Why do AI projects fail-and how can they succeed?

The Root Causes of Failure for Artificial Intelligence Projects and How They Can Succeed.

A recent research report by the RAND was published last week and was top of my reading list.

The highlights:

⚡ AI projects have 2x the rate of failure for information technology projects that do not involve AI.

⚡ AI projects differ to other IT projects, in terms of project characteristics, such as costly labor and capital requirements and high algorithm complexity.

⚡The leading root cause of failure for AI projects? The business stakeholders often misunderstand — or miscommunicate — what problem needs to be solved using AI.

⚡Data is king. The other notable root cause of failure identified by interviewees was limitations in the quality and utility of data available to train the AI models.

A comment on the approach.

The authors interviewed 65 data scientists and engineers with at least five years of experience in building AI/ML models in industry or academia.

Two main ways in which the RAND research approach adds to the conversation / differs from other studies on the topic:

1. They talk to individuals building AI applications - not the business leaders of the organization.

Benefit? Bring in the perspective of those who understand the specifics of the technology.

Disadvantage? The study's focus on nonmanagerial engineers may skew results toward highlighting leadership failures rather than providing a balanced perspective.

2. They use semi-structured interviews with smaller sample - not structured surveys of large sample.

Benefit? Nuance and depth.

Disadvantage? Results may not be representative.

Recommendations

The researchers bring together recommendations for future success of AI projects. These range from stakeholder alignment, to data and infrastructure requirements.

The one that stood out for me:

“Choose enduring problems"

AI projects require time and patience to complete, so longer-term and consistent commitment are essential.

My conversations with clients indicate that they struggle to separate the hype around AI from it’s real-life implications on their business.

Using strategic foresight tools can help you to prioritise where AI is the best fit for your organization.

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Are you looking to understand how AI can create new opportunities and risks for your organization? Get in touch with me for an introductory call to see how I can help.