The ICC’s policy paper on inclusive AI offers a timely and necessary call to action. The full promise of AI, for innovation, development & human progress, can only be realized if it is truly inclusive.

Achieving Inclusive AI – Delivering for Business and Society - Based on the ICC’s 2025 policy paper on Inclusive AI

by ChatGPT-4o

Introduction

Artificial Intelligence (AI) is rapidly transforming societies and economies worldwide. Yet, as the International Chamber of Commerce (ICC) warns in its July 2025 policy paper, “Achieving Inclusive AI,” these transformative benefits risk being unevenly distributed. While AI promises accelerated innovation, productivity gains, and societal benefits—from sustainable development to breakthroughs in education and healthcare—roughly one-third of the global population remains offline. Without deliberate action, this AI revolution could exacerbate the global digital divide, entrench inequality, and leave the Global South behind.

The ICC’s framework identifies the key building blocks of inclusive AI and offers a blueprint for governments, industry, and civil society to ensure that AI serves all humanity. This essay explores the ICC’s arguments, evaluates their merits, and provides recommendations for stakeholders.

Why Inclusive AI Matters

The ICC rightly asserts that inclusive AI is not just a matter of fairness—it is a business and development imperative. Inclusive AI can:

• Enable broader market participation;

• Enhance economic resilience;

• Support achievement of the UN Sustainable Development Goals (SDGs);

• Foster global innovation ecosystems;

• Empower marginalised populations, especially in the Global South.

Without equitable access to AI-enabling infrastructure, data, computing capacity, and skills, societies risk deepening socio-economic divides. Linguistic and cultural exclusion from dominant AI systems further compounds the issue, limiting their relevance and accuracy for non-Western populations.

Barriers to Inclusion

The ICC outlines significant structural barriers to inclusive AI:

1. Infrastructure deficits – Reliable electricity, internet connectivity, and sustainable data centres are still absent in many regions.

2. Data inequality – The lack of diverse, high-quality, and accessible data impedes the development of contextually appropriate AI.

3. Skills gaps – Large segments of the workforce lack the AI literacy necessary to participate in or benefit from emerging digital economies.

4. Underdeveloped local innovation ecosystems – Start-ups in the Global South often lack capital, access to large language models (LLMs), and fair regulatory environments.

5. Fragmented policy frameworks – Inconsistent global rules on data privacy, IP, cybersecurity, and AI ethics create compliance burdens, especially for SMEs.

Key Building Blocks for Inclusive AI

The ICC’s framework identifies eight pillars that must be strengthened in parallel to achieve inclusive AI:

1. Infrastructure and connectivity – Investment in clean energy, broadband networks, and sustainable data centres.

2. Access to data and compute – Creation of diverse data commons and support for open-source AI tools.

3. Skills development – AI education from primary school to adult reskilling, with targeted support for women and youth.

4. Local innovation – Support for multilingual models, national AI hubs, and start-up-friendly regulation.

5. Ethical AI governance – Alignment with OECD, UNESCO, and G7/G20 principles to ensure trustworthy AI.

6. Enabling regulatory environments – Cross-border data flows, cybersecurity, and IP frameworks that strike a balance between innovation and rights protection.

7. Harmonised AI standards – Multistakeholder collaboration to develop and adopt interoperable, voluntary international standards.

8. Targeted initiatives for the Global South – Capacity-building programs such as CurrentAI and AI4D, supported by international donors and industry.

Strengths of the ICC Approach

The ICC’s policy paper is commendable for its holistic and pragmatic approach:

• Balanced view: It acknowledges both the promise and perils of AI.

• Concrete recommendations: Rather than abstract principles, the paper offers actionable steps for infrastructure, education, governance, and innovation.

• Emphasis on partnership: The ICC foregrounds the importance of public-private collaboration, multilateral frameworks, and community engagement.

• Alignment with global frameworks: Its reference to established ethical AI models (OECD, UNESCO, UN) provides consistency and legitimacy.

Points for Further Consideration

While the ICC's roadmap is robust, several gaps and areas merit further emphasis:

1. Accountability mechanisms: The paper highlights ethics but is less clear on how to enforce compliance or address harms caused by biased or unsafe AI models.

2. Sustainability concerns: The resource intensity of AI systems (especially water and energy use in data centres) is acknowledged but needs firmer regulatory and innovation commitments.

3. IP rights tension: While recommending balance, the ICC glosses over the acute tensions between generative AI systems and copyright/IP law, especially in the context of data scraping.

4. Geopolitical risks: The recommendations could go further in addressing how geopolitical tensions (e.g. data localization laws, AI nationalism) may undermine global cooperation and standard-setting.

5. Civic participation: Inclusive AI is also about power—who defines the problems AI solves and whose values are embedded in its logic? Marginalised voices need structural inclusion in AI design and governance.

Recommendations for Stakeholders

For Governments:

• Develop inclusive national AI strategies rooted in local needs and global ethical norms.

• Invest in AI infrastructure, education, and open data initiatives with a focus on under-resourced regions.

• Enact and enforce data privacy, cybersecurity, and IP regulations that empower citizens and creators without stifling innovation.

• Support cross-border data sharing, particularly in scientific and humanitarian domains.

For Businesses:

• Make multilingual, culturally sensitive AI models a strategic priority.

• Share non-sensitive training data and invest in open-source tools to support local innovators.

• Lead workforce upskilling initiatives, especially in SMEs and in partnership with education providers.

• Adopt and report adherence to voluntary AI standards (e.g. OECD, G7 Hiroshima Code of Conduct).

For Civil Society and Academia:

• Act as watchdogs, advocates, and co-creators of ethical AI policies.

• Develop context-relevant AI literacy programs, especially for underserved communities.

• Ensure AI systems reflect diverse epistemologies, languages, and value systems.

• Participate actively in global and local standard-setting and policy forums.

For Multilateral Bodies and Donors:

• Fund capacity-building programs like AI4D and CurrentAI that support local ownership of AI in developing nations.

• Facilitate knowledge sharing, joint R&D, and policy harmonisation efforts.

• Establish AI inclusion impact metrics to evaluate progress across countries and regions.

Conclusion

The ICC’s policy paper on inclusive AI offers a timely and necessary call to action. It makes clear that the full promise of AI—for innovation, development, and human progress—can only be realized if it is truly inclusive. This demands systemic changes in infrastructure investment, data governance, regulatory frameworks, education, and business practices.

Inclusive AI is not just a moral imperative—it is a strategic necessity. It’s time for all stakeholders to shift from intention to implementation and ensure that AI works for everyone, everywhere, every day.

Citation:
ICC (2025), Policy paper on Achieving Inclusive AI. www.iccwbo.org