The concept of AI (which attempts to understand, design, and model intelligent systems), was invented by Stanford’s John McCarthy back in 1958. Yet, across the seven decades, the adoption of AI has been steady, yet sedate. The ever-evolving research in the field of AI, since the time of its inception, has seen a significant change in how intelligent systems are being designed in the present day.
Early adopters of AI technologies have been rewarded for their perseverance and are way ahead in the game as compared to their counterparts. They are reaping benefits in the form of increased revenues and expanded market shares, and they have carved out a niche for themselves with their par excellence products. The development of newer, better AI technologies has only motivated organizations further to embrace AI and reform their business strategies.
Although more businesses, big or small, have started implementing AI in their products, it’s noteworthy that the rate of acceptance across organizations varies remarkably. The variance in adoption can be attributed largely to the business challenges faced in employing AI effectively and how well organizations are equipped to overcome these challenges. Evidence suggest that despite AI success stories, which are becoming more prominent and visible, organizations are still facing challenges when it comes to the business implementation of these technologies.
A survey report by HBR of over 3000 global executives reveals that “Only 20% of the respondents use one or more AI technologies at scale or in a core part of the business.”
Enterprise data is growing rapidly in volume and variety, and it is posing bigger challenges. Data is often located across disparate sources and formats, which affects organizations’ ability to collect, store and integrate data. Overcoming these challenges is critical for paving the way for AI readiness and AI initiatives.
Are you waiting to transform your business with AI, but are unsure about the best approach? The white paper “Democratized Artificial Intelligence,” written by Ness’s Chief Solutions Officer, Rajeev Sharma, shares best practices for organizations to develop a roadmap for building AI within existing products and platforms. Read more at http://bit.ly/2eN7aZW