Artificial intelligence can offer competitive advantages, but it’s not easy to drive success without understanding how to overcome the challenges.
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Artificial intelligence will change the way we live, work and play. In the process, it will challenge existing businesses, create new ones and fundamentally shift the economy. There’s no shortage of reports on enterprises investing in , but there are relatively few details about lessons learned and what can be done to improve the design of those plans. Here are seven ways to overcome inherent technical challenges, organizational barriers and a lack of precedent for pilot programs:
1. Pick a high-impact business problem
Transformative initiatives with significant organizational and cultural barriers require sponsorship from the highest leadership levels as they often take longer and are more complex. Start by addressing a high-impact problem that will not just get one-time executive sponsorship but ongoing executive engagement. This will also prevent the initiative from getting cut when the next budget crunch hits.
2. Understand feasible use cases
While headlines about the possibilities and consequences of abound, the reality is that current techniques still have several limitations. Consider an early feasibility assessment. Does the organization currently generate, store and analyze the types of data required by the machine-learning algorithm? Is the underlying process that will be improved already software-enabled? If the answer to both questions is no, chances are that even if offers potential benefits, the time and investment may not be worth the risk.
3. Know your use case and your data
Not all
4. Plan for IT infrastructure requirements
The IT infrastructure (network connectivity and computational power) required for
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