Describes how AI is being integrated into various stages of M&A, from strategy development to due diligence. Most usage is in early stages (pre-deal) but is expanding. Gen AI is credited with improving speed, cost, and accuracy.

Details AI-enabled employee-facing use cases in corporate banking across five categories—product development, customer engagement, risk & compliance, and infrastructure. Focuses on areas like content generation, detection models, synthetic data use, and improved analysis.

Discusses AI use cases in fashion, highlighting "product discovery and customer search" as the top priority. Explains customer demand, AI improvements, competitive tech developments, and emerging commercial success stories for 2025.

Most workers don’t believe AI will fully replace their jobs in the near term, but many expect it to be used in their roles. Still, few are taking steps to prepare. The slide stresses the need for reskilling, especially in sectors likely to be most affected by AI.

Investigates the adoption of AI initiatives across global regions, reflecting on current business practices and future trends.

Highlights shift from centralized to decentralized AI experimentation. Shows most organizations prefer open collaboration (40%) or democratized approaches (34%). Right panel elaborates on balanced experimentation models and aligning AI with business outcomes.

Provides a structured plan for incorporating AI into business practices, focusing on scalability, workforce transformation, and ethical considerations.

This slide explores preferred values for AI integration, with "innovative" topping the list globally. Many also emphasize “responsible,” “safe,” and “cautious,” showing the tension between progress and regulation. Country-level data shows how cultural values shape attitudes.

Illustrates different strategies companies use to ready their workforce for AI, such as developing guidelines, providing AI tools, and acquiring AI skills.

Highlights a 60% projected increase in GenAI investments over 3 years, starting from a 30% increase in 2024, indicating rising ambitions and commitment to AI.

The slide maps countries based on their technology strength and AI investment levels. Germany appears as a tech leader but lags behind nations like the US and China in investment. The visual reinforces the point that Germany needs to increase AI investment to match its technical capability.

Describes expanding use of AI in businesses and increasing investment. Charts AI budget share by sector and maturity level. Highlights governance, strategic alignment, and the EU AI Act's anticipated impact.

This slide reveals that retailers are prioritizing customer-facing AI functions such as customer insights, CX orchestration, and marketing over backend operations. It highlights the trend of using AI for personalization and emotional connection. Despite backend potential, most investments are going toward functions with visible customer impact and faster returns.

This slide highlights that AI's economic potential in DF9 will require scaling investment by 8x compared to a 4x increase during earlier tech waves (1995–2007). It discusses the need for reskilling, proper infrastructure, and how private/public sectors must prioritize investment to capture AI benefits.

Shows the surge in AI investment by major hyperscalers like AWS, Microsoft, and Alphabet. It also identifies sectors with highest AI adoption—led by Information and Professional Services—and expectations for broader deployment in the next 6 months.

The slide shows 71% of respondents believe it's wise to delay major AI investments until the tech landscape is clearer. It highlights lack of a dominant AI model, leadership concerns about control, and the role of automation. It reveals banks’ cautious yet evolving stance towards AI, with adoption happening selectively and with reservations around operational impact.

The slide discusses how societal concerns about the responsible use of AI are affecting investments, with a significant number of leaders approaching AI investments cautiously due to these concerns.

This slide captures perceptions across countries about whether AI will improve, worsen, or not affect their job over the next 3–5 years. Optimism is highest in Asia and Latin America, while skepticism is more prevalent in Western Europe.

This slide examines perceived risk of AI replacing jobs within five years across different countries. Southeast Asia expresses greater concern compared to Europe and North America. The data reflects varying levels of anxiety about job displacement.

This slide tracks the year-over-year change in belief that AI will replace current jobs. Gen Z maintains the highest level of concern, while Baby Boomers show the least concern. Overall, responses have remained relatively stable between 2023 and 2024.

This slide shows perceived likelihood across countries that AI will change how people perform their current jobs in the next five years. Asian countries like Indonesia and Thailand show the highest perceived likelihood, while Western European countries show more skepticism.

The slide outlines guiding principles for driving an AI journey, emphasizing prioritizing value creation, encouraging innovation, assessing capabilities, involving the organization, and using AI responsibly.

This slide visualizes how well citizens of various countries understand what artificial intelligence is. It ranks countries and breaks down understanding by gender, generation, income, education, and employment status, highlighting demographic differences in awareness.

This slide evaluates opinions across countries on AI’s effect on the broader job market in the next 3–5 years. Results are mixed, with Latin America and Asia leaning optimistic, and European nations showing concern or neutrality.

Explains layered AI governance: organizational processes, data compliance, model performance testing, and user impact review. Designed to support safe, ethical AI at scale.

Illustrates AI maturity levels (beginner, implementer, leader) across company revenue bands, industries, and regions. Highlights disparities in adoption and positioning for AI leadership across sectors and regions.

This slide emphasizes the critical role of AI in gaining competitive advantage, highlighting survey data on the importance of AI, and showing a projection of AI transformation timelines.

Defines an AI maturity model based on usage and actions taken. Categorizes companies into three groups based on their AI implementation readiness. Provides criteria and scoring method for classification.

Highlights distribution of AI maturity across surveyed companies, showing that only 8% are front-runners. Notes distinctions between fast-followers and front-runners, with most companies still in early AI phases. Suggests significant room for growth in scaling strategic AI capabilities.

It analyzes AI maturity levels across various industries, showing current standings and future projections. The data helps in understanding which industries are leading in AI adoption.