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Building Modern AI Apps & Driving AI Adoption with Less Time and Effort

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Studies by market-research institutes estimate that the contribution of AI to the economy will be as high as $15.7tr within the next decade (source: PwC – Sizing the Prize). However, recent surveys reveal that businesses still fail to productionise more than 85% of AI projects, which is heavily preventing or limiting their ROI. Among other factors, the inability to consume AI models by the business’s end-users is identified as a significant hurdle to adopting AI and transforming the business.

This doesn’t seem a surprise as developing a modern AI application that can consume predictive models is one of the most time-consuming tasks in the data science lifecycle. It takes software engineers, data scientists and others’ collective effort many hours to develop a solid AI product.

As a result, many data science models never reach business users or get into production.

Does this sound familiar? Watch this session to learn how H2O Wave enables organisations to develop AI applications in a short amount of time and with little effort, therefore contributing to AI adoption across the company.


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