% automatable now and could reach 53% by 2030.
“For example, digital technology is already automatable at 11%, and by twenty thirty, it will be at 53%, right?”
Undated
Davide Grande advised that every euro invested in AI should return ten times the investment.
“The most important part of this, I think, is whenever you do AI, be obsessed with value creation. Every euro invested in AI must return ten times the investment.”
Undated
Davide Grande said AI can move mergers and acquisitions from manual, time-consuming research to a programmatic approach that quickly identifies acquisition targets.
“In M A, we'll move from a contingent approach with manual time-consuming research to a programmatic approach where you can basically instantly find the best targets for M A”
Undated
Davide Grande said that in McKinsey's experience more than 50% of the time spent on strategic planning and control goes into creating reports that nobody reads and crunching data.
“according to our experience, more than 50% of the time of strategic planning and control is typically spent in creating reports that nobody reads, crunching data, et cetera.”
Undated
A highly efficient company combined data from more than fifty sources, including invoices, contracts, payments and operational data, to look for AI-driven cost savings, according to Davide Grande.
“why don't we leverage the data we have from more than fifty data sources, both financial data like invoices, contracts, payments, so not just numbers, but also PDFs”
Undated
Using AI on combined data, one client identified more than one hundred cost levers and reduced external costs by about 9-10%, according to Davide Grande.
“they have found more than one hundred leavers, and they they reduced external cost by 9%, nine to 10%.”
Undated
A client built an AI model that calculated the expected daily energy consumption of each branch, and the CFO's team received an alert when actual use exceeded it.
“they basically built an AI model where in each branch they would calculate every day of the year what is the statistically expected energy consumption.”
Undated
Davide Grande said the energy-monitoring AI model alone saved the client tens of millions of euros, at a time of high energy prices linked to the war in Ukraine.
“So that means only with this AI model, they saved tens of millions of euros.”
Undated
A client renegotiated IT help-desk contracts, winning 10% savings immediately and 15-20% in future contracts by arguing that suppliers' AI-driven productivity gains should be shared.
“And so they went there, hey, we're going to share this, these profits. And so they renegotiated 10% savings right away and fifteen to 20% savings in the future contracts.”
Undated
Davide Grande said some of his clients have invested hundreds of millions in building a perfect data platform and still not reached that goal.
“I've got clients that have invested hundreds of millions in building the perfect data platform, not getting there.”
Episodes