The slide shows the percentage of respondents in each country who believe AI’s benefits outweigh its drawbacks. It reflects overall optimism or skepticism towards AI's societal value and utility.

This slide presents how much respondents across countries trust AI systems to avoid discrimination or bias. It highlights global perceptions of fairness in AI and potential ethical concerns.

The slide provides an overview of how Equifax leverages its proprietary data alongside advanced AI capabilities to enhance decision-making processes and product development, highlighting the strategic use of technology in business.

This slide presents challenges to AI adoption among retailers, including data fragmentation, poor quality, integration complexity, high costs, lack of leadership, and ethical concerns. It segments these barriers into five core domains and provides insight into how small and mid-sized businesses especially struggle with foundational AI readiness factors.

The slide presents the top challenges organizations face when integrating AI. Security and data privacy concerns top the list, followed by lack of AI expertise, and difficulty measuring ROI. Additional barriers include ethical risks, data silos, and lack of leadership support. The data highlights common obstacles that hinder successful AI adoption in financial services.

This slide highlights the various challenges and inefficiencies faced by organizations in scaling AI initiatives. It is useful for understanding barriers to technology adoption and strategizing on overcoming these challenges.

Identifies top AI-related challenges companies face at different maturity levels. Multi-disciplinary teams are the greatest challenge across most groups, followed by data foundation and security risk. Reinforces the idea that challenges evolve as companies mature in AI adoption.

Shows that 64% of executives prefer AI-human collaboration, with fewer choosing either extreme (AI-led or human-led). This reflects a trend toward integration rather than substitution.

The slide highlights the financial services sector's tendency toward data-centric risk responses. It introduces KPMG Australia's AI compliance platform and outlines key strategies for regulated sectors to manage digital transformation, with a strong focus on AI-driven regulatory response and risk framework evolution.

The slide identifies semiconductor opportunities in AI compute, automotive MCUs, infotainment processors, and IoT modules. It balances this with risks like long commercialization cycles and supply chain gaps, stressing India's strategic positioning.

Highlights concerns employees have about AI's impact on professional identity and suggests actions CEOs can take to address these concerns.

Depicts nervousness levels around AI across 31 countries, highlighting the U.S. as one of the most apprehensive. Bar chart includes percentage increase from 2021 to 2023.

Shows what companies expect from auditors regarding AI controls, including more thorough reviews, governance assessments, and attestation roles. Discusses gaps in current regulatory frameworks and future compliance needs.

Describes decision-making structure for responsible AI: a strategy-setting AI Trust Council and execution-focused AI Delivery Pod, backed by multidisciplinary teams.

Shows advanced AI use cases including automation/decision-making, workflow redesign, and error/problem detection. Highlights advanced automation of trading logic, smart contracts, and risk management processes across three waves.

Public concern about deepfakes as a tool for disinformation is high globally (75%). Canada (78%) and the US (74%) also show significant concern on this issue.

Analyzes trends in AI deployment and investment, showing a significant increase in AI applications and investment plans. It is relevant for discussions on technology budgeting and strategic investment in the tech industry.

Offers strategies for optimizing AI deployment, including investing in culture and leadership, transforming operations, and orchestrating tech and talent. This slide is ideal for strategic planning sessions in technology sectors.

Advocates for a strategic approach to AI ecosystems, emphasizing the need for collaboration, data access, and careful partner selection to optimize AI technologies and cost efficiency.

This slide shows that marketing is the most focused AI function for driving effectiveness in retail. It outlines how AI is used to predict outcomes and enable data-driven decision-making, with small and mid-sized retailers focused on customer insights and sales. It also mentions the rise of omnichannel approaches and use of customer lookalike models.

The slide focuses on the "Enable" phase of AI adoption, emphasizing the need to prepare people and foundational systems. It outlines top leadership goals, such as improving efficiency, customer experience, and mitigating risks. It underscores the importance of AI literacy, ethical alignment, and building a strong initial base for scaling AI.

The slide identifies key enablers for successful AI deployment, such as ROI evaluation, data accuracy, interoperable systems, and skilled workforce. It highlights that e-commerce players prioritize AI investment more than ROI and stresses the importance of annotated data and skilled teams for long-term AI integration success.

This slide shows how people across different countries believe AI will influence their entertainment options such as TV, music, movies, and books. The data shows generally high optimism, especially in China and Latin America.

Highlights the involvement of different business leaders, such as chief ethics officers and boards of directors, in developing AI ethics policies.

Ranks various methods of communicating AI ethics to the workforce, highlighting which methods are perceived as most effective by C-level executives.

Discusses how companies communicate AI ethics to their employees, including workshops, internal specialists, and ethical reporting methods.

Lists current and planned initiatives for responsible AI use. These include employee education, third-party reviews, ethical frameworks, and disclosures. Distinguishes between what’s already in place and what CEOs aim to implement in 2024.

The slide highlights the percentage of organizations hiring or planning to hire for various ethical positions in AI and technology, such as AI ethics researchers, compliance specialists, and policy analysts.

Emphasizes the importance of ethics and governance in AI deployment. Introduces the KPMG Trusted AI framework and its 10 ethical pillars to ensure responsible, transparent, and compliant AI implementation.

Lists top public concerns regarding AI (e.g., privacy, bias, misinformation). Visual data shows levels of worry using segmented bar charts to represent varying degrees of concern from "Very worried" to "Not worried". Tied to Ipsos' FAST (fair, accountable, secure, transparent) framework.

Lists five best practices for generative AI: ethical use, privacy/security, workforce training, public transparency, and fostering economic impact. Each section outlines strategic and regulatory considerations.

Addresses the ethical challenges AI faces, such as decision-making transparency and bias. It provides statistical insights into public perceptions and concerns across different countries.

This slide highlights that people feel most uncomfortable with AI-generated fake content (images, voices) and high-stakes decisions like welfare assessment. The discomfort stems from lack of trust in AI's ability to act responsibly without human oversight.

Outlines AI evolution from descriptive to generative stages. Shows how AI capabilities have grown over time, with modern AI capable of generating solutions and foresight, building on foundational descriptive and diagnostic insights.

The slide details generative AI adoption across demographics and geographies, indicating widespread early use and notable surprises (e.g., boomers using it more than millennials).

Analyzes how familiarity with AI influences perceptions, important for understanding market readiness and potential resistance or advocacy for AI initiatives.

The slide shows that AI companies received one-third of global VC funding in 2024, with strong CEO support for AI adoption. AI dominates VC portfolios, particularly in unicorns and early-stage ventures, maintaining its position as a leading investment theme despite broader sectoral challenges.

Predicts anticipated future change in daily life due to AI technologies. High agreement levels in Asia-Pacific regions and younger, wealthier, and more educated groups.

This slide highlights expected future impact of AI, showing global anticipation that AI will significantly shape lives in the coming 3–5 years. Agreement is generally higher than in the retrospective view (Slide 19082), with strongest expectations from China, Indonesia, and South Korea.

Demonstrates potential changes in job roles and work distribution with the integration of AI, aiming at operational optimization and enhanced efficiency.

This slide emphasizes the importance of collaboration between governments, tech companies, and the public in the development of AI. It shows that trust is highest in academic institutions and tech companies, despite generally low institutional trust globally.

Survey data highlighting global concern (74%) about AI-driven cybersecurity threats. Canada and the US show above-average levels of concern at 78% and 76% respectively.

Explains that true AI value comes 70% from people and processes, 20% from technology, and only 10% from algorithms—contrasting perception with operational reality.

This slide illustrates Nigerian CEOs’ expectations of AI becoming a core part of business strategy, workforce transformation, and product development. It emphasizes high integration in business processes and technology platforms, underlining the growing relevance of AI in long-term planning and operations.

This slide shows country-by-country agreement on whether AI products and services have significantly impacted daily life in the past 3–5 years. Agreement is highest in China, Southeast Asia, and South Korea, while Western countries show lower agreement.

Evaluates how people in New Zealand perceive the current and future impact of AI on their daily lives. Forecast shows higher expectations for the future than past experiences.

The slide presents a global comparison of public opinion on whether AI will improve, worsen, or not affect the economy in the next 3–5 years. Results are shown for multiple countries, highlighting optimism in places like China and Indonesia.

Evaluates CEO perspectives on AI's potential impact versus the internet revolution, highlighting significant regional insights.

Compares public sentiment about AI from different years, useful for discussions on technology adoption and workforce transformation.

This slide presents findings on AI strategy alignment and vision clarity in organizations. Only 15% are fully embedded into strategy, and only 31% have a clear vision. It emphasizes gaps in strategic alignment and AI foresight.

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.

This slide maps AI maturity levels in retail, indicating most brands are in the exploratory or early-win stages. Very few are in the refinement or pinnacle phases. Commentary highlights perceived lag in progress relative to competitors and industry norms. E-commerce brands are further ahead.

The slide shows that at early AI maturity, organizations prioritize operational improvements such as risk mitigation and cost reduction over strategic goals. It explains how AI enhances employee experience through automation, reducing manual effort and improving decision-making and customer interactions. A quote adds perspective on AI’s workforce impact.

The slide outlines three phases for accelerating AI adoption based on organizational maturity. It provides tactical steps for identifying AI opportunities, piloting tools, and implementing them at scale. Specific AI tools and maturity considerations are also included.

This slide analyzes the maturity levels of AI adoption across various retail functions, revealing that most brands are still experimenting or ideating. Only a few functions such as sales and marketing show mature solutions. The visual compares ten functions and explains trends in AI data usage and implementation, highlighting areas of opportunity and early adoption.

Discusses AI adoption stages, revealing only 31% have scaled AI to production. Most organizations are still in early or testing phases. It notes the productivity gains from AI and the importance of aligning AI strategy with business goals.

Reviews business outcomes from AI initiatives, with a focus on revenue generation and market expansion. Useful for evaluating the effectiveness of AI strategies and planning future business models in tech-driven industries.

This slide reflects global and demographic agreement levels regarding the influence of AI on daily life in the recent past, with South Korea and Thailand at the top.

This slide visualizes the share of respondents across multiple countries who express nervousness about AI-powered products and services. It ranks countries by agreement level and highlights global sentiment towards AI adoption and unease.

Provides high-level statistics from 32 countries about attitudes toward AI: understanding, trust, job risk, and excitement/nervousness. Highlights generational differences in perception and expectations regarding AI’s future impact.

This slide explores public sentiment toward AI's impact, showing a split in opinion: 55% say AI is improving life, while 45% feel it's making life worse. It emphasizes that while many see incremental benefits, concerns persist about AI's broader societal effects.

Discusses differing AI perceptions between managerial levels, useful for organizational strategy and understanding internal stakeholder perspectives.

It explains how AI Achievers outperform others in multiple areas such as strategy, data management, talent, and responsible AI practices. The slide focuses on the key differentiators of successful AI implementation.

It explains how AI Achievers outperform others in multiple areas such as strategy, data management, talent, and responsible AI practices. The slide focuses on the key differentiators of successful AI implementation.

Explores the gap between current AI usage and perceived potential. It emphasizes how people believe AI could help with scheduling, research, content creation, etc., more than they currently use it for. Includes forward-looking perspectives and examples of future applications.

Outlines the main priorities for AI and ML implementations for the year 2021, focusing on responsible AI tools.

This slide focuses on what society considers the most important AI applications, with medical breakthroughs, security, and climate solutions ranked highest. It reflects public preference for innovations that solve real-world problems.

It discusses the transition of AI projects from pilot phases to full production, using Procter & Gamble as a case study. The slide highlights the effectiveness of scaling AI solutions across enterprises.

This slide measures familiarity with AI-powered products and services. It ranks countries by agreement and shows demographic patterns by gender, generation, income, and education, revealing significant differences in functional AI literacy.

This slide displays the percentage of respondents in 32 countries who claim to know which products and services use AI. Results show significant variation, with higher knowledge in Asia and lower in Europe/North America. Includes 2023 data comparison.

Discusses the proposed EU regulations for AI, detailing risk categories, compliance requirements, and the impact on AI applications across various sectors.