A sound AI business strategy is vital for those looking to harness the transformative power of tech. The principles? Defining clear objectives, understanding where to play, and identifying how to win.

By assessing data readiness, prioritizing impactful use cases, and building cross-functional teams, organizations can create an AI strategy roadmap that guides successful AI implementation strategies, positioning them for future growth.

Customized AI strategies

Our team builds bespoke enterprise AI strategies tailored to your specific business goals and market demands. Our solutions aren’t one-size-fits-all.

Diverse, expert guidance

Our collective intelligence—with talent from five continents, 18 offices, and over 50 nationalities—provides insight based on extensive experience and the latest AI advancements.

Streamlined AI adoption

Our straightforward approach speeds the adoption of AI & Gen AI, with easy-to-follow roadmaps, smart tips, and practical frameworks for smooth integration.

Maximized ROI

Get the most out of your AI investments with strategies that boost innovation, efficiency, and real-world results the impact your triple bottom line: people, planet profit.

Customized AI strategies

Our team builds bespoke enterprise AI strategies tailored to your specific business goals and market demands. Our solutions aren’t one-size-fits-all.

Diverse, expert guidance

Our collective intelligence—with talent from five continents, 18 offices, and over 50 nationalities—provides insight based on extensive experience and the latest AI advancements.

Streamlined AI adoption

Our straightforward approach speeds the adoption of AI & Gen AI, with easy-to-follow roadmaps, smart tips, and practical frameworks for smooth integration.

Maximized ROI

Get the most out of your AI investments with strategies that boost innovation, efficiency, and real-world results the impact your triple bottom line: people, planet profit.

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Key Benefits & Target Indicators 

2x faster

go-to-market

For businesses launching new products and/or services.

30% drop in

operational costs

Through AI-driven optimization, cutting out manual tasks and freeing your team to focus on more important initiatives.

25-35% improved

decision-making

Business judgements are quicker and more accurate thanks to data-driven insights and predictive analytics from AI.

20-30% increase

in productivity

By accelerating processes through AI-driven automation.

2x faster

go-to-market

For businesses launching new products and/or services.

30% drop in

operational costs

Through AI-driven optimization, cutting out manual tasks and freeing your team to focus on more important initiatives.

25-35% improved

decision-making

Business judgements are quicker and more accurate thanks to data-driven insights and predictive analytics from AI.

20-30% increase

in productivity

By accelerating processes through AI-driven automation.

Retail, Luxury & Consumer Goods | Industry Use Case

AI-driven demand forecasting

AI-driven demand forecasting

Challenge:

Tchibo faced difficulties in accurately predicting product demand, which led to inefficiencies in inventory management and logistics. The company needed a simple solution to enhance forecasting capabilities.

Solution:

An AI-driven service utilizing Google’s Vertex AI, analyzing over three years of product, marketing, sales, and logistics data to predict online demand for products up to 84 days in advance.

30%

Improved demand forecasting.

20%

Reduced excess inventory costs due to better alignment of supply with demand.

25%

Less time spent on logistics planning.

* For illustrative purposes, based on publicly available information

Retail, Luxury & Consumer Goods | Industry Use Case

AI-driven demand forecasting

AI-driven demand forecasting

Challenge:

Amazon faced the challenge of maintaining efficiency and responsiveness within its vast supply chain network. Traditional forecasting methods were often inadequate in predicting demand fluctuations, leading stockouts or excess inventory.

Solution:

An AI-driven supply chain optimization system that leverages machine learning and predictive analytics. The system analyzes massive troves of data from various sources to improve demand forecasting accuracy.

30%

Reduction in inventory costs.

95%

More accurate demand forecasting.

20%

Reduced delivery times through optimized logistics.

* For illustrative purposes, based on publicly available information

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