SMART BUILD

For Smart Build, a successful first Global Dialogue on AI Governance would deliver practical, inclusive, and action-oriented outcomes that accelerate responsible AI adoption globally. First, the Dialogue should establish a clear global framework for ethical, transparent, and accountable AI governance, ensuring AI is safe, human-centric, and aligned with the United Nations Sustainable Development Goals (SDGs). This framework should address data privacy, fairness, cybersecurity, bias mitigation, and responsible AI deployment. Second, it should create stronger international cooperation mechanisms between governments, the private sector, startups, academia, and development organizations to bridge the AI divide between developed and developing countries. Emerging economies like Bangladesh need access to AI knowledge, funding, infrastructure, and capacity-building opportunities. Third, the Dialogue should promote sector-specific AI implementation strategies for high-impact sectors such as climate resilience, smart infrastructure, water and wastewater management, agriculture, healthcare, education, and industrial automation. Fourth, it should encourage funding platforms and innovation matchmaking opportunities for startups and youth-led innovators developing impactful AI solutions for sustainability and economic development. Finally, success would mean producing a concrete action roadmap with measurable commitments, pilot initiatives, and follow-up mechanisms to ensure that discussions lead to implementation. At Smart Build, we believe AI governance should not only regulate risks but also unlock innovation for sustainable development, empowering youth, industries, and nations to build a smarter, greener, and more inclusive future.

• Social, economic, ethical, cultural, linguistic and technical implications of AI
• AI capacity-building
• Protection and promotion of human rights
• Open-source software, open data and open AI models

At Smart Build, our priorities are driven by the need to ensure AI creates sustainable, inclusive, and measurable impact, especially in developing countries like Bangladesh. AI capacity-building is critical because many emerging economies face gaps in skills, infrastructure, and access to AI technologies. We actively work on youth empowerment and innovation programs to build future-ready AI talent. Safe, secure and trustworthy AI is essential for deploying AI in critical sectors such as water management, industrial automation, smart infrastructure, and climate resilience, where system reliability and security directly affect lives and the environment. Transparency, accountability, and human oversight are important to ensure AI systems remain ethical, explainable, and aligned with human decision-making, especially in industrial and public-sector applications. Finally, the social, economic, ethical, cultural, linguistic, and technical implications of AI are highly relevant because AI must be inclusive and adaptable to local contexts, languages, and socioeconomic realities. In countries like Bangladesh, localized AI solutions can bridge development gaps while respecting culture and ethics. We believe these priorities will help create an AI ecosystem that is innovative, responsible, and accessible for all.

Yes. From the perspective of Smart Build, several important cross-cutting and emerging issues deserve stronger attention in the Global Dialogue on AI Governance. First, AI for climate resilience and sustainability should be recognized as a distinct priority. AI can play a transformative role in addressing climate change through smart water management, disaster prediction, energy optimization, sustainable agriculture, and pollution monitoring. Second, AI access and affordability remain major concerns for developing countries. Beyond capacity-building, affordable access to computing power, datasets, cloud infrastructure, and AI tools is essential to reduce the global AI divide. Third, youth empowerment and future workforce transformation should be highlighted. AI is rapidly reshaping industries and job markets, making reskilling, digital literacy, and innovation-driven entrepreneurship urgent priorities. Fourth, AI for industrial development and smart manufacturing is an emerging area with significant economic potential, particularly for countries with strong manufacturing sectors. AI can improve efficiency, safety, predictive maintenance, and ESG compliance. Finally, global innovation matchmaking and financing mechanisms are needed to connect startups, innovators, governments, and development partners. Many impactful AI solutions fail to scale due to limited access to funding and partnerships. Addressing these cross-cutting issues would ensure that AI governance not only manages risks but also accelerates inclusive innovation, sustainable development, and economic growth worldwide.

In Bangladesh and across similar developing economies, gaps in AI governance are creating both challenges and opportunities, particularly in sectors such as manufacturing, textiles, climate resilience, agriculture, water management, and smart infrastructure—areas where Smart Build actively works. One major challenge is the lack of clear regulatory frameworks and standards for safe, secure, and trustworthy AI. This creates uncertainty for industries seeking to adopt AI in critical operations such as factory automation, wastewater treatment, predictive maintenance, and energy optimization. Another challenge is limited AI capacity, including shortages of skilled professionals, insufficient computing infrastructure, and limited access to quality local datasets. This slows innovation and widens the gap between developed and developing nations. Transparency and accountability gaps also create risks. Without proper oversight, AI systems may produce biased, inaccurate, or non-transparent decisions, especially in public services and industrial environments. At the same time, the opportunities are significant. AI can improve productivity in the textile and manufacturing sectors, strengthen disaster prediction and climate adaptation, optimize water and energy use, and accelerate sustainable urban development. For Bangladesh, AI governance that supports innovation while ensuring safety and inclusiveness can unlock economic growth, create jobs, empower youth, and improve global competitiveness. International cooperation, funding, and knowledge-sharing are essential to help developing countries responsibly adopt and scale AI solutions for sustainable development.

The Global Dialogue on AI Governance can play a transformative role in advancing international cooperation by creating an inclusive global platform where governments, private sector leaders, startups, academia, and development organizations collaborate on practical AI governance solutions. From the perspective of Smart Build, the Dialogue can help align global standards and best practices for safe, secure, transparent, and trustworthy AI while allowing flexibility for local adaptation in different economic and cultural contexts. It can also bridge the gap between developed and developing countries by promoting knowledge-sharing, technical assistance, and AI capacity-building initiatives. Countries like Bangladesh need access to skills development, infrastructure, funding, and policy guidance to responsibly scale AI solutions. The Dialogue can further act as a platform for international innovation matchmaking—connecting startups and innovators with governments, investors, industries, and global development partners. This can accelerate deployment of AI solutions in climate resilience, water management, industrial automation, smart infrastructure, healthcare, and agriculture. In addition, the AI Dialogue can support cross-border cooperation on emerging issues such as AI ethics, cybersecurity, data governance, misinformation, and environmental impacts of AI systems. Most importantly, it should produce actionable roadmaps, pilot programs, and measurable commitments rather than remaining only a discussion forum. By turning dialogue into implementation, the platform can help ensure AI becomes a force for inclusive innovation, sustainable development, and shared global prosperity.

The Global Dialogue on AI Governance should build upon and connect with existing global initiatives such as the UNESCO Recommendation on the Ethics of AI, the OECD AI Principles, the ITU AI for Good platform, and ongoing UN-led digital cooperation efforts. It should also align with industry and development-focused initiatives led by organizations such as the World Bank, regional development banks, and innovation-driven partnerships between governments, academia, and the private sector. From the perspective of Smart Build, these existing mechanisms provide a strong foundation for ethical frameworks, technical standards, and capacity-building efforts. However, they are often fragmented, with limited coordination between policy-level discussions and on-the-ground implementation, especially in developing economies like Bangladesh. The added value of the AI Dialogue would be its ability to unify these efforts under a single inclusive, action-oriented platform. It can serve as a bridge between global policy frameworks and practical deployment by facilitating real-world pilot projects, cross-border innovation matchmaking, and implementation-focused partnerships. In addition, the AI Dialogue can strengthen participation from startups, youth innovators, and SMEs—groups that are often underrepresented in global governance discussions but are key drivers of AI innovation. It can also support structured knowledge transfer, funding alignment, and capacity-building programs tailored to emerging economies. Most importantly, the Dialogue can shift global AI governance from fragmented principles to coordinated implementation—ensuring that AI is not only responsibly governed but also effectively used to drive sustainable development, climate resilience, and inclusive economic growth.

Different stakeholders can contribute meaningfully to the Global Dialogue on AI Governance by engaging through structured, multi-level participation models that ensure inclusivity, practicality, and implementation focus. Governments can provide policy direction, regulatory alignment, and national priorities, ensuring AI governance frameworks are grounded in public interest. International organizations such as the United Nations can facilitate coordination, neutrality, and global standard-setting. The private sector, including companies like Smart Build, can contribute real-world use cases, technological expertise, and scalable AI solutions in areas such as climate resilience, smart infrastructure, industrial automation, and sustainability. Startups, academia, and civil society should be actively included to ensure innovation, ethical oversight, and social accountability. Youth-led organizations and researchers can provide fresh perspectives on emerging risks and opportunities. In terms of structure, the AI Dialogue should adopt a hybrid format combining high-level plenaries with focused technical working groups. These groups should address sector-specific challenges such as AI in climate, health, industry, and public services. A strong emphasis should be placed on outcome-driven sessions, including pilot project design, cross-border partnerships, and funding matchmaking. Digital participation platforms should be integrated to ensure accessibility for stakeholders from developing countries like Bangladesh. Additionally, the Dialogue should include a continuous engagement mechanism beyond annual meetings, allowing stakeholders to track progress, share updates, and scale successful initiatives. This structure would ensure that the AI Dialogue becomes not only inclusive, but also action-oriented, bridging the gap between global policy discussions and real-world implementation.

In global AI governance discussions such as the Global Dialogue on AI Governance, several important voices remain underrepresented, particularly from developing and emerging economies. First, Global South countries, including nations like Bangladesh, often have limited representation in shaping AI standards despite being significantly affected by AI-driven economic and social transformations. Their inclusion is essential to ensure governance frameworks are globally equitable and context-aware. Second, startups, SMEs, and innovation-driven companies—such as Smart Build—are frequently underrepresented compared to large technology corporations, even though they are key drivers of applied innovation in sectors like climate tech, smart infrastructure, and industrial automation. Third, youth, technical practitioners, and grassroots innovators are often missing from high-level policy discussions. Yet they are the ones actively developing and deploying AI solutions in real-world environments. Fourth, communities affected by AI deployment, including workers in manufacturing, agriculture, and informal sectors, are rarely included, despite being directly impacted by automation, data systems, and digital transformation. To include these voices, the AI governance process should introduce structured participation quotas, regional representation mechanisms, and open digital consultation platforms. It should also support capacity-building programs that enable stakeholders from developing regions to meaningfully engage in policy discussions. Hybrid participation models—combining in-person forums with accessible virtual engagement—can further reduce barriers. Additionally, dedicated funding for participation from underrepresented regions and sectors can ensure equitable involvement. By broadening participation, AI governance can become more balanced, inclusive, and responsive, ensuring that global AI systems reflect the needs and realities of all societies, not only the most technologically advanced.

Innovative engagement formats for the Global Dialogue on AI Governance should prioritize inclusivity, real-world implementation, and cross-sector collaboration, moving beyond traditional panel discussions. First, challenge-based working groups can be introduced, where governments, industry players, startups like Smart Build, and researchers collaboratively solve specific governance or sectoral problems such as AI in climate resilience, water management, or industrial automation. Second, live pilot project showcases and AI sandboxes can allow participants to test governance frameworks in real-time applications, especially in sectors relevant to developing countries like Bangladesh. Third, global innovation matchmaking sessions can connect startups, investors, development agencies, and policymakers to facilitate partnerships, funding, and scaling of responsible AI solutions. Fourth, interactive policy simulation labs can help stakeholders understand the real-world implications of AI governance decisions through scenario-based exercises, improving practical policymaking. Fifth, open digital participation platforms with asynchronous engagement tools can ensure continuous global input beyond physical meetings, allowing youth, SMEs, and underrepresented communities to contribute meaningfully. Finally, sector-focused roundtables combined with field demonstrations can bridge the gap between policy and implementation, showcasing AI applications in agriculture, manufacturing, healthcare, and infrastructure. These formats would transform the AI Dialogue into an action-oriented ecosystem rather than a traditional conference, ensuring that outcomes lead to measurable impact, scalable partnerships, and inclusive global AI governance.

Several emerging policies, practices, and platforms demonstrate effective approaches to AI governance that balance innovation with responsibility. At the international level, the UNESCO Recommendation on the Ethics of AI provides a strong normative framework focused on human rights, transparency, and inclusivity. Similarly, the OECD AI Principles offer practical guidance on trustworthy AI, emphasizing accountability, robustness, and fairness. The ITU AI for Good initiative has also become a leading global platform for demonstrating real-world AI applications aligned with the Sustainable Development Goals. The United Nations digital cooperation efforts, including discussions on global digital compacts, are helping establish shared principles for emerging technologies while promoting cross-border collaboration. At the implementation level, regulatory sandbox approaches adopted in several countries allow innovators to test AI solutions under controlled environments, reducing risks while encouraging experimentation. This is particularly relevant for sectors such as healthcare, finance, and industrial automation. Open-source AI ecosystems and data-sharing initiatives are also important, enabling broader access to AI tools and reducing inequality in technological development. Platforms that support public-private partnerships and innovation matchmaking further help scale impactful solutions. From a developing country perspective such as Bangladesh, applied innovation is especially critical. Organizations like Smart Build are contributing by developing AI-driven solutions for smart infrastructure, water management, energy efficiency, and industrial automation-demonstrating how AI governance principles can be translated into real-world sustainability outcomes. Together, these approaches highlight the importance of combining global policy frameworks with local innovation ecosystems to ensure AI is safe, inclusive, and development-oriented.