WSIS Action Line C7 E-agriculture - Advancing Trusted Data Governance, Inclusive AI, and Digital Public Goods to enable scalable DPI and collaborative, Multilingual Innovation Ecosystems for Agrifood Systems Transformation

She argues that digital technologies have clear benefits for agri-food systems, including improving how food is produced and distributed and helping farmers access timely information. However, these benefits are not automatic, and without proper governance and enabling frameworks, digitalisation can deepen existing inequalities instead of supporting underserved rural communities.

She states that digital technologies are increasingly shaping how food is produced, distributed and consumed, and that they can help farmers access timely information and improve early warning systems . She then warns that these benefits are not automatic and that without the right governance and framework, digitalisation could reinforce existing inequities, while stressing that the aim is to serve underserved communities and rural populations .

She presents the session’s central framing question as how countries can use data governance, inclusive AI and digital public goods to build scalable digital public infrastructure for transforming agri-food systems. Her framing emphasises that technology must be considered alongside the wider ecosystem needed to make solutions trusted, scalable and locally relevant.

She explicitly introduces the session’s theme as the question of how data governance, inclusive AI and digital public goods can help countries build scalable digital public infrastructure for agri-food system transformation . She also adds that the session is an opportunity to look beyond technology to the broader ecosystem and enabling conditions needed to make solutions trusted, scalable and locally relevant .

In her closing summary, she concludes that digital transformation in agriculture is not simply a technical matter. Instead, progress depends on a broader set of conditions including governance, inclusion, institutional capacity, interoperability and trust.

In closing, she says the discussion showed that the agenda depends not only on technology but also on governance, inclusion, institutional capacity, interoperability and trust .

He argues that the debate has evolved beyond whether to digitise agriculture. The more important question now is how to ensure that each new wave of digital innovation is people-centred and built to be trusted, interoperable, affordable and inclusive.

He notes that although AI has rapidly become foundational, many long-standing access barriers for rural people remain, including connectivity, digital skills and service access . He then reframes the core question as no longer simply how to digitise agriculture and close the digital divide, but how to ensure that each new generation of digital innovation remains trusted, interoperable, affordable, inclusive and designed around people rather than technology .

He stresses that digital transformation succeeds only when technology is accompanied by institutional, policy and social alignment. Lasting impact comes from trust and from coordinating business models, institutions and human behaviour, not from technical tools alone.

He says the community has learned that technology alone does not transform agri-food systems and that successful innovation happens when technology, institutions, policies, business models and human behaviour evolve together and align . He also adds that adoption depends as much on trust as on technology and on farmers’ capacity to take risks .

He identifies fragmentation as a structural obstacle preventing digital agriculture from scaling effectively. When applications, datasets and platforms are disconnected or closed, costs rise, innovation slows and impact is limited.

He explicitly says that one of the greatest obstacles to scale is fragmentation, describing isolated applications, closed data sets and incompatible platforms as factors that increase costs, slow innovation and limit impact .

He argues that DPGs and DPI are essential because they provide the foundations for digital ecosystems that can scale. Their value lies in openness and interoperability, which help avoid fragmentation and support broad public value.

He says that because fragmentation is such a major challenge, digital public goods and digital public infrastructure have become very important . He explains that they provide foundations for ecosystems that are open, interoperable and scalable rather than fragmented into disconnected digital islands . He also adds that successful countries invest in digital public infrastructure, digital public goods, open standards and open source solutions to reduce costs, encourage collaboration and prevent digital monopolies .

She presents trusted data as a basic requirement for inclusive digital transformation in agriculture. In her view, trusted data underpins better decision-making, improved services and sustainable innovation across agri-food systems.

She explains that trusted data is the foundation of inclusive digital transformation because it enables better decisions, stronger services and sustainable innovation in agri-food systems .

She argues that the promise of digital transformation is still constrained by unresolved governance problems around data. These problems include fragmentation, poor interoperability, weak privacy and security protections, unclear rules on consent and ownership, and inadequate access to high-quality trusted datasets.

She lists continuing challenges such as fragmentation of data ecosystems and governance issues when introducing the topic . She then specifies key barriers in trusted data, including fragmentation, limited interoperability, privacy and security concerns, problems around consent and data ownership, data quality issues, and limited access to trusted datasets .

She supports the use of AI in agriculture but insists it must be deployed responsibly and inclusively. She highlights that current obstacles include biased algorithms, underrepresentation of certain groups, weak AI skills in rural areas, and unresolved concerns about transparency, accountability and ethics.

She says AI is transforming agri-food systems and creating significant opportunities that farmers also need to benefit from . She then identifies major challenges for inclusive AI, including bias in algorithms, underrepresentation of some groups, limited data skills and AI capacity in rural areas, and the need to ensure transparency, accountability and ethics in AI .

She argues that FAO has institutionalised digital agriculture in its strategic planning and produced substantial results over 20 years. These include large-scale knowledge-sharing communities, digital platforms, AI guidance, DPG activity and support for many countries’ digital agriculture strategies.

She says digital agriculture and digital technologies are embedded in FAO’s Strategic Framework 2022-31, including a major programme priority area and accelerators such as data, technology and innovation . She reports that over 20 years of WSIS Action Line C7 implementation, the e-agriculture community of practice grew from 19,000 members in 2024 to 170,000 members worldwide . She also cites FAO platforms supporting data-driven decision-making, the digital agriculture and AI roadmap guiding responsible AI, and support for more than 32 countries in developing national digital agriculture strategies .

She argues that FAO is actively developing and scaling DPG-based solutions rather than only adopting them. She also emphasises that these solutions are human-centred, support youth-led innovation and are implemented in ways that strengthen country ownership through participation.

She states that FAO embraces a DPI-based strategy not just as a user but as one of the builders of DPG solutions . She adds that FAO has been an member of the Digital Public Goods Alliance since 2022 with 11 certified DPGs, is scaling these solutions to farmers in a human-centred way, and is promoting them through innovation challenges such as Reboot the Earth with the UN Office of ICT . She also says FAO supports more than 32 countries through participatory approaches that promote ownership and respond to real needs .

She argues that no single actor can deliver digital transformation in agriculture alone. Trusted and scalable solutions require broad collaboration across public institutions, academia, development partners, the private sector and farmers themselves.

She says that beyond trusted data, AI and DPGs, collaboration and innovation ecosystems are also needed as foundational elements . She further notes that initiatives such as village programmes, innovation hubs and the Elevate programme strengthen multi-stakeholder collaboration among government, academia, development partners and the private sector while responding to grassroots needs . She closes by reaffirming commitment to multi-stakeholder cooperation involving government, private sector, academia, civil society and farmers .

He argues that in humanitarian and food security settings, data governance must begin with protecting vulnerable people. Trust depends on collecting only what is necessary, handling data securely and applying a strong duty of care when data moves across organisations and borders.

He explains that WFP operates in over 80 countries in complex situations and that data governance is mission-critical when deciding who receives food assistance, where supplies are pre-positioned and which communities are most at risk . He says WFP’s global data and AI strategies establish principles for data governance . He then states that every dataset represents vulnerable people, so WFP takes collection, storage and protection of personal data very seriously, avoids collecting or sharing more than required, and uses duty of care as a foundational element for safe cross-institutional and cross-border data use .

He argues that AI should be treated as a tool that accelerates decision-making, not as a substitute for human responsibility. This is especially important where decisions directly affect vulnerable people, so governance must ensure human oversight remains central.

He says that for WFP, AI is an accelerator and not a replacement for human judgement . He adds that there must always be room for human decision-making, especially when decisions affect vulnerable people, and that as AI and data increasingly inform who receives assistance, human oversight becomes critical .

He argues that repeatedly building similar digital agriculture systems in separate countries and projects wastes resources and creates sustainability problems. Reusable and adaptable digital public goods provide a more efficient and sustainable alternative.

He explains that the Digital Public Goods Alliance works to align how donors and governments reuse digital technologies for sustainable development . He then says that similar farmer registries, advisory platforms and market systems keep being rebuilt country by country and project by project, each with its own funding lifecycle and sustainability challenges . As an alternative, he proposes reusable and readaptable DPG components and notes that the DPGA registry already includes over 200 certified and verified DPGs .

He argues that technical certification does not by itself make DPGs effective or legitimate. They must also be governed in ways that build trust, ensure transparency and allow local adaptation to real agricultural and linguistic contexts.

He says that being certified is not enough and strongly agrees that trust is one of the key issues . He argues that the biggest inefficiency in digital agriculture is not technical but institutional capability . He then explains that governance matters because code, data and AI systems behind advisory services need to be verified and adapted to actual needs such as local crops, local practitioners and especially local languages, instead of operating as black boxes .

He argues that DPGs only become truly valuable when they can interoperate through open standards. Interoperability allows separate digital components to connect and function as a coherent public-interest ecosystem.

He states that infrastructure-level value depends on interoperability . He gives the example that when tools comply with open standards, a payment rail can talk to an early warning system and this kind of composition is only possible when there is openness by default .

He argues that the issue is no longer whether AI and DPI can transform agriculture in Africa, but whether they can be delivered at scale across a highly diverse continent. The challenge is continental deployment across many countries with different laws, regulations and development realities.

He says most people no longer question whether AI or DPI can transform agriculture, and that the real question is how to ensure they actually reach farmers, entrepreneurs and policymakers at scale . He stresses that this means continental scale, describing Africa as a continent of 1.4 billion people with over 50 different realities, laws and regulations, and noting that agriculture remains vital as the population is expected nearly to double by 2050 .

He argues that both DPI and AI already have practical use cases that can directly benefit farmers. DPI helps connect farmers to essential services, while AI supports better agricultural decisions and resilience through forecasting and detection tools.

He lists practical DPI benefits, saying a farmer can access digital identity, receive digital payments, obtain weather services, insure crops, and access input subsidies and market information . He also says AI can improve crop disease detection, support precision agriculture, forecast climate, predict yields and strengthen early warning systems .

He identifies fragmentation as the main barrier preventing Africa from unlocking the benefits of AI and DPI in agriculture. When actors build separate systems and standards without planning for interoperability, the result is duplication, inefficiency and higher costs.

He explicitly says that the biggest obstacle today is fragmentation . He explains that countries, donors, partners and projects too often build separate platforms, separate datasets and separate standards without interoperability in mind, leading to duplication, inefficiencies, higher costs and continental interoperability problems .

He argues that Africa needs collective, regional action rather than isolated national or project-based efforts. Harmonised frameworks, shared DPGs and continental learning mechanisms are necessary to avoid repeated disconnected pilots and unlock broader opportunities.

He says Smart Africa is in this space and brings together 42 African countries at head-of-state level through ministers of ICT and agriculture . He explains that the aim is to harmonise interoperability frameworks, trusted data governance and shared DPGs, while also creating mechanisms for learning and innovation . He concludes by saying Africa does not need a new generation of disconnected pilots, but rather regional cooperation that looks beyond the country level and national focus .

He argues that digital agriculture can only flourish when there is a strong infrastructure base combined with appropriate regulation. Infrastructure by itself is insufficient if the rules needed for a healthy digital marketplace are missing.

He says that any meaningful application marketplace first needs the ‘soil’ over which things can grow, which in ICT means sound infrastructure along with the right regulations . He adds that even where infrastructure or fibre exists, the digital marketplace often does not flourish because the right regulations are not in place .

He argues that regulation should actively lower costs and make market entry easier. Measures such as infrastructure sharing, wholesale arrangements and public-private partnerships can improve affordability and stimulate infrastructure investment.

He specifies that the right regulations can include sharing infrastructure to reduce costs and barriers to entry, wholesaling, and dividing the market into parts that make business entry easier . He also says public-private partnerships should be encouraged to help increase investment in infrastructure .

He argues that connectivity is only one part of inclusion. Rural communities also need the skills, affordability and trusted services necessary to use digital tools meaningfully.

He says digital readiness is another essential aspect and that populations must be able to use digital assets for e-applications to grow . He notes ITU’s work on digital skills through the ITU Academy and says a combination of digital skills, affordable access and trusted digital services is needed for communities to benefit .

He argues that digital agriculture works best when policy planning is coordinated across sectors rather than handled in silos. Open data sharing, spectrum innovation and inclusive design are all necessary to support effective agri-food transformation.

He says openness is needed and that connectivity, agriculture and rural development policies should be planned together using data-driven planning and cross-silo data sharing . He adds that innovation can be enabled through spectrum sharing or innovative spectrum policies that support AI, IoT and next-generation networks in agriculture . He also emphasises that products for farmers should be designed with inclusion in mind and gives the example of ITU’s work with Lesotho on the open-source Agrivisory application and its broader data marketplace efforts .

She argues that effective digital agriculture must begin with people rather than tools. Involving smallholder farmers throughout design and implementation helps ensure that services fit local realities and earn users’ trust.

She says that although AI and digital technologies create significant opportunities, digital technologies alone do not drive transformation . She then states that, from IFAD’s experience, successful digital agriculture starts with people and the realities of smallholder farmers, and that engaging farmers throughout design and implementation makes solutions more tailored, trusted and responsive to local priorities .

She argues that inclusion cannot be an afterthought in digital agriculture. Services must be deliberately designed to reach women, youth and marginalised groups, including through multilingual and low-connectivity-friendly channels.

She says digital inclusion should be built in from the outset to support women, youth and marginalised groups . She adds that services should support local languages, work in low-connectivity environments, and provide multiple access channels including radio, SMS, USSD and voice-based services to improve access and address digital literacy gaps .

She argues that inclusive digital agriculture needs strong institutional and technical foundations. Registries, data governance frameworks and interoperable ecosystems make secure data sharing and coordinated service delivery possible.

She states that sustainable digital transformation requires strong digital foundations and depends on trusted data governance, digital public infrastructure and interoperable systems . She then says IFAD supports countries through digital farmer registries, national data governance frameworks and interoperable digital ecosystems that enable secure data sharing, better coordination and more efficient service delivery .

She argues that sustainability depends on country ownership and local institutional capacity, not just on launching digital tools. The real measure of success is whether people’s livelihoods and resilience improve through better access to services and opportunities.

She says digital solutions are more sustainable when embedded in national institutions and supported by local capacities so that countries have ownership . She concludes that success should be measured not by the number of digital tools deployed, but by whether rural women, youth and marginalised communities gain better access to information, markets, finance and opportunities that improve livelihoods and resilience .