๐ก๐ฎ๐๐ถ๐ด๐ฎ๐๐ถ๐ป๐ด ๐๐ต๐ฒ ๐๐ฎ๐๐ฎ ๐๐ฎ๐ป๐ฑ๐๐ฐ๐ฎ๐ฝ๐ฒ: ๐๐ฒ๐๐ผ๐ป๐ฑ ๐๐ฎ๐ฟ๐ธ ๐๐ฎ๐๐ฎ ๐ถ๐ป ๐๐๐ต๐ถ๐ผ๐ฝ๐ถ๐ฎ’๐ ๐๐ ๐๐ผ๐๐ฟ๐ป๐ฒ๐
One of the most persistent roadblocks to successful AI adoption globally is the often overlooked challenge of dark data - information collected but left unused, hidden in silos or stored in ways that make it difficult to retrieve. This overlooked asset not only delays innovation but also increases cybersecurity vulnerabilities.
While global organizations increasingly invest in unified data ecosystems-anchored in a single source of truth- our experience in Ethiopia exposes a different, even more fundamental issue.
In many cases, we’re not battling ๐ฑ๐ฎ๐ฟ๐ธ ๐ฑ๐ฎ๐๐ฎ - we’re battling a ๐ฑ๐ฎ๐๐ฎ ๐ฑ๐ฟ๐ผ๐๐ด๐ต๐.
Too often, the focus remains limited to capturing required financial or compliance data. Meanwhile, critical operational insights, institutional knowledge, and contextual understanding are either undocumented or managed informally or on the fly. This scarcity of structured, qualitative data makes even the early stages of AI readiness feel like a distant goal.
It’s a stark contrast: globally, companies are overwhelmed by unsearchable content; in Ethiopia, we’re often still grappling with how to consistently capture day-to-day business knowledge in the first place. Without a widespread data-first mindset in core operations, the adoption of transformative AI tools becomes even more difficult.
Yet, therein lies our opportunity.
Technologies like Google's Vertex AI Search, with its ability to extract meaning from even minimal or unstructured datasets, can help bridge this early-stage data gap. It proves that AI isn’t just a consumer of datasets-it’s a catalyst for uncovering value in what little we have and building from there.
So what must we prioritize in Ethiopia?
✅ ๐๐๐ถ๐น๐ฑ ๐๐๐ฟ๐ผ๐ป๐ด ๐ฑ๐ฎ๐๐ฎ ๐ด๐ผ๐๐ฒ๐ฟ๐ป๐ฎ๐ป๐ฐ๐ฒ ๐ณ๐ฟ๐ผ๐บ ๐๐ต๐ฒ ๐ด๐ฟ๐ผ๐๐ป๐ฑ ๐๐ฝ
✅ ๐๐ป๐๐ฒ๐๐ ๐ถ๐ป ๐๐ผ๐ผ๐น๐ ๐๐ผ ๐๐๐๐๐ฒ๐บ๐ฎ๐๐ถ๐ฐ๐ฎ๐น๐น๐ ๐ฐ๐ฎ๐ฝ๐๐๐ฟ๐ฒ ๐ฎ๐ป๐ฑ ๐บ๐ผ๐ป๐ถ๐๐ผ๐ฟ ๐ฎ๐น๐น ๐ณ๐ผ๐ฟ๐บ๐ ๐ผ๐ณ ๐ฑ๐ฎ๐๐ฎ
✅ ๐๐ป๐ด๐ฟ๐ฎ๐ถ๐ป ๐ฎ ‘๐ฑ๐ฎ๐๐ฎ-๐ณ๐ถ๐ฟ๐๐’ ๐ฒ๐๐ต๐ผ๐ ๐ถ๐ป ๐ฒ๐๐ฒ๐ฟ๐๐ฑ๐ฎ๐ ๐ฏ๐๐๐ถ๐ป๐ฒ๐๐ ๐ฝ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ๐
These foundational steps are not optional - they are essential for unleashing latest technologies / AI’s full potential.
But I’d love to widen the lens:
๐๐ฒ๐๐ผ๐ป๐ฑ ๐ฑ๐ฎ๐ฟ๐ธ ๐ฑ๐ฎ๐๐ฎ ๐ฎ๐ป๐ฑ ๐๐๐๐๐ฒ๐บ๐ถ๐ฐ ๐ฑ๐ฎ๐๐ฎ ๐ด๐ฎ๐ฝ๐, ๐๐ต๐ฎ๐ ๐ผ๐๐ต๐ฒ๐ฟ ๐ฐ๐ต๐ฎ๐น๐น๐ฒ๐ป๐ด๐ฒ๐ ๐ฑ๐ผ ๐๐ผ๐ ๐ฏ๐ฒ๐น๐ถ๐ฒ๐๐ฒ ๐๐๐ฎ๐ป๐ฑ ๐ถ๐ป ๐๐ต๐ฒ ๐๐ฎ๐ ๐ผ๐ณ ๐๐’๐ ๐ผ๐ฟ ๐น๐ฎ๐๐ฒ๐๐ ๐๐ฒ๐ฐ๐ต๐ป๐ผ๐น๐ผ๐ด๐ถ๐ฒ๐ ๐๐ฟ๐ฎ๐ป๐๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ถ๐๐ฒ ๐ถ๐บ๐ฝ๐ฎ๐ฐ๐ ๐ถ๐ป ๐๐๐ต๐ถ๐ผ๐ฝ๐ถ๐ฎ?
Let’s shape this journey together.
#Ethiopia #AI #DataGovernance #DigitalTransformation #Innovation #BusinessChallenges #DataStrategy
Too often, the focus remains limited to capturing required financial or compliance data. Meanwhile, critical operational insights, institutional knowledge, and contextual understanding are either undocumented or managed informally or on the fly. This scarcity of structured, qualitative data makes even the early stages of AI readiness feel like a distant goal.
It’s a stark contrast: globally, companies are overwhelmed by unsearchable content; in Ethiopia, we’re often still grappling with how to consistently capture day-to-day business knowledge in the first place. Without a widespread data-first mindset in core operations, the adoption of transformative AI tools becomes even more difficult.
Yet, therein lies our opportunity.
Technologies like Google's Vertex AI Search, with its ability to extract meaning from even minimal or unstructured datasets, can help bridge this early-stage data gap. It proves that AI isn’t just a consumer of datasets-it’s a catalyst for uncovering value in what little we have and building from there.
So what must we prioritize in Ethiopia?
✅ ๐๐๐ถ๐น๐ฑ ๐๐๐ฟ๐ผ๐ป๐ด ๐ฑ๐ฎ๐๐ฎ ๐ด๐ผ๐๐ฒ๐ฟ๐ป๐ฎ๐ป๐ฐ๐ฒ ๐ณ๐ฟ๐ผ๐บ ๐๐ต๐ฒ ๐ด๐ฟ๐ผ๐๐ป๐ฑ ๐๐ฝ
✅ ๐๐ป๐๐ฒ๐๐ ๐ถ๐ป ๐๐ผ๐ผ๐น๐ ๐๐ผ ๐๐๐๐๐ฒ๐บ๐ฎ๐๐ถ๐ฐ๐ฎ๐น๐น๐ ๐ฐ๐ฎ๐ฝ๐๐๐ฟ๐ฒ ๐ฎ๐ป๐ฑ ๐บ๐ผ๐ป๐ถ๐๐ผ๐ฟ ๐ฎ๐น๐น ๐ณ๐ผ๐ฟ๐บ๐ ๐ผ๐ณ ๐ฑ๐ฎ๐๐ฎ
✅ ๐๐ป๐ด๐ฟ๐ฎ๐ถ๐ป ๐ฎ ‘๐ฑ๐ฎ๐๐ฎ-๐ณ๐ถ๐ฟ๐๐’ ๐ฒ๐๐ต๐ผ๐ ๐ถ๐ป ๐ฒ๐๐ฒ๐ฟ๐๐ฑ๐ฎ๐ ๐ฏ๐๐๐ถ๐ป๐ฒ๐๐ ๐ฝ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ๐
These foundational steps are not optional - they are essential for unleashing latest technologies / AI’s full potential.
But I’d love to widen the lens:
๐๐ฒ๐๐ผ๐ป๐ฑ ๐ฑ๐ฎ๐ฟ๐ธ ๐ฑ๐ฎ๐๐ฎ ๐ฎ๐ป๐ฑ ๐๐๐๐๐ฒ๐บ๐ถ๐ฐ ๐ฑ๐ฎ๐๐ฎ ๐ด๐ฎ๐ฝ๐, ๐๐ต๐ฎ๐ ๐ผ๐๐ต๐ฒ๐ฟ ๐ฐ๐ต๐ฎ๐น๐น๐ฒ๐ป๐ด๐ฒ๐ ๐ฑ๐ผ ๐๐ผ๐ ๐ฏ๐ฒ๐น๐ถ๐ฒ๐๐ฒ ๐๐๐ฎ๐ป๐ฑ ๐ถ๐ป ๐๐ต๐ฒ ๐๐ฎ๐ ๐ผ๐ณ ๐๐’๐ ๐ผ๐ฟ ๐น๐ฎ๐๐ฒ๐๐ ๐๐ฒ๐ฐ๐ต๐ป๐ผ๐น๐ผ๐ด๐ถ๐ฒ๐ ๐๐ฟ๐ฎ๐ป๐๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ถ๐๐ฒ ๐ถ๐บ๐ฝ๐ฎ๐ฐ๐ ๐ถ๐ป ๐๐๐ต๐ถ๐ผ๐ฝ๐ถ๐ฎ?
Let’s shape this journey together.
#Ethiopia #AI #DataGovernance #DigitalTransformation #Innovation #BusinessChallenges #DataStrategy
Comments
Post a Comment