Today’s artificial intelligence (AI) technology movement is transformational and will require new leadership skills that are embracing of change. However, the key driver will not be technology along, but assuring the maturity of the right capabilities.
copyright by www.cio.com
Companies committed to adopting AI will need to develop corporate strategies and governance policies that will require in-depth knowledge of the capabilities to assure expectations are in alignment with the promised value to their business partners.
Managing the challenge
The expectations for AI are astronomical with irrefutable results. You don’t have to look any further than your wrist to ask Siri what are the best Thai restaurants within a five-mile radius of my current location.
Technology leaders today are under more pressure to deliver business value that is enhanced with AI solutions than ever before. The culture change required to implement AI will be daunting. It will be challenging to acquire AI talent and address competing priorities for AI investment. The insistence that AI will eliminate jobs may be true at some future date. However, for the foreseeable future, companies will require vast number of people in both business and data analytics that can bridge business areas that are reliant on each other.
The challenge for technology leaders is to understand what are the capabilities of AI and how to manage the expectations for delivering value in their information management strategy. Too much emphases have been placed on developing big data solutions with machine learning (ML) capabilities.
What defines AI
The problem with this emphases on machine learning is that there is an underlying assumption that machine learning is synonymous with artificial intelligence. This could be no farther from the truth, depending on your definition of AI. Yes, machine learning is the foundation for AI, and a lot of advanced features have been developed with machine learning. However, the reality is that there is only so much you can accomplish with machine learning capabilities. […]
read more – copyright by www.cio.com
Today’s artificial intelligence (AI) technology movement is transformational and will require new leadership skills that are embracing of change. However, the key driver will not be technology along, but assuring the maturity of the right capabilities.
copyright by www.cio.com
Managing the challenge
The expectations for AI are astronomical with irrefutable results. You don’t have to look any further than your wrist to ask Siri what are the best Thai restaurants within a five-mile radius of my current location.
Technology leaders today are under more pressure to deliver business value that is enhanced with AI solutions than ever before. The culture change required to implement AI will be daunting. It will be challenging to acquire AI talent and address competing priorities for AI investment. The insistence that AI will eliminate jobs may be true at some future date. However, for the foreseeable future, companies will require vast number of people in both business and data analytics that can bridge business areas that are reliant on each other.
The challenge for technology leaders is to understand what are the capabilities of AI and how to manage the expectations for delivering value in their information management strategy. Too much emphases have been placed on developing big data solutions with machine learning (ML) capabilities.
What defines AI
The problem with this emphases on machine learning is that there is an underlying assumption that machine learning is synonymous with artificial intelligence. This could be no farther from the truth, depending on your definition of AI. Yes, machine learning is the foundation for AI, and a lot of advanced features have been developed with machine learning. However, the reality is that there is only so much you can accomplish with machine learning capabilities. […]
read more – copyright by www.cio.com
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