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.