Europe’s AI moment: AWS’s view from the inside

Europe’s AI moment: AWS’s view from the inside

AI

2 feb 2026

This image features a large, illuminated AWS logo set in an urban, glass building environment during dusk, capturing the essence of modern technological advancement; perfectly reflecting Europe’s AI moment with AWS’s involvement.
This image features a large, illuminated AWS logo set in an urban, glass building environment during dusk, capturing the essence of modern technological advancement; perfectly reflecting Europe’s AI moment with AWS’s involvement.

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In a McKinsey interview published 30 January 2026, AWS EMEA chief Tanuja Randery says Europe’s AI adoption is accelerating — five businesses a minute are adopting AI and uptake rose ~30% last year. The big unlocks now: clearer, consistent regulation, closing the digital-skills gap, and better late-stage capital.

Europe’s AI moment: 5 takeaways from AWS’s Tanuja Randery

Why this matters now
In a new interview with McKinsey & Company (30 January 2026), Tanuja Randery sets out a confident picture of Europe’s AI trajectory — and a blunt to-do list for leaders. Adoption is surging (“five businesses every minute”), up roughly 30% year on year, but scale will hinge on regulation, skills and capital.

1) Adoption is real — and broadening beyond pilots

Randery describes a European market moving faster than many assume, spanning enterprises, digital natives and start-ups. McKinsey’s piece quotes two punchy stats: five new AI-adopting businesses per minute and a near-30% annual rise in adoption. The “why” is shifting from cost savings to growth and innovation.

2) The value pool is big — if Europe moves quickly

Citing internal and ecosystem research, she points to $400bn of potential gen-AI value for Europe, rising to ~$3tn when broader cloud and digital are included. Those figures align with messaging from AWS’s London Tech Week keynote in 2025. The takeaway: speed confers advantage.

3) Three blockers: regulation, skills, capital

  • Regulation: The EU AI Act is a milestone, but inconsistent implementation risks a patchwork that slows innovation. Business needs responsible AI and predictability across markets.

  • Skills: Europe produces top researchers, yet lacks mainstream digital skills at scale. Upskilling is decisive for adoption beyond pilots.

  • Capital: Late-stage funding, especially for female-founded ventures, remains thin — constraining scaling.

4) What “good” looks like inside enterprises: a three-stage path

Randery outlines a progression leaders can map to their own roadmaps:

  1. Efficiency (most are here): automations, chatbots, summarisation to free capacity.

  2. Operational transformation: end-to-end workflows redesigned; only ~12% of large enterprises are at this stage today.

  3. Strategic reinvention: new business models and products led by start-ups and agile incumbents.

5) Trust, choice and performance: the European flavour of AI infrastructure

Asked how global tech adapts to Europe’s data environment, Randery emphasises choice (multi-model access via AWS Bedrock), security by design, and data control/sovereignty — plus investment in chips with partners like Nvidia and in AWS’s own silicon. For regulated sectors, she stresses “built and operated in Europe” infrastructure.

So what should leaders do in Q1–Q2 2026?

1) Move from pilots to portfolios. Treat AI as a product pipeline: dozens of small bets, governed by a common platform and guardrails. (Map work to the three stages above.)

2) Get regulatory-ready. Align use-case risk tiers, model provenance, and data-residency controls now to avoid retrofitting when EU rules harden.

3) Attack the skills gap. Prioritise role-based enablement (analyst, PM, engineer, compliance) and build “AI product owner” capability for stage-2/3 value.

4) Architect for choice. Multi-model, retrieval-augmented patterns and clear API boundaries preserve flexibility as models and chips evolve. Randery’s “choice-security-performance” triad is a useful North Star.

5) Tie AI to growth metrics. Move beyond generic productivity claims; track cycle-time, win-rate, upsell and new-revenue contributions per AI feature.

Editor’s note (2 February 2026): This piece summarises the interview as published on 30 January 2026; figures and quotes reflect that article and related AWS materials. We’ll update if AWS or McKinsey provide new data.

FAQ

Q1: How fast is Europe adopting AI?
A: According to AWS EMEA’s Tanuja Randery, Europe saw ~30% higher adoption over the past year, with five businesses every minute adopting AI.

Q2: Where is the near-term value?
A: Gen AI could unlock up to $400bn for Europe, with the broader digital stack worth around $3tn, if organisations move quickly.

Q3: What’s holding Europe back?
A: Inconsistent regulation, a shortage of mainstream digital skills, and limited late-stage capital for scaling — especially for female founders.

In a McKinsey interview published 30 January 2026, AWS EMEA chief Tanuja Randery says Europe’s AI adoption is accelerating — five businesses a minute are adopting AI and uptake rose ~30% last year. The big unlocks now: clearer, consistent regulation, closing the digital-skills gap, and better late-stage capital.

Europe’s AI moment: 5 takeaways from AWS’s Tanuja Randery

Why this matters now
In a new interview with McKinsey & Company (30 January 2026), Tanuja Randery sets out a confident picture of Europe’s AI trajectory — and a blunt to-do list for leaders. Adoption is surging (“five businesses every minute”), up roughly 30% year on year, but scale will hinge on regulation, skills and capital.

1) Adoption is real — and broadening beyond pilots

Randery describes a European market moving faster than many assume, spanning enterprises, digital natives and start-ups. McKinsey’s piece quotes two punchy stats: five new AI-adopting businesses per minute and a near-30% annual rise in adoption. The “why” is shifting from cost savings to growth and innovation.

2) The value pool is big — if Europe moves quickly

Citing internal and ecosystem research, she points to $400bn of potential gen-AI value for Europe, rising to ~$3tn when broader cloud and digital are included. Those figures align with messaging from AWS’s London Tech Week keynote in 2025. The takeaway: speed confers advantage.

3) Three blockers: regulation, skills, capital

  • Regulation: The EU AI Act is a milestone, but inconsistent implementation risks a patchwork that slows innovation. Business needs responsible AI and predictability across markets.

  • Skills: Europe produces top researchers, yet lacks mainstream digital skills at scale. Upskilling is decisive for adoption beyond pilots.

  • Capital: Late-stage funding, especially for female-founded ventures, remains thin — constraining scaling.

4) What “good” looks like inside enterprises: a three-stage path

Randery outlines a progression leaders can map to their own roadmaps:

  1. Efficiency (most are here): automations, chatbots, summarisation to free capacity.

  2. Operational transformation: end-to-end workflows redesigned; only ~12% of large enterprises are at this stage today.

  3. Strategic reinvention: new business models and products led by start-ups and agile incumbents.

5) Trust, choice and performance: the European flavour of AI infrastructure

Asked how global tech adapts to Europe’s data environment, Randery emphasises choice (multi-model access via AWS Bedrock), security by design, and data control/sovereignty — plus investment in chips with partners like Nvidia and in AWS’s own silicon. For regulated sectors, she stresses “built and operated in Europe” infrastructure.

So what should leaders do in Q1–Q2 2026?

1) Move from pilots to portfolios. Treat AI as a product pipeline: dozens of small bets, governed by a common platform and guardrails. (Map work to the three stages above.)

2) Get regulatory-ready. Align use-case risk tiers, model provenance, and data-residency controls now to avoid retrofitting when EU rules harden.

3) Attack the skills gap. Prioritise role-based enablement (analyst, PM, engineer, compliance) and build “AI product owner” capability for stage-2/3 value.

4) Architect for choice. Multi-model, retrieval-augmented patterns and clear API boundaries preserve flexibility as models and chips evolve. Randery’s “choice-security-performance” triad is a useful North Star.

5) Tie AI to growth metrics. Move beyond generic productivity claims; track cycle-time, win-rate, upsell and new-revenue contributions per AI feature.

Editor’s note (2 February 2026): This piece summarises the interview as published on 30 January 2026; figures and quotes reflect that article and related AWS materials. We’ll update if AWS or McKinsey provide new data.

FAQ

Q1: How fast is Europe adopting AI?
A: According to AWS EMEA’s Tanuja Randery, Europe saw ~30% higher adoption over the past year, with five businesses every minute adopting AI.

Q2: Where is the near-term value?
A: Gen AI could unlock up to $400bn for Europe, with the broader digital stack worth around $3tn, if organisations move quickly.

Q3: What’s holding Europe back?
A: Inconsistent regulation, a shortage of mainstream digital skills, and limited late-stage capital for scaling — especially for female founders.

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Número de la empresa: 256 9431 77 | Derechos de autor 2026 | Términos y Condiciones | Política de Privacidad

Generación
Digital

Oficina en el Reino Unido
33 Queen St,
Londres
EC4R 1AP
Reino Unido

Oficina en Canadá
1 University Ave,
Toronto,
ON M5J 1T1,
Canadá

Oficina NAMER
77 Sands St,
Brooklyn,
NY 11201,
Estados Unidos

Oficina EMEA
Calle Charlemont, Saint Kevin's, Dublín,
D02 VN88,
Irlanda

Oficina en Medio Oriente
6994 Alsharq 3890,
An Narjis,
Riyadh 13343,
Arabia Saudita

UK Fast Growth Index UBS Logo
Financial Times FT 1000 Logo
Febe Growth 100 Logo (Background Removed)


Número de Empresa: 256 9431 77
Términos y Condiciones
Política de Privacidad
Derechos de Autor 2026