In January 2020, former U.S. AFRICOM commander General Stephen Townsend woke up to devastating news: the U.S. base in Manda Bay, Kenya, had been attacked by the al-Shabaab terrorist group. The attack left multiple aircraft destroyed, several personnel injured, and four Americans unaccounted for. By the end of the day, security was restored, but at a devastating cost: three Americans had died.
In the aftermath, an after-action review revealed that intelligence reports had hinted at a potential attack on airfields in Kenya, including Manda Bay. However, the reports were vague, fragmented, and not connected in time. The data was there, but the insights needed to act decisively were lost in the noise.
Bringing clarity to the chaos
In a recent talk with our valued advisor, General Townsend shared how advanced analytical tools could have helped analysts connect the dots in time to prevent the Manda Bay attack. Reports referenced a possible airfield attack in Kenya, another flagged Lamu County, and a third noted threats to United Nations aircraft. Individually, these reports seemed unremarkable. But together, they painted a clear picture: the U.S. base at Manda Bay was at risk.
How AI enables smarter, faster analysis
Primer’s AI is built to tackle the exact problem Townsend described: making sense of fragmented intelligence. Such capabilities allow analysts to:
- Aggregate and synthesize data: Automatically pull together related reports and highlight emerging patterns.
- Map locations visually: Display locations like Lamu County on a map, revealing that it has only two airfields: a commercial airport and the U.S. base. This insight would have narrowed down the threat location immediately.
- Cluster related insights: Group reports about Lamu County, airfields, and potential targets like UN aircraft to reveal a clearer threat picture.
- Chronologically plot events: Highlight the history of attacks in the region, which might have provided further context for assessing risk. While Manda Bay had seen no attacks in 16 years, other Kenyan locations had been targeted recently. Combining these factors could have prompted a more urgent re-evaluation of the threat level.
By surfacing these connections in real time, tools like Primer’s platform empower analysts to provide decision-makers with timely, precise, and actionable insights.
Why this matters
General Townsend recounted how, after the attack, he asked key questions that advanced tools could have answered in minutes: How many airfields are in Lamu County? Just two. Where are UN aircraft based? Nowhere nearby—indicating a possible misidentification of U.S. aircraft. Had these connections been made earlier, the attack might have been prevented.
AI doesn’t just make analysts faster—it makes them smarter, turning a flood of data into decisive action. In environments where every second counts, tools like these can mean the difference between reacting to a crisis and preventing one entirely.
