IDC Survey: Impact of GenAI on an Organization’s Competitive Position or Business Models

A recent survey of technology buyers worldwide found that technology decision making, financial and operational systems and customer engagement, experience and support are the three business areas where generative artificial intelligence (GenAI) is most likely to impact their organization’s future competitive position or business model. The survey, conducted by International Data Corporation (IDC), also found notable differences in expectations across geographic regions.

While tech buyers in North America identified financial and operational systems as the business area most likely to be affected by GenAI, their counterparts in Western Europe indicated that IT and line of business (LOB) technology decision making will see the most impact. In Asia/Pacific, survey respondents felt GenAI would affect customer engagement, experience and support the most.

“What the survey results confirm is that the application of GenAI across business functions will be broad and its impact will span a wide range of competitive and business model areas,” Matt Acaro, research director for computer vision AI tools and technology at IDC, said. “Another thing the results highlight is that GenAI’s ability to process, understand and derive value from a wide range of data sources is its real superpower. It is exactly this capability that enables GenAI models and applications to be integrated and used within so many different business and customer processes and workflows. As organizations gain more experience with GenAI technologies, we expect them to use what they have learned to deploy GenAI in new areas.”

In addition to the three business areas identified as most likely to be impacted by GenAI, the survey included four other business areas for consideration: customer acquisition and sales; product design and development; data-driven decision making; and talent and staffing. Customer acquisition and sales and talent and staffing were the two business areas considered least likely to be impacted by GenAI.

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