Why data infrastructure will impact AI initiatives
As more artificial intelligence applications emerge, healthcare organizations’ databases need to evolve to support them.
In 2017, artificial intelligence and digital transformation vaulted to the forefront of organizations’ priorities, and these technologies will continue to drive new initiatives in 2018.
Recent research suggests that the AI market will surpass $100 billion by 2025, and 89 percent of organizations say the industry is being disrupted by digital technology. For organizations toward succeed today, digital strategies must underlie the move to innovation and improve customer experience.
And to support these efforts, it’s vital for organizations to build out the necessary data infrastructure.
Today, AI is more of a trendy buzzword than a practical reality. Difficult to execute, AI is only as good as the underlying data, and data integrity still varies from enterprise to enterprise. However, the early stages of machine learning applications are emerging, and in the years ahead we’ll see more organizations use this advanced technology, particularly in tandem with the Internet of Things, and it will empower a more meaningful user experiences.
Throughout this transformation, the database will play an instrumental role by accommodating rapidly changing data at scale, while keeping big data sets reliable and secure, although true implementation of AI is still several years away.
Organizations are beginning to understand the link between customer engagement and digital transformation and, in turn, they’re recognizing that their current infrastructure will not help them achieve this transformation. As more organizations evolve their models by fundamentally rethinking their data—how it is managed, how it is moved, and how it is presented to the customer—they also will rethink how their data infrastructure can provide the agility they need to achieve their digital transformation goals.
The re-platforming of the organizational database infrastructure to modern platforms that enable fluidity of data movement and secure management from edge to cloud will accelerate at an unprecedented pace.
In the process, one-trick technology solutions that solve singular customer problems will begin to peel away, as the cost and complexity of integrating numerous point solutions that address niche issues will no longer be worth the headache. To maintain a lasting relationship with their customers, technology vendors will need to provide one platform that fills multiple customer requirements, and having an agile approach to technology will be the key differentiator.
As organizations seek to deploy AI implementations and undergo digital transformations, it’s advances in their data architecture that will make this possible. And if there’s one consistent truth across all industries, it’s that the organizations that best adapt to the ever-changing digital landscape will be the ones to succeed in 2018 and beyond.
Recent research suggests that the AI market will surpass $100 billion by 2025, and 89 percent of organizations say the industry is being disrupted by digital technology. For organizations toward succeed today, digital strategies must underlie the move to innovation and improve customer experience.
And to support these efforts, it’s vital for organizations to build out the necessary data infrastructure.
Today, AI is more of a trendy buzzword than a practical reality. Difficult to execute, AI is only as good as the underlying data, and data integrity still varies from enterprise to enterprise. However, the early stages of machine learning applications are emerging, and in the years ahead we’ll see more organizations use this advanced technology, particularly in tandem with the Internet of Things, and it will empower a more meaningful user experiences.Throughout this transformation, the database will play an instrumental role by accommodating rapidly changing data at scale, while keeping big data sets reliable and secure, although true implementation of AI is still several years away.
Organizations are beginning to understand the link between customer engagement and digital transformation and, in turn, they’re recognizing that their current infrastructure will not help them achieve this transformation. As more organizations evolve their models by fundamentally rethinking their data—how it is managed, how it is moved, and how it is presented to the customer—they also will rethink how their data infrastructure can provide the agility they need to achieve their digital transformation goals.
The re-platforming of the organizational database infrastructure to modern platforms that enable fluidity of data movement and secure management from edge to cloud will accelerate at an unprecedented pace.
In the process, one-trick technology solutions that solve singular customer problems will begin to peel away, as the cost and complexity of integrating numerous point solutions that address niche issues will no longer be worth the headache. To maintain a lasting relationship with their customers, technology vendors will need to provide one platform that fills multiple customer requirements, and having an agile approach to technology will be the key differentiator.
As organizations seek to deploy AI implementations and undergo digital transformations, it’s advances in their data architecture that will make this possible. And if there’s one consistent truth across all industries, it’s that the organizations that best adapt to the ever-changing digital landscape will be the ones to succeed in 2018 and beyond.
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