- How to Begin Healthcare Artificial Intelligence Deployment
- Vendor Development Aids Healthcare Artificial Intelligence
The AI market will see the most growth in the software segment covering nearly 40 percent of all AI spending, according to IDC. This area includes conversational AI applications such as chatbots and personal assistants, and deep learning and machine learning applications.
Server and storage hardware are predicted to be the rea wit the second most growth at the beginning of the forecast period but will taper off in favor of related IT business services, like remote hosting and cloud storage.
The biggest use of AI powered automation will be in automated threat intelligence and prevention and automated preventive maintenance.
"Worldwide cognitive/artificial intelligence spending has moved beyond the early adopters to mainstream industry-wide use case implementation," said Marianne Daquila, research manager Customer Insights & Analysis at IDC. "Early adopters in banking, retail and manufacturing have successfully leveraged cognitive/AI systems as part of their digital transformation strategies.”
“These strategies have helped companies personalize their relationship with customers, thwart fraudulent losses, and keep factories running,” she continued. “Increasingly, we are seeing more local governments keeping people safe with cognitive/AI systems. There is no doubt that the predicted double-digit year-over-year growth will be driven by even more decision makers, across all industries, who do not want to be left behind."
While healthcare has many uses for AI in IT infrastructure as well as patient facing applications, adoption of AI in the medical field is behind other industries. Healthcare has traditionally lagged behind other industries with technology adoption. Similar to widespread cloud adoption, AI is a different approach to interacting with data and many organizations don’t want to take the risk to try out a new technology when the technology they are using still works.
Despite this initial hesitation in adoption, healthcare is expected to make significant investments in AI over the next several years, says IDC. However healthcare organizations need to be prepared to integrate AI into their existing infrastructure which can be a challenge.
A Tractica report released earlier this year, healthcare organizations found it difficult to integrate AI into their operational processes.
“Enabling AI at the enterprise scale is not a plug-and-play proposition,” Tractica Principal Analyst Keith Kirkpatrick said in a statement. “Significant time, resources, and capital must be deployed, and in most cases, internal company teams are not experienced enough with AI, nor do they have the cutting-edge data science skills to adequately embark upon a truly transformational AI implementation.”
Entities need to decide how they’re going to handle the infrastructure changes needed to process and store data. Organizations must also find the staff needed to manage and monitor the AI solution.
AI is still a young technology when it comes to enterprise IT infrastructure implementation, but it is expected grow significantly worldwide over the next several years.
As healthcare organizations look to implement an AI solution in the near future, ensuring the organization’s health IT infrastructure can support it is key to deploying a successful AI analytics solution.
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