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Hi and Welcome to the Tech A newsletter DeepDive
Over the past three weeks, I've shared detailed insights about the current state of AI implementation in businesses, drawing from my experience as a former R&D Program Manager and CTO, combined with data from 16 major industry reports covering over 3000 companies.

Here's your 3-minute executive summary of all three parts 👇️ 

⚡ Your 2-Minute Summary

The Current Reality : AI can indeed bring tremendous value, but for the few that adopt the right strategy (Read Part 1 Here)

• Despite massive investments, only 26% of businesses are generating tangible value from AI, of which 4% have been able to achieve significant value.

• Most successful implementations see nearly 3x ROI and 30% premium on key financial metrics

• 62% of value comes from core business functions (operations 23%, sales 20%, R&D 13%)

• Financial services, Tech/Telecom, and Industrial sectors are leading adoption

• Enterprise average spend: >$1M yearly on GenAI

What differentiates the AI leaders from the Learners? (Read Part 2 Here):

• 70-80% of AI initiatives never move beyond the pilot phase

• Success requires addressing three critical areas:

  • People/Process (70% of effort needed)

  • Technology (20%)

  • Algorithms (10%)

  • This 70-20-10 split challenges a common misconception: while many organizations focus on technical capabilities, successful AI implementation is predominantly a people and process challenge.

• Main barriers: ROI measurement, talent acquisition, data quality, and system integration

• Success markers: Companies that scale successfully, invest more, plan, and execute a comprehensive enterprise-level/multi-year strategy.

The Winning Playbook (Read Part 3 Here):

1. Start with Strategy: Follow the 10-20-70 rule (algorithms-tech-people)

2. Focus on High-Impact Pilots: Begin small but target core business processes. You need the initial ROI to reinvest and get executive buy in.

3. Build the Foundation: Invest in infrastructure and quality data. Address data challenges early, ensuring AI tools integrate seamlessly with existing systems. Prepare teams through training and process adaptations.

4. Scale Strategically: Form cross-disciplinary teams, establish AI Centers of Excellence, and create governance frameworks. Address gaps in technology, data, and strategy to support organization-wide scaling efforts.

5. Drive Adoption: AI success requires cultural change. Embed AI into workflows, reimagine processes, and foster digital literacy across teams.

🎁Exclusive Resource Pack

As a subscriber, you can access all 16 industry reports that formed the backbone of this analysis. These include the latest insights from BCG, McKinsey, Deloitte, IBM, Dataiku, and more.

Download Reports Here-> Link

Reports included:

• BCG: Built for the Future 2024 Global Study

• Accenture: Built to Scale

• Deloitte State of GenAI Q3 2024

• IBM Global AI Adoption Index 2024

• Dataiku: AI Today

• ... and 11 more

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Amine Rabehi

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