Why AI-as-a-Service gains traction in the healthcare C-suite

There is tremendous complexity involved in developing AI and machine learning solutions that meet a business’ actual needs. Developing the right algorithms requires data scientists who know what they are looking for and why, to cull useful information and predictions that deliver on the promise of AI. However, it is not feasible or cost-effective for every organization to arm itself with enough domain knowledge and data scientists to build solutions in-house. 
AI-as-a-Service is gaining momentum precisely because AI-based solutions can be economically used as a service by many companies for many purposes. Those companies that deliver AI-based solutions targeting specific needs understand vertical industries and build sophisticated models to find actionable information with remarkable efficiency. Thanks to the cloud, providers can deliver AI solutions as a service that can be accessed, refined and expanded in ways that were unfathomable in the past.
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 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 weeks.*
Health system C-suite favors AI-as-a-Service
Health system executives prefer a turnkey approach to deploy artificial intelligence. AI-as-a-Service vendors provide the expertise to identify the processes ready for automation, have the tools and skills to quickly develop, train and deploy AI solutions and continue to maintain the solution and allow adoption to changing data availabilities and changes in the processes over time.
AI-as-a-Service advantages perceived by the C-suite
· Actionable insights in value of available data and contribution to data strategy evolution,
· Higher value tasks for patient-oriented healthcare and IT resources,
· AI solutions that evolve and adapt with changing data availabilities,
· AI experts available, with specific AI knowledge in the healthcare domain,
· Upfront understanding of costs.

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