Public Perception of Generative Artificial Intelligence: A Global Overview and Implications for Investor Communication and Engagement

The advent of generative artificial intelligence (AI) has sparked a broad set of reactions across the globe, reflecting varying degrees of acceptance, concern, and enthusiasm. Understanding these geographic variations in public perception is critical for public companies as they develop and communicate their strategic, operational, and financial plans related to AI deployment to institutional investors.

Below we outline the current state of public sentiment towards generative AI in different regions and outlines how companies can navigate these perceptions in their investor communications and engagement strategies.

North America

In North America, particularly the United States, public perception of generative AI is mixed but leans towards caution. A Pew Research Center survey found that 52% of Americans are more concerned than excited about AI, while only 10% are more excited than concerned. The primary concerns include job displacement, data privacy, and the potential for AI to exacerbate social biases.

A recent study by the Brookings Institution highlights that many Americans are apprehensive about AI’s impact on employment, fearing that AI technologies could replace human jobs across various sectors. Additionally, the American Civil Liberties Union (ACLU) has raised issues regarding data privacy, particularly how AI systems collect and will use personal information. In Canada, similar concerns are prevalent, with additional emphasis on the ethical use of AI and its potential impact on civil liberties.

Investor Relations Implications:

• Transparency and Accountability: Emphasize a commitment to ethical AI practices, highlighting measures to proactively mitigate potential job displacement and ensure data privacy. Companies can develop and communicate transparent AI policies and communicate how they protect user data and prevent misuse.
• Regulatory Compliance: Demonstrate proactive engagement with regulatory bodies to ensure compliance with evolving standards. This includes adhering to guidelines from bodies such as the Federal Trade Commission (FTC) and ensuring data protection practices align with regulations like the California Consumer Privacy Act (CCPA).

Europe

In Europe, the sentiment towards generative AI is similarly cautious, with a strong emphasis on ethical considerations and data privacy. The European Union's General Data Protection Regulation (GDPR) reflects a high level of public concern about data protection. A recent survey by the European Commission noted that while Europeans recognize the potential benefits of AI, they are wary of its implications for privacy and job security.

Similarly, the European Economic and Social Committee (EESC) has highlighted concerns about AI’s role in increasing social inequality and its potential to perpetuate existing biases. In the UK, public sentiment mirrors broader European concerns, with strong calls for ethical AI deployment and significant attention on the potential for AI to disrupt job markets. Meanwhile, in Germany, there is robust support for stringent AI regulations to ensure transparency and accountability.

Investor Relations Implications:

• Ethical AI Development: Communicate adherence to ethical AI guidelines and frameworks, such as those proposed by the EU, to gain public and investor trust. This can involve adopting standards from the European Commission’s Ethics Guidelines for Trustworthy AI.
• Stakeholder Engagement: Engage with stakeholders, including policymakers and civil society organizations, to align AI strategies with public expectations and regulatory requirements. Participating in multi-stakeholder initiatives and public consultations can also enhance credibility.

Asia-Pacific

In the Asia-Pacific region, perceptions of generative AI vary widely. Countries like China and Japan have shown significant enthusiasm for AI, driven by strong government support and public acceptance. In China, for instance, the government’s AI development plan aims to make the country a global AI leader by 2030. This ambition is generally well-received by the public, who view AI as a key driver of economic growth and innovation. Public sentiment in Japan also leans positive, with a strong focus on AI’s potential to boost economic productivity and address societal challenges like an aging population.

Conversely, in countries like India, while there is excitement about AI’s potential, there are significant concerns about job displacement and the digital divide. A report by NASSCOM highlights both the opportunities and challenges posed by AI in the Indian context, emphasizing the need for skills development and digital infrastructure improvements. In Australia, public sentiment towards AI is generally positive, with significant interest in AI’s potential to drive innovation and economic growth. However, there are concerns about ethical considerations and the need for robust regulatory frameworks to manage AI deployment.

Investor Relations Implications:

• Localized Strategies: Tailor AI deployment strategies to reflect local public sentiment and regulatory environments. In enthusiastic markets like China, emphasize innovation and growth, while in India, address job displacement concerns.
• Government Collaboration: Collaborate with local governments on AI initiatives to enhance public trust and support for AI projects. Forming public-private partnerships to develop AI infrastructure and educational programs can demonstrate a commitment to societal benefits.

Latin America

In Latin America, public perception of AI is generally cautious but hopeful. There is significant interest in leveraging AI for social good, such as improving healthcare and education. However, concerns about inequality and access to technology persist. A report by the Inter-American Development Bank indicates a cautious optimism towards AI, with a strong desire for inclusive and equitable AI policies.

Countries like Brazil and Mexico have seen initiatives to integrate AI into public services, yet the digital divide remains a significant challenge. Addressing these disparities is critical for gaining public trust and support.

Investor Relations Implications:

• Inclusive AI Initiatives: Highlight AI projects that focus on social impact, such as healthcare and education, which can resonate well with the public and investors. Showcase case studies and pilot projects that demonstrate tangible benefits to communities.
• Educational Outreach: Invest in AI education and training programs to address concerns about the digital divide and showcase a commitment to equitable growth. Collaborations with local universities and NGOs can enhance the reach and impact of these initiatives.

Middle East and Africa

In the Middle East and Africa, there is a growing interest in AI, particularly for its potential to drive economic development and innovation. In the UAE, the government has launched several initiatives to integrate AI into public services and has created the world’s first Ministry of Artificial Intelligence. This proactive approach has been met with public optimism about AI’s potential benefits.

However, in many African countries, there is still a significant digital divide that impacts the adoption and perception of AI. Concerns about job displacement and the need for infrastructure development are prevalent. A report from Afrobarometer indicates that while there is interest in technology and innovation, there are also concerns about equitable access and the potential for AI to exacerbate existing inequalities.

Investor Relations Implications:

• Infrastructure Development: Emphasize the role in supporting infrastructure development to facilitate AI adoption. This can include investments in digital infrastructure and partnerships with local governments to enhance connectivity.
• Equitable Access: Address concerns about equitable access to AI technologies by developing inclusive strategies that benefit all segments of the population. This can involve creating AI solutions tailored to local needs and ensuring affordability.

Communicating with Institutional Investors

Given these diverse public perceptions, public companies must adopt a nuanced approach when communicating their AI strategies to institutional investors. Here are the key considerations:

1. Conduct an Impact Intelligence Project: Impact Intelligence is the next generation of investor perception. It is critical to understand the degree to which investors are focused on understanding the inter-relationship of generative AI, public opinion, and the companies business and technology strategy.
2. Describe the Technology Investment Portfolio: Outline the investments associated with generative AI, the payback period and how these investments will have positive benefits for the investor community, for employees and society.
3. Highlight Ethical Practices: Investors are increasingly concerned about the ethical implications of AI. Emphasize commitment to ethical AI development, including fairness, transparency, and accountability and provide concrete examples of ethical AI applications and partnerships with ethical oversight bodies.
4. Showcase Regulatory Compliance: Demonstrate proactive engagement with regulatory bodies and adherence to local regulations to reassure investors about the sustainability of AI initiatives. Include detailed reports on compliance with GDPR, CCPA, and other relevant regulations in investor communications.
5. Focus on Long-Term Value: Articulate how AI investments will drive long-term value, balancing innovation with risk management. Address public concerns about the potential for job displacement and data privacy. Highlight AI’s role in driving efficiencies, innovation, and creating new job categories to illustrate a balanced approach.
6. Engage in Public Dialogue: Participate in public dialogues and collaborations with stakeholders to enhance reputation and build trust with both the public and investors. Host webinars, participate in industry conferences, and engage in community outreach programs to demonstrate commitment to transparency and societal impact.
7. Sustainability and Social Impact: Integrate AI strategies with broader corporate social responsibility (CSR) and sustainability goals to resonate with ESG-focused investors. Outline how AI initiatives contribute to sustainability targets, such as reducing carbon footprints through optimized processes, to align with investor priorities.
8. Impact: Provide metrics on the impact of AI initiatives to help investors understand the tangible benefits and progress. Regular updates and transparent reporting on AI projects’ performance, challenges, and milestones are critical to enhance and elevate valuation.

Understanding and addressing public perception of generative AI across different geographies is essential for public companies. By aligning their strategic, operational, and financial plans with local sentiments and regulatory landscapes, companies can effectively communicate their AI initiatives to institutional investors, fostering trust, long-term investment end elevating value.