AI tools can help leaders make informed decisions, especially under pressure by offering real-time insights and predictive analysis.
Copyright: hbr.org – “How AI Can Help Leaders Make Better Decisions Under Pressure”
More and more businesses are turning to AI-powered technologies to help close the data-insight gap and improve their decision-making capabilities in time-critical, high-pressure situations. These technologies encompass a wide range of tools, including virtual assistants, virtual and augmented reality, process discovery, task mining, and an array of data analytics and business intelligence platforms. Recently, there has been tremendous interest in generative AI or large-language models, a whole class of algorithms that are able to ingest vast tracts of data — text, numbers, software code, images, videos, formulas, and so on — understand their probabilistic structure, and create summaries, answers, simulations, and alternative scenarios based on these data. This article addresses three critical questions faced by decision-makers in using these technologies: 1) In what contexts are AI decision-making technologies likely to be beneficial? 2) What are some of the challenges and risks of using these technologies? and 3) How can business leaders effectively benefit from these technologies while mitigating the risks?
Business leaders and managers face increasing pressure to make the right decisions in the workplace. According to research by Oracle and Seth Stephens-Davidowitz, 85% of business leaders have experienced decision stress, and three-quarters have seen the daily volume of decisions they need to make increase tenfold over the last three years.
Poor decision making is estimated to cost firms on average at least 3% of profits, which for a $5 billion company amounts to a loss of around $150 million each year. The costs of poor decision making are not just financial, however — a delayed shipment to an important supplier, a failure in IT systems, or a single poorly managed interaction with an unhappy customer on social media can all quickly spiral out of control and inflict significant reputational and regulatory costs on firms.
Against this backdrop, more and more businesses are turning to AI-powered technologies to help close the data-insight gap and improve their decision-making capabilities in time-critical, high-pressure situations. These technologies encompass a wide range of tools, including virtual assistants, virtual and augmented reality, tools for process discovery and task mining, and an array of data analytics and business intelligence platforms. Recently, there has been tremendous interest in generative AI or large language models (LLMs), a whole class of algorithms that are able to ingest vast tracts of data — text, numbers, software code, images, videos, formulas, and so on — understand their probabilistic structure, and create summaries, answers, simulations, and alternative scenarios based on these data. Well-known generative AI models include OpenAI’s ChatGPT, Google’s Bard, Meta’s Llama 2, and Anthropic, but there are many more.[…]
Read more: www.hbr.org
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AI tools can help leaders make informed decisions, especially under pressure by offering real-time insights and predictive analysis.
Copyright: hbr.org – “How AI Can Help Leaders Make Better Decisions Under Pressure”
Business leaders and managers face increasing pressure to make the right decisions in the workplace. According to research by Oracle and Seth Stephens-Davidowitz, 85% of business leaders have experienced decision stress, and three-quarters have seen the daily volume of decisions they need to make increase tenfold over the last three years.
Poor decision making is estimated to cost firms on average at least 3% of profits, which for a $5 billion company amounts to a loss of around $150 million each year. The costs of poor decision making are not just financial, however — a delayed shipment to an important supplier, a failure in IT systems, or a single poorly managed interaction with an unhappy customer on social media can all quickly spiral out of control and inflict significant reputational and regulatory costs on firms.
Against this backdrop, more and more businesses are turning to AI-powered technologies to help close the data-insight gap and improve their decision-making capabilities in time-critical, high-pressure situations. These technologies encompass a wide range of tools, including virtual assistants, virtual and augmented reality, tools for process discovery and task mining, and an array of data analytics and business intelligence platforms. Recently, there has been tremendous interest in generative AI or large language models (LLMs), a whole class of algorithms that are able to ingest vast tracts of data — text, numbers, software code, images, videos, formulas, and so on — understand their probabilistic structure, and create summaries, answers, simulations, and alternative scenarios based on these data. Well-known generative AI models include OpenAI’s ChatGPT, Google’s Bard, Meta’s Llama 2, and Anthropic, but there are many more.[…]
Read more: www.hbr.org
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
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