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The challenge of innovation

· Fabio Panetta, Governor of the Banca d'Italia (Italy)

Summary written by Dark Majestic in its own words · topics: financial stability, trade, fragmentation and geopolitics, growth, investment and productivity, technology, ai and cyber risk

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· Fabio Panetta Wiki · Banca d'Italia WikiThe challenge of innovation

ContextAddress by Fabio Panetta, Governor of the Bank of Italy, at the 10th Annual Research Conference of the National Bank of Ukraine and the National Bank of Poland “Central banks response to future challenges: resilience, credibility, and innovation”, Kyiv….

Why it mattersSpoken in Kyiv, this speech links war, economic coercion and technology to one question: how central banks stay credible and independent under heavy pressure.

Problems raised
  1. Wars and geopolitical fragmentation make the economic environment more volatile.
  2. Economic and financial dependencies are being used as weapons.
  3. Fast technological change challenges how central banks keep their credibility.
Solutions proposed
  1. Protect central bank independence and the capacity to act under pressure.
  2. Build resilience, learning from Ukraine's central bank experience.
  3. Adapt to innovation rather than resist it, to stay credible.
Read the speech summary

1. Credibility tested in two ways

In Kyiv, at a research conference jointly organised by the Ukrainian and Polish central banks, the Governor of the Bank of Italy expressed solidarity with Ukraine and argued that central bank credibility sometimes requires standing firm and sometimes adapting. Geopolitical conflict tests the first quality; artificial intelligence and digitalisation test the second.

2. Lessons from the hryvnia

Ukraine's currency turned thirty in 2026. After the 2014-15 crisis, when it lost over half its value and banks were restructured, the National Bank of Ukraine adopted inflation targeting, a more flexible exchange rate and risk-based supervision. These reforms allowed it to keep monetary and financial stability after the 2022 invasion: inflation passed 26%, the policy rate went to 25%, banks kept working and inflation later fell. A new four-year IMF programme approved in February 2026 recognised this record, while alignment with EU banking rules progressed. The lesson is that credibility is accumulated in calm times and proven in extreme ones.

3. AI and the economy

Generative AI is spreading faster than personal computers or the internet did. Central banks must understand it, both as an analytical tool and as a force changing the economy. In the short run, AI investment lifts demand and prices for computing power, energy and specialised staff. In the long run, productivity gains could be large; Bank of Italy research suggests more than one extra point of annual labour productivity growth for Italy. Such a supply gain would normally mean more growth and lower inflation, but its timing and size are uncertain and it also affects incomes and spending.

4. Demand, inequality and gaps between countries

Should AI chiefly generate new kinds of work and lift expected wages, households may spend more and inflation could last longer; if it mainly replaces workers, precautionary saving could bring disinflation sooner. The outcome will be uneven across workers and firms, possibly favouring large companies. Central banks will therefore need to know who gains, not only how much. Between countries, the United States leads in AI investment, which widens its trade deficit and draws foreign money into its stock market, while Europe lags but could still catch up through adoption. Faster adopters may win lasting productivity and market share, with possible swings in exchange rates whose direction is hard to predict.

5. Consequences for policy

The effect of AI on the neutral interest rate is ambiguous: faster productivity pushes it up, while inequality, extra saving or a larger capital share pull it down. Stock valuations built on optimistic AI profits leave room for abrupt corrections. He therefore recommended pragmatism, giving observed demand, activity and inflation more weight than estimates of unobservable variables, and investing in skills and models.

6. Supervision and payments

AI can improve credit scoring, fraud detection and risk control, but common models or a few technology suppliers could spread errors across the system, so supervisors need deeper technical knowledge. New payment providers raise efficiency but also complexity and cyber risk. The two-tier system, in which public money issued by the central bank anchors the private services built on it, should be adapted rather than abandoned. Stable prices, a sound financial system and public confidence in money stay the foundations.

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