The ESG and Data for Good Center of Excellence Urges World Leaders at Davos to Confront AI Governance Risks for the Sake of Humanity

As the world’s foremost leaders gather at the Annual Meeting of the World Economic Forum, the ESG and Data for Good (D4G) Center of Excellence underscores the urgent necessity of prioritizing Artificial Intelligence (AI) governance and the ethical considerations inherent in its development and deployment. AI is no longer a sectoral or technical concern; it is a force that is reshaping economies, industries, social structures, and political landscapes across the globe. Its pervasive influence presents both unprecedented opportunities and profound risks.

While AI has the potential to drive efficiencies, enhance decision-making, and unlock innovation at an unparalleled scale, it also carries the potential to exacerbate existing inequalities and perpetuate biases. Algorithmic bias remains a persistent challenge, manifesting in ways that can entrench social disparities, discriminate against vulnerable populations, and undermine human agency. Moreover, there is a growing concern that over-reliance on AI could weaken critical human capabilities, including problem-solving, decision-making, and creative thinking. These risks, if left unchecked, could have profound societal consequences.

In recognition of these challenges, the ESG and D4G Center of Excellence calls upon global leaders to take immediate, coordinated, and meaningful action. We urge them to adopt a multi-pronged approach that emphasizes collaboration, protection, innovation, and education.

  1. Encouraging and Facilitating Ecosystem Synergies and Partnerships
    The magnitude and complexity of the challenges posed by AI cannot be addressed by any single actor. Governments, private sector entities, academia, civil society, international organizations and even individuals must work together to establish coherent frameworks for responsible AI development and deployment. Partnerships across the ecosystem are essential to share knowledge, align standards, and harmonize approaches to governance. By fostering synergies, we can ensure that AI serves as a tool for collective progress rather than a driver of fragmentation or inequality.
  2. Protecting Communities Through Agile Policies and Regulations
    The speed at which AI technologies are evolving demands equally agile governance mechanisms. Policies and regulations must be developed proactively and updated continuously to respond to emerging challenges. Such frameworks must prioritize the protection of human rights and account for the diverse needs of all segments of society, particularly the most vulnerable. Ethical AI cannot be an afterthought; it must be embedded at every stage of development and deployment, ensuring that technological progress does not come at the expense of societal well-being.
  3. Promoting Responsible Innovation
    Innovation remains a cornerstone of progress, yet it must be guided by ethical imperatives. Encouraging responsible innovation means creating an environment where technological breakthroughs are aligned with societal values, environmental sustainability, and human-centric objectives. Incentivizing ethical research and development, supporting open-source collaborations, and recognizing the social impact of technological solutions are critical components of a responsible innovation ecosystem.
  4. Capacity Building and Awareness as the Key Enablers
    Finally, the foundation of responsible AI governance lies in knowledge, awareness, and capacity building. All stakeholders including policymakers, technologists, and the general public must be equipped with the understanding necessary to navigate AI’s complexities. Awareness campaigns must begin at the most basic levels, cultivating literacy in AI ethics, risks, and opportunities. Education and training programs should be inclusive, accessible, and continuous, ensuring that individuals and organizations are prepared not only to utilize AI effectively but also to challenge its misuse and advocate for ethical standards.

The ESG and D4G Center of Excellence emphasizes that AI’s promise can only be realized if it is governed with foresight, ethics, and collective responsibility. The global community stands at a pivotal moment: the decisions made today will shape the technological and societal landscapes of tomorrow. We call upon all leaders, stakeholders, and citizens to act decisively, collaboratively, and conscientiously, ensuring that AI remains a force for inclusive progress, human dignity, and shared prosperity.

Trustworthy AI: Shaping a Future that Puts People First

Artificial Intelligence (AI): A Disruption that has changed our world

Whether we accept it or not, AI has changed us in different ways. It has changed how we think, act, and work. For instance, if you are currently studying, you may no longer worry as much about your thesis or reading dozens of papers because AI can just do that in seconds. If you are pursuing a new career, AI can customize a roadmap to help and if you are working, it can assist with your daily tasks, brainstorming ideas and conducting research.

In fact, 75% of knowledge workers use AI at work today, with 90% reporting that it helps them save time, 85% stating it allows them focus on their most important tasks while 84% saying it enhances their creativity. This rapid uptake of AI is not at the individual level alone, the adoption of AI at the organizational level has doubled from year 2023 to year 2024 and organizations started deriving business value from it. Leaders of organizations are starting searching for candidates with AI skills. According to the 2024 Work Trend Index, 71% of organizational leaders would rather hire less experienced candidates with AI skills than those with experience but no AI expertise. Supporting this shift, a report by the World Economic Forum predicts that AI will create 97 million new jobs. So, this shift in mindset and behavior, what we call the AI transformation, is happening right now.

AI is also reshaping the way industries operate, creating massive economic value with its contribution to the global economy expected to reach $15.7 trillion by 2030. For instance, in healthcare industry, AI is accelerating breakthroughs in disease diagnosis, drug discovery, and personalized medicine,  potentially generating up to $150 billion in annual savings for the U.S. healthcare system alone by 2026. Meanwhile, in manufacturing, the AI revolution is equally remarkable. AI-driven automation is streamlining production, reducing waste, and improving quality control. It’s no surprise that investment in AI for manufacturing is projected to reach $16.7 billion by 2026, according to the World Economic Forum.

AI, particularly Generative AI, has been designed for humans. Large Language models (LLMs) are trained and built with memory to tell a story. They are built so they can relate to their audience and the person they are chatting with. Since people are at the center of this technology, it must be built in a way that earns and maintains their trust. Trust has been a growing concern about AI especially with its accelerating adoption by organizations. Based on KPMG global study of shifting public perception of AI, 61% of people are wary about trusting AI systems. So, trust must be at the heart of this technology because, quite simply, if people do not trust it, they are not going to use it.

The Pillars of Trustworthy AI

Making AI trustworthy requires prioritizing three key pillars; security, privacy and safety. Security is essential to protect against sensitive data leakage and emerging threats, such as prompt injection attacks. These risks are pressing since 78% of AI users are bringing their own AI tools to work, often providing information to unapproved AI systems (shadow AI), which increases the risk of data oversharing. Around 80% of business leaders see the leakage of sensitive data by staff as a top concern. To address this, AI developers must not only commit to strong security measures but also have the capabilities to implement them effectively. This includes securing and governing data, detecting and responding to threats, and ensuring compliance with regulations.

Privacy, a fundamental right, is crucial for preventing personal data breaches. Privacy is not just about protecting stored personal data but also about safeguarding information during processing. AI models should comply with data privacy laws, regularly assess and mitigate privacy risks, and respect user consent and preferences. Protecting the data of the users shall be the top priority since data is the fuel that powers AI and any harm or misuse of the data will erode trust in AI models or applications.

Safety is ensuring that AI applications do not generate harmful, unreliable content or ungrounded outputs. AI model is considered safe when it behaves as expected and operates only within the scope of the materials it has legal rights to use.

Key Pillars of Trustworthy AI: Security, Privacy, Safety, and Governance

The pillar that ties all these pillars together, ensuring that all of them are effectively implemented is governance. There are new regulations and frameworks emerging around the world such as the EU AI Act, Artificial Intelligence and Data Act (AIDA) in Canada, NIST AI Risk Management framework in U.S., and Australia’s AI Action plan. These frameworks are designed to ensure that AI systems secure, safe, and privacy-compliant. Companies that adhere to these regulations foster trust and confidence in their products.

However, building trustworthy AI is not a one-time effort, it is a continuous process. It requires ongoing risk assessment, mitigation planning, and continuous monitoring to ensure AI systems remain reliable and worthy of public trust.

The Future: Adapting to AI Transformation

As AI adoption accelerates across individuals and organizations, it brings both opportunities and risks. This transformation is expected to create between 20 to 50 million jobs by 2030, many of which will demand new skills. This makes upskilling critical. AI literacy programs alone won’t be enough; people need to learn not just how to use AI but also how to navigate its risks. Understanding how to leverage AI responsibly will empower individuals to make informed decisions about which AI applications to trust.

Awareness must also come from the top down. While many regions and countries are establishing Ethical AI and Data Acts, Africa and the MENA region still lag behind in this area. This must become a priority, as strong governance is the key to unlocking AI’s full potential while ensuring it serves the people it was designed to help, without causing harm.

The future will not wait. AI is reshaping the world right now, and those who fail to adapt will be left behind. The question is no longer whether AI will transform industries but rather how we will shape that transformation to build a future that is innovative, responsible, and, above all, human-centric.

References

1.  2024 Work Trend Index Annual Report from Microsoft and LinkedIn

2. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-2024

3. https://www.weforum.org/press/2020/10/recession-and-automation-changes-our-future-of-work-but-there-are-jobs-coming-report-says-52c5162fce/

4. https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf

5. https://www.accenture.com/content/dam/accenture/final/a-com-migration/manual/r3/pdf/pdf-49/Accenture-health-artificial-intelligence-j.pdf

6. https://assets.kpmg.com/content/dam/kpmg/es/pdf/2023/09/trust-in-ai-report.pdf

7. https://news.microsoft.com/wp-content/uploads/prod/sites/711/2024/11/Gen-AI-Survey-FINAL-20231228.pdf

8. https://www.mckinsey.com/featured-insights/future-of-work/jobs-lost-jobs-gained-what-the-future-of-work-will-mean-for-jobs-skills-and-wages