Digital Solutions
Embracing AI To Accelerate Achieving Programmatic And SDG Goals
By Michael Mwangi
At the apex of development sector project planning is achieving Sustainable Development Goals . Plans which are guided by funding , communication , media , stakeholder engagement , M & E , policy influencing to create positive social impact , economic prosperity and environmental conservation . None profit and for-profit projects like to juggle words like evidence , result areas , milestones , innovation , capacity building , thought leadership expertise , financial competence , Return-On-Investment ( ROI ), Level-of- Effort ( LoE ) amongst others , and they are many ‘ key words ’ used to demonstrate competence to deliver on the project objectives .
Some of the areas which steer the development sector are Public Health , Sustainable Livelihood , Education , Water Sanitation & Hygiene , Women & Child Development , Environment & Sustainability , Agriculture & Rural Development , Governance , Urban Development , Micro Finance , just to name a few . The list is endless .
Conducting a thorough needs assessment is the first step in understanding the challenges and opportunities within communities . It involves engaging with community members to gather data , to identify priorities , strengths , and areas for improvement .
Over and above needs assessment , project cycles also need to have data to understand
AI facilitates evidence-based policymaking by analyzing data trends , evaluating program outcomes , and identifying areas for improvement . This data-driven approach empowers policymakers to make informed decisions , allocate resources more effectively , and maximize the impact of development interventions . social dynamics , mobilise resources and determine what collaboration and partnerships to work with . Capacity building another fundamental of project cycles also involves leveraging media strategies for communication , monitoring and evaluation and learning , sustainability Implementation and exit strategy planning . Whatever the need plan or goal data is critical to succeed . The Implication is that project leaders must keep up with innovation in the technology curve .
Despite the vast potential of Artificial Intelligence ( AI ) to produce new evidence , provide accurate specific data , streamline processes , enhance innovation and communication , its adoption in the development sector remains limited . Project leaders , must spearhead efforts to foster external development partnerships , cultivate AI expertise , and instill an entrepreneurial mindset to harness the transformative power of AI effectively .
The challenge lies in aligning public leadership with the community , country and UN Sustainable Development Goals to provide effective decision support for resource allocation .
Predicting Unmeasurable Wealth
In developing countries , collecting data on basic economic quantities , such as wealth
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