How can digital innovations support climate action. Moving from digial technologies being the problem to contributing towards the fight agains climate change. This presentation provides an overview of the BMZ-supported digital and green transformation programs from around the world. Digital technologies and data can make a differnce, however it needs to be given a purpose and fit the needs of people, local communities and the planet.

1. Digital4Climate – Leveraging digital
innovations & data for climate action
Bjorn-Soren Gigler, Head of Data Economy Program
Digital Transformation Cluster
bjorn-soren.gigler@giz.de
UN Climate Change Global Innovation Hub Pavillon @COP28
Digital readiness of developing countries: how it can accelerate climate action
December, 6, 2023

2. Intersection between Green and
Digital Transformation
• Paris Agreement: need for innovations and technology pull
and push
• Green and Digital transformation are taking place at the
same time and are closely intertwined with each other
• Digital innovations (AI, Blockchain, IoT, supercomputing)
provide unprecedented opportunities to enhance
sustainability of economy & society
• Radical new thinking and business models are
required- Business as usual will not be sufficient to
address the climate crisis
• Getting innovations out of the lab into the market-
Commercialization of digital clean tech solutions is an
important challenge
• Scale-up of clean tech innovations: 2 valleys of death. Lack
of early-stage financing and growth financing- most
innovative startups

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Shaping the Twin Transition
The ICT sector is estimated to
make up
3.7%
of greenhouse gas emissions,
expected to rise further if not
properly addressed.
ICT has the potential to reduce
greenhouse gases by
20%
until 2030.
Shaping digital
transformation in a
climate-friendly way
Harnessing the potential
of digital technologies
to achieve climate goals
Twin Transition
Digital transformation + climate transition
Green Tech,
Green Data
Climate
Impact
Adaptation
Climate
Impact
Mitigation

4. The Digital Economy Index (DEI) has six pillars, or sub-indices. These measure the
foundations for digital transformation, the prevalence of required enabling factors, and the
digital transformation of the economy and government, and include:
Connectivity Use of Internet
Services
Human Capital
and Skill
Development
Entrepreneurship
and Innovation
Digital Integration
in the Market
Digital
Government and
Service Delivery
assess the
foundations for digital
transformation
investigate the prevalence of
required enabling factors in
the economy and the society
measure the depth of changes in
the everyday operations of key
arenas for digital transformation
Digital Economy Index

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Soren Gigler: (2011) Informational Capabilities - The Missing Link for the Impact of ICT on
Development
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Digital Readiness: digital and data capabilities

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Titel der Präsentation
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• Support the monitoring and evaluation of
NDCs (national determined contributions).
• Improve measurement, verification and
reporting of CO2 emissions across sectors.
• Enhance data-driven decision-making by
policy makers, consumers and investors
• Facilitating climate finance through improved
visibility and credibility (international
cooperation)
Data4Climate – Paris Agreement

7. Digital & Green Transition Priority Areas
1) Enabling Environment and Policy Advice:
• provide policy advice to governments to develop twin transition policies and support the
development of national strategies and create the vision and enabling conditions for
digital for climate action and sustainability
2) Capacity Building and Technical Assistance:
• to support partner countries by raising the awareness, enhance the institutional capacities
and provide technical assistance to policymakers about the opportunities and risks of the
digital and green transition
3) Innovation Ecosystems and Digital 4 Climate Hubs
to support the development of national and local innovation ecosystem
through a network of Digital Innovation Hubs that link digital innovative
startups, with research institutions, corporates, governments and investors
3) Innovation Finance and Sustainable Digital Infrastructure
to provide technical assistance to public and private partners in the preparation of a
portfolio of bankable investment programs in green and secure infrastructure
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8 Enabling a Twin Transition

9. Data Economy Program
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• First draft of guidelines for developing
climate friendly data infrastructure
have been developed through DDP
• Support of analytical work on Catalyzing
the Green Digital Transformation Report
Promotes a sustainable data-driven economy by supporting partner countries to implement data governance
policies fostering the sharing of data to drive local socio-economic and ecological value creation.
The Data Economy Flagship is supporting African Partner Countries​,
improving the conditions for a value-generating data economy that
benefits all citizens of AU countries
Areas of action:
• Data Policy: Developing and supportsing the implementation of a
data regulatory framework in Africa to enable countries to make
sovereign use of their data
• Data Value Creation: Fostering data-driven solutions with local
partners by testing secotrial data-driven use-cases and regulatory
sandboxes
• Green Data Infrastructure: Support the development of bankable
green digital and data infrastructure projects
• Capacities on Data: Strengthening government and private sector
knowledge for a value-generating data economy
GIZ project lead: bjorn-soren.gigler@giz.de
Collaboration with the
World Bank, ITU , UNEP

10. Increase of GHG Emissions of the Digital sector
Until 2040 global GHG emissions of the ICT sector are
expected to reach 6-7%
Rapid growth of data centers is an
important source of GHG emissions

11. Implementation partners: World Bank, Digital
Development Programme
Key Actions
• Enhance global awareness & inspire action
 Establish a technical working group with interested DDP
partners
 Disseminate knowledge, tools, best practices and case studies
 Support regional and country level dialogue
• Create actionable knowledge:
 develop guidance material through needs assessment and
stakeholder consultations
 Use for lending and investment project preparation within the
WB Group
• Test and support adoption at scale
 Apply, test, and refine developed knowledge in digital
operations
 Green data centers will be among the focus areas
 Support platforms/ partnership for scale (e. g. open-data
software platforms)
Green Digital Infrastructure
Objective
Reduce negative climate impact of the digital economy and
leverage its enabling role for accelerated action on climate
change adaption/ mitigation
Approach
• Synergy development among DDP (Digital
Development Programme) partners & stakeholders
• Regional and country-level policy dialogue
• Knowledge exchange
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13. Implementation partners: GSMA
Key Actions
• Mapping of the Indonesian climate-tech ecosystem:
exploring the role that digital technology is (or could be)
playing to support climate mitigation, adaptation, and
resilience
• Public-private sector dialogues, strategic partnerships, and
capacity building
• Advise for government & existing initiatives on data-driven
approaches
• Showcasing and publicising results and learnings of the hub
• Tailored support for local innovators to improve and
implement their solutions
• Drive sustainable energy access and green economic
development in rural areas
• Support and scale digital approaches on waste management
and circular economy
Digital Transformation Centers- Mobile Innovation Hub
Indonesia
Objective
Support Indonesia unlocking the potential of digital
technology to achieve sustainable, low-carbon and climate-
resilient development outcomes
Approach
Focus on:
• Sustainable energy and green economic development
• Digitalisation of waste management
• Natural resource management (NRM)
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15. Implementation partners: Lacuna Fund
(Rockefeller Foundation, Wellcome Trust etc.)
Lacuna Fund – Accessible data for local climate action
Objective
• Improve planning for and response to climate impacts
through open AI innovation
• Promote green development and better understand
climate harms on health and livelihoods
Approach
• Address gaps in climate data in partner
countries
• Focus on the promising sectors of renewable
energies & agriculture/ forestry
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Key Actions
• Support the creation, aggregation, and maintenance for
training and valuation of machine learning models by and
for local communities
• Promote sharing of data, best practices, AI models:
establish a global exchange on AI innovation and climate
protection
• Applications:
 Open local training data from the Global South
 Earth observation data for food security (e. g.
automated crop survey for department of agriculture)
 Satellite data for climate-friendly energy supply (e. g.
identify locations for green solar-based mini grids)

16. • Aim: Remote sensing and AI to support widespread data
collection and analysis of crop yield estimates and predicted
crop failure at scale
• For whom: Small-holder farmers in rural Africa & policy
makers
• For what: Predictive climate change mitigation
recommendations (web app, mobile) based on crop health,
weather predictions, specific soil conditions for improved
agricultural practices (irrigation or selection of alternative
crops); interventions for subsidies
• How: Open sourcing of data and models on land-use/farm
boundary estimation, image-based dataset that phenotypes
crop varieties through crop cycle (Radiant Earth ml hub)
• Why Artificial Intelligence? Near-real-time, directly
implementable CC-mitigation recommendations to
smallholder farmers on village level
AI for a Food and Nutrition Early Warning System
FAIR Forward – Artificial Intelligence for all.
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17. • Aim: Use AI to better identify forests with
high carbon stock and protect them
• Main partners: High Carbon Stock
Approach (HCSA) and ETH Zürich
• For whom: Small-holder farmers, commodity
sectors, NGOs and local/regional governments for
sustainable agricultural planning, forest protection
and sustainable supply-chain management
• For what: All these groups can better identify
forests with high carbon stock and therefor better
protect them
• How: Data and AI models for maps will be and
made openly accessible to create broad access to
this highly advanced tech and enable local
stakeholders to build on it
• Why Artificial Intelligence? AI makes the HCS
approach more efficient, less expensive, and adds
the ability to scale across geographies and regions
High Carbon Stock Approach Indonesia
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