Kyndryl Holdings Inc.
02/10/2025 | Press release | Distributed by Public on 02/10/2025 08:04
Closing the readiness gap: How businesses can thrive in the AI era
<_p3d_22_22_>Businesses are investing heavily in artificial intelligence (AI), but only 42% are seeing a positive return on investment. The newly released Kyndryl AI Readiness Report - a supplement to the Kyndryl Readiness Report - explains why.\r\n
Here, Kyndryl experts Michael Bradshaw, Victoria Pelletier, Kim Basile and Cory Musselman detail how senior leaders must unite in service to a shared strategy for their companies to benefit the most from their AI investments.
\r\n \r\n"}}" id="text-faee4a4412" class="cmp-text cmp-text-v2 cmp-text__article-text newsroom-tpl">Businesses are investing heavily in artificial intelligence (AI), but only 42% are seeing a positive return on investment. The newly released Kyndryl AI Readiness Report - a supplement to the Kyndryl Readiness Report - explains why.
Here, Kyndryl experts Michael Bradshaw, Victoria Pelletier, Kim Basile and Cory Musselman detail how senior leaders must unite in service to a shared strategy for their companies to benefit the most from their AI investments.
<_p3d_22_22_> \r\n
How can businesses close the readiness gap and implement AI successfully?
\r\nBradshaw: Closing the readiness gap starts with identifying use cases where AI can help organizations achieve their business goals. As enterprises evaluate their AI options, they must build a foundation of strong operational security, place people at the center of AI design to unlock new value and establish enterprise-wide trust in AI generally. At each step, business and technology leaders must play critical roles in driving the change that will help AI deliver on its transformative potential. They also should work with trusted partners who can help turn technology advances into competitive advantages.
\r\n \r\n"}}" id="text-18fbdd1322" class="cmp-text cmp-text-v2 cmp-text__article-text newsroom-tpl">How can businesses close the readiness gap and implement AI successfully?
Bradshaw: Closing the readiness gap starts with identifying use cases where AI can help organizations achieve their business goals. As enterprises evaluate their AI options, they must build a foundation of strong operational security, place people at the center of AI design to unlock new value and establish enterprise-wide trust in AI generally. At each step, business and technology leaders must play critical roles in driving the change that will help AI deliver on its transformative potential. They also should work with trusted partners who can help turn technology advances into competitive advantages.
<_p3d_22_22_>More from Michael Bradshaw\r\n
How businesses can start to close the AI readiness gap ↗
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More from Michael Bradshaw
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What role does company culture play in the successful implementation of AI?
\r\nPelletier: Successful implementation and adoption of any new technology depends more on how deeply it considers and integrates with human systems than on the technology itself. At its core, AI readiness is a behavioral transformation, and its successful implementation requires enterprises to embrace human-centered design principles to navigate this shift. That means understanding the people interacting with the system and building solutions that address their needs holistically while accounting for the inevitable exceptions to process or workflow standards.
\r\nBy embedding human-centered design into every stage of AI implementation - which is both operationally effective and emotionally resonant - enterprises can help ensure their AI initiatives deliver meaningful long-term outcomes.
\r\n \r\n"}}" id="text-c6d7da271a" class="cmp-text cmp-text-v2 cmp-text__article-text newsroom-tpl">What role does company culture play in the successful implementation of AI?
Pelletier: Successful implementation and adoption of any new technology depends more on how deeply it considers and integrates with human systems than on the technology itself. At its core, AI readiness is a behavioral transformation, and its successful implementation requires enterprises to embrace human-centered design principles to navigate this shift. That means understanding the people interacting with the system and building solutions that address their needs holistically while accounting for the inevitable exceptions to process or workflow standards.
By embedding human-centered design into every stage of AI implementation - which is both operationally effective and emotionally resonant - enterprises can help ensure their AI initiatives deliver meaningful long-term outcomes.
<_p3d_22_22_>More from Victoria Pelletier\r\n
AI's real challenge? Human behavior ↗
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More from Victoria Pelletier
<_p3d_22_22_> \r\n
How can organizations address the common barriers to AI adoption?
\r\nBradshaw: Common barriers to AI adoption include concerns over data privacy, data security and emerging regulatory requirements throughout the global digital economy. There's also uncertainty about value as leaders define short- and long-term success. Technical debt, insufficient data foundations and acute talent shortages also limit enterprises' ability to fully integrate AI across their operations.
\r\nSimply investing in AI doesn't guarantee readiness to deploy it at scale, manage emerging risks or extract long-term value. As enterprises look to the future, closing the readiness gap will require leaders who champion change. The results will depend as much on people as on technology.
\r\n \r\n"}}" id="text-98c1bc4194" class="cmp-text cmp-text-v2 cmp-text__article-text newsroom-tpl">How can organizations address the common barriers to AI adoption?
Bradshaw: Common barriers to AI adoption include concerns over data privacy, data security and emerging regulatory requirements throughout the global digital economy. There's also uncertainty about value as leaders define short- and long-term success. Technical debt, insufficient data foundations and acute talent shortages also limit enterprises' ability to fully integrate AI across their operations.
Simply investing in AI doesn't guarantee readiness to deploy it at scale, manage emerging risks or extract long-term value. As enterprises look to the future, closing the readiness gap will require leaders who champion change. The results will depend as much on people as on technology.