MIT SMR Connections | Content Commissioned by AWS and NVIDIA

Implementing AI: From Exploration to Execution

The content on this page was commissioned by our sponsor, Amazon Web Services (AWS) and NVIDIA. The MIT SMR editorial staff was not involved in the selection, writing, or editing of the content on this page.

Artificial intelligence — in particular, machine learning — is widely recognized as a transformative set of technologies that will fuel competitive advantage, innovation, and growth across a range of industries. How are leaders in AI adoption identifying their most promising use cases and choosing the most appropriate technology infrastructure? How are they confronting implementation challenges?

Interest and investment in artificial intelligence may be higher now than at any time since the field emerged in the mid-1950s. Research is thriving in both industry and academic settings, and applications are proliferating across market sectors. AI-fueled innovations can be found in a range of areas, such as virtual assistants, advanced analytics, smart devices, robots, and autonomous vehicles.

AI is also entering the business mainstream, and the mandate to formulate strategies to apply AI — and do so ahead of competitors — is high on the C-suite and board agenda. With cloud services offering on-demand access to advanced computing infrastructure and managed AI services, it’s increasingly easy for companies of all sizes to experiment and innovate.

To stay in the vanguard, C-suite executives must not only understand their own business domain, but also educate themselves on AI capabilities. Our new report aims to help, by giving leaders considering their own AI strategies an updated look at recommended approaches to AI in the enterprise and lessons learned from three early adopter organizations.

Insight into technology choices, developing use cases, and scaling adoption are shared by these AI leaders in financial services, e-commerce, and technology services:

  • Liberty Mutual Insurance — New chatbot software integrated into productivity software is making it easier for employees to get answers to questions.
  • Zalando — Europe’s largest fashion retailer is on a mission to democratize machine learning across the company.
  • Samsung SDS — As it develops AI applications for its professional services customers, the company is using that work to continually upgrade its Brightics platform.

Read the full report for expert perspectives on the issues that enterprise leaders must work through as they develop strategies for applying cognitive technologies in their organizations.