Disclaimer:
Please be aware that the content herein has not been peer reviewed. It consists of personal reflections, insights, and learnings of the contributor(s). It may not be exhaustive, nor does it aim to be authoritative knowledge.
Learnings on your challenge
What are the top key insights you generated about your learning challenge during this Action Learning Plan? (Please list a maximum of 5 key insights)
The integration of generative AI in public sector water management requires not only technical adaptation but also deep organizational change management, including addressing resistance and building digital skills.
Siloed information and manual processes are major bottlenecks; digital solutions must be paired with process redesign and improved internal communication.
Ethical and legal frameworks are essential for AI adoption in government, especially regarding data protection, transparency, and accountability.
Early and continuous involvement of end-users (public officials, technical staff) in co design and testing increases acceptance and relevance of AI tools.
Multi-stakeholder collaboration (government, academia, private sector, and international organizations) accelerates learning and solution development, but requires clear governance and shared objectives.
Considering the outcomes of this learning challenge, which of the following best describe the handover process? (Please select all that apply)
Other
Can you provide more detail on your handover process?
The project’s outputs (AI solution prototype, change management guide, and implementation roadmap) have been formally delivered to the State Water Commission of Querétaro and shared with UNDP Mexico’s digital innovation team.
Key learnings and recommendations will be integrated into the Country Office’s digital transformation agenda.
While the solution has not yet scaled within the Comisión Estatal de Aguas (CEA) of Querétaro the methodology and tools could be of use for replication in the country officce.
Ongoing support and knowledge transfer mechanisms (e.g., documentation, training sessions, and a change committee) have been established to ensure sustainability.
Please paste any link(s) to blog(s) or publication(s) that articulate the learnings on your frontier challenge.
Data and Methods
Relating to your types of data, why did you chose these? What gaps in available data were these addressing?
Traditional administrative data alone did not capture bottlenecks or user pain points; user feedback and workflow logs provided critical context for process redesign.
Legal documents were necessary to ensure compliance and ethical use of AI.
AI-generated analytics enabled real-time monitoring and identification of inefficiencies that were previously invisible.
Why was it necessary to apply the above innovation method on your frontier challenge? How did these help you to unpack the system?
Action learning and codesign ensured that solutions addressed real needs and built ownership among stakeholders.
Rapid prototyping and user testing allowed for iterative improvement and early identification of technical and organizational barriers.
Change management frameworks were essential to address resistance and craft recommendations to facilitate adoption in the future.
Partners
Please indicate what partners you have actually worked with for this learning challenge.
Please state the name of the partner:
State Water Commission of Queretaro (Comisión Estatal de Aguas de Querétaro)
What sector does your partner belong to?
Government (&related)
Please provide a brief description of the partnership.
State Water Commission of Queretaro (Comisión Estatal de Aguas de Querétaro) is our “client”, this means that the AI solution is being designed for their use in the processes of water feasibility checks needed to manage access to water resources in the state. They are providing us with access to their information, data and personnel to conduct the learning cycle. Furthermore, it is expected that they will adopt the solution we test and scale it afterwards on their own.
Is this a new and unusual partner for UNDP?
No
Please indicate what partners you have actually worked with for this learning challenge.
Please state the name of the partner:
Ministry of Finance
What sector does your partner belong to?
Government (&related)
Please provide a brief description of the partnership.
The Ministry of Finance acted as a digital transformation champion and facilitated inter-agency collaboration. They are legally responsible for the Digital Strategy of the State of Queretaro. They oversee the design and roll out of digital solutions in all the ministries and government entities of the state. They are our key liason in the government and help us reach out to local actors, access resources to implement our learning cycle (e.g. venues, data, events) and connect our pilot to the state’s strategy to ensure its adoption.
End
Bonus question: How did the interplay of innovation methods, new forms of data and unusual partners enable you to learn & generate insights, that otherwise you would have not been able to achieve?
The combination of rapid design sprints and co-design sessions with diverse partners enabled rapid identification of both technical and organizational barriers. Access to new data sources (user feedback, workflow analytics) revealed hidden inefficiencies and resistance points. Collaboration with grad students from CIDE brought fresh perspectives and accelerated solution development, leading to more robust and contextually relevant outcomes.
Please upload any further supporting evidence / documents / data you have produced on your frontier challenge that showcase your learnings.
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6Clean water and sanitation
11Sustainable cities and communities
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