3 Reasons Why Artificial Intelligence Projects Fail

3 Reasons Why Artificial Intelligence Projects Fail

By knowing the potential pitfalls, businesses can be better positioned to make smart decisions leading to successful artificial intelligence deployment. Here are 3 Reasons Why Artificial Intelligence Projects Fail

Businesses will be better positioned to make smart decisions that lead to a successful AI deployment if they understand the potential pitfalls.

Businesses have been challenged by unimaginable forces in 2020 that have precipitated substantial disruption to the traditional business paradigms. Remote work became standard, not optional, as government-mandated stay-at-home orders caused a physically separated employee base, leading to a radical shift in how they performed their tasks. With this widespread disruption to the workforce and the impact upon productivity and customer service, large and medium-sized businesses have invested in solutions like chatbots, RPA, and IVRs for quick fixes. Some turned to artificial intelligence (AI) in a bid for a quick recovery, taking on conversational, analytical, and other forms of artificial intelligence at breakneck speed. Our own research shows that 88% of businesses adopted or scaled AI in order to regain their edge and stay ahead of the curve. The hopes are high, and the need has never been greater.

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