... operational decision making of supply chain and business unit leaders. Draft the risk appetite statement. Failure to provide guidance on how to actin uncertain situations often results in supply chain strategy decisions that fall outside the range of acceptable risk. Communicate the supply chain risk appetite. ...
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... Discover the top innovation trendsin midsize enterprises (MSEs) based on submissions to the 2025 Gartner Eye on Innovation Awards for Midsize Enterprises. MSE CIOs can use these insights as inspiration for their current and future initiatives. Gartner Research ...
... Mary Mesaglio, Frank Buytendijk and Helen Poitevin. 5:57 Top Strategic Technology Trends Global Chief of Research Chris Howard walks through the Gartner 2024 Top Strategic Technology Trends live at the Gartner IT Symposium/Xpo™ conference. 30:39 AI in Finance: The Next Industrial Revolution? Analysts Alex ...
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Analyst(s): Christine Lee | Jeremy D'Hoinne | Pete Shoard
... AI champions outpace other users in productivity but must be intentionally created and developed. Discover what defines this high-performing persona, how they differ from the broader workforce, and how executive leaders can implement strategies to develop and retain top AI user talent. Insights at a Glance ...
Analyst(s): Julia McDowell | Swagatam Basu | Diana Sanchez
... Currently, supply chain buyers persist in investing in AI technologies, even as ROI remains unclear, but that will not continue. High-tech executives need to address the drivers behind ongoing spend and the risks of unverified outcomes to build their customers’ confidence in achieving the desired ROI. Insights ...
... the need to automate complex workflows, reduce reliance on specialized skills and enable more predictive IT operations — outcomes that directly align with CIO priorities. What are the top challenges to AI for I&O? The top challenges to AI adoption in I&O are lack of budget, difficulty integrating AI with ...
... reaching limits of scalability and performance, requiring product leaders to evaluate new architectures such as neuromorphic computing, a key component in the AI race. Early use cases where neuromorphic computing can be applied include event detection, pattern recognition and small dataset training. Overview ...