Enterprise AI is a category of enterprise software that harnesses advanced artificial intelligence techniques to drive digital transformation. Developing and deploying Enterprise AI at scale requires a new technology stack.

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Over the last four decades, the information technology industry has grown from about $120 billion globally in 1980 to more than $2 trillion. During this time, the IT industry has experienced the transition from mainframe computing to minicomputers, to personal computing, to internet computing, and to handheld computing. The software industry has transitioned from custom applications based on mainframe standards such as MVS, VSAM, and ISAM, to applications developed on a relational database foundation, to enterprise application software, to SaaS and mobile apps, and now to the AI-enabled enterprise. The internet and the iPhone changed everything. Each of these transitions represented a replacement market for its predecessor. Each delivered dramatic benefits in productivity.

Each offered organizations the opportunity to gain sustainable competitive advantage. Companies that failed to take advantage of each new generation of technology ceased to be competitive. Today it is unimaginable that a major global corporation would try to close its books without an enterprise resource planning system or run its business solely on mainframe computers.

The IT industry is now undergoing another major transition. A new generation of 21st century technologies – including elastic cloud computing, the internet of things, and artificial intelligence – is driving digital transformation across industry, commerce, and government globally. Digital transformation presents a number of unique requirements that create the need for an entirely new software technology stack. The requirements are daunting.

This paper defines the requirements of the new digital transformation software stack. It explains why the current approach to developing AI and IoT enterprise software – i.e., using structured programming to build applications by assembling and integrating various open source components and cloud services – is slow, costly, and ineffective.

Finally, this paper describes how the C3 AI™ Suite with its unique model-driven architecture fully addresses the requirements for the digital transformation software stack, providing a low-code/no-code AI and IoT platform that accelerates software development by a factor of 26 or more, reduces cost and risk, and delivers future-proof applications.