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The Emergence of AIaaS

SaaS and PaaS have become part of the everyday tech lexicon since emerging as delivery models, shifting how enterprises purchase and implement technology. A new “_” as a service model is aspiring to become just as widely adopted based on its potential to drive business outcomes with unmatched efficiency: artificial intelligence as a service (AIaaS).

The AIaaS Opportunity

According to recent research, AI-based software revenue is expected to climb from $9.5 billion in 2018 to $118.6 billion in 2025 as companies seek new insights into their respective businesses that can give them a competitive edge. Organizations recognize that their systems hold virtual treasure troves of data but don’t know what to do with it or how to harness it. They do understand, however, that machines can complete a level of analysis in seconds that teams of dedicated researchers couldn’t attain even over the course of weeks.

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Build vs. Buy: The Conundrum Facing the Insurance Industry as It Embraces AI

Artificial intelligence (AI) has been discussed everywhere over the last few years, and now it’s made its way into the commercial insurance industry. Organizations are using AI and machine learning for everything from streamlining operations to offering more personalized care and better customer service. There is an increasing sense of urgency about getting started on the AI journey. The question is how? Do they develop a custom solution in-house or purchase a third-party solution already on the market?

At first blush, the temptation to build can be strong — after all, you can design exactly what you want for your specific environment. But, in reality, it’s hard to accurately weigh the perceived benefits of a highly customized internal platform against the time and cost requirements compared to purchasing a tested, third-party solution. To help figure out the best course of action for your organization, I’d like to share some criteria that may guide you.