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5 steps to move AI beyond buzzwords to deliver true transformative impact

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The headlines read “Artificial Intelligence (AI) will completely transform your business.” But does the hype match the reality? We have been seeing these exclamations for two decades, but where are the examples? Where are the success stories? Is AI really a game changer, and does it actually apply to my business?





Every ten years it seems there is a new technology that is going to change the world, but all too often only leads to disappointment when adopting it becomes too challenging. For several decades this has been the story behind Artificial Intelligence and Machine Learning.





However, we have now reached a tipping point with AI where the compute capacity, ubiquitous connectivity, and wealth of data can match the moment and assist business leaders to create unique competitive advantages by better serving customers, improving processes, enhancing employee experience, or reducing costs. As Andy Jassy, CEO of Amazon, said, “Most applications, in the fullness of time, will be infused in some way with machine learning and artificial intelligence.”





As I advise in my presentation “, a complimentary, interactive guide for business leaders and AI practitioners to conceptualize and build their applications.













AWS | AI Use Case ExplorerWith over 100 use cases and sub use cases and 400 customer success stories, this tool can help you quickly identify the right use case to get started based on your industry, function, and desired business outcome. Once you have identified your use cases, you can read about success stories from around the world and kickstart your deployment, from proof-of-concept to full production, by following an expert-curated action plan provided for your specific use case.





Do not boil the ocean … we tried that … it did not work





As an industry, we have learned hard lessons from trying to deploy monolithic data warehouses, business intelligence implementations, and analytics solutions by gathering, cleaning, and preparing tremendous swaths of data from across the entire enterprise. This delayed value, increased cost, raised complexity, and ultimately failed to deliver. Instead, focus on gathering the data specific to the use case you are implementing, and drive quickly through proof-of-concept to production and value. Then move on to the next use case and do the same thing again, expanding your data assets as needed.





Technology is not the objective, it is the enabler





True value does not come from just using a new technology, but rather from using new technology to reimagine existing processes. As you look to implement your AI project go beyond just creating an AI-enabled twin of your existing process, and instead reimagine the process using the new capabilities of AI.





As AI transforms the way we live and work, from optimizing business processes to personalizing content for consumers, I am excited about all of the innovative and impactful AI applications that can assist businesses as well as individuals in the coming years. The possibilities are endless! I invite you to check out the AI Use Case Explorer site and explore your organization’s unique path to AI success.





ABOUT THE AUTHOR:





Tom Godden is an Enterprise Strategist and Evangelist at Amazon Web Services (AWS). Prior to AWS, Tom was the Chief Information Officer for Foundation Medicine where he helped build the world’s leading, FDA regulated, cancer genomics diagnostic, research, and patient outcomes platform to improve outcomes and inform next-generation precision medicine. Previously, Tom held multiple senior technology leadership roles at Wolters Kluwer in Alphen aan den Rijn Netherlands and has over 17 years in the healthcare and life sciences industry. Tom has a Bachelor’s degree from Arizona State University.


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