Today’s artificial intelligenceArtificial Intelligence knows many different definitions, but in general it can be defined as a machine completing complex tasks intelligently, meaning that it mirrors human intelligence and evolves with time. (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.

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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 analyticsData analysis is simply put the study of data in order to take better informed decisions. All business decisions should be made with the best information available, data analysis tries to provide this information through different algorithms and statistical techniques. 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 dataBig Data describes data collections so big that humans are not capable of sifting through all of it in a timely manner. However, with the help of algorithms it is usually possible to find patterns within the data so far hidden to human analyzers.  solutions with machine learning (MLSimilar to humans, machines learn through experience, e.g. seeing data. This process of presenting data to an algorithm and seeing improvement in the performance/accuracy is called machine learning. ) 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.  […]

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