The promise of AI is everywhere, but the reality for most organizations tells a different story. Studies show that between 70-85% of AI projects fail to deliver meaningful business value. After working with dozens of organizations across East Africa, we have identified three consistent root causes.
The first is starting with technology instead of problems. Too many teams choose an AI tool and then look for something to do with it. Successful adoption starts with a clear business problem, a measurable outcome, and only then an evaluation of which AI approach fits best.
The second is underestimating the data foundation. AI systems are only as good as the data they consume. Organizations that skip the work of cleaning, structuring, and governing their data end up with impressive demos that fall apart in production.
The third is treating AI as a one-time project rather than an ongoing capability. AI adoption is not a deployment; it is a transformation. It requires new skills, new processes, and a culture that embraces experimentation and iteration.
At Craqt, we address these challenges through our Process Embedding methodology. We start by mapping your existing workflows, identifying the highest-impact opportunities, and building a phased roadmap that delivers quick wins while building toward long-term transformation.
