Why AI projects Fail

Why do 85% of AI projects fail? The importance of strategic AI planning

unrealistic, inflated, and inaccurate expectations.

Companies often have an overly optimistic view of what AI can achieve in a short timeframe, leading to disappointment and project failure.

Accurate and relevant data labeling is crucial for training effective AI models, and any missteps can derail the entire project.

inappropriate labeling of data for training AI components.

Insufficient support of an organization's business leaders

This results in the abandonment of AI projects despite their great potential. A related struggle is change management since AI is not just about using an AI system but also about redesigning the process where the AI sits.

If stakeholders don’t trust the AI’s outputs, they are less likely to integrate and utilize the AI solutions, leading to underutilization and failure.

Low confidence in the AI model

the lack of skilled resources

Given the high demand for AI and data science expertise, many organizations struggle to recruit and retain the necessary talent to advance their projects.

AI models require vast amounts of high-quality data to function effectively, and insufficient data can severely limit a project’s success.

The lack of quality and quantity of data

The ever-growing diversity of data types and formats

AI systems must be able to process and integrate various data sources seamlessly, which is often a complex and resource-intensive task.

AI projects often require advanced infrastructure and technologies that many organizations may not have readily available, leading to delays and additional costs.

Underlying technology challenges

misalignment of business goals with real-world data

AI models must be designed to solve real business problems, and any disconnect between business objectives and the AI’s capabilities can result in ineffective solutions.

Forward-thinking strategies are essential, but they must be grounded in realistic assessments of AI’s current capabilities and limitations to avoid unattainable goal-setting.

inappropriate futuristic planning

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Indrek JürgensonCIO, Cleveron