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John Kostoulas is VP, Market Positioning and Strategy at <\/em>Dayforce<\/em><\/a>, and a global HR technology and transformation expert.<\/em><\/p>\n \u200bIn the first quarter of 2026, I spent a lot of time in CIO and IT leader events. Across conversations, there seemed to be a consensus: The first wave of enterprise AI adoption was fast, visible and, in many cases, deceptively easy. Organizations launched faster than ever, teams experimented and, above all, every executive conversation included AI strategy somewhere between cybersecurity and growth targets.<\/p>\n For CIOs and IT leaders, this created a rare moment of elevation. Their perception shifted from infrastructure operators to business transformation architects almost overnight.<\/p>\n Now comes the harder part: turning AI momentum into operational reality. The stakes are higher, and so is executive attention. What’s puzzling all of these IT leaders I met is that scaling AI isn’t really a technology problem anymore.<\/p>\n Organizations that get real value from AI are redesigning how people, workflows, decisions and systems operate together. Success in this new era requires a strong understanding of technology, but technology alone isn’t enough. The most effective organizations will orchestrate a seamless partnership between people and technology\u2014much like a well-executed tango\u2014in which trust and skills are developed together.<\/p>\n On AI skills development, we saw workers’ positive intentions in the Dayforce Pulse of Talent research<\/a>: 63% of respondents said it’s\u202fsomewhat or\u202fvery important for them. They know this development is vital for their careers, but the same research found that 84% of surveyed employees and 64% of surveyed managers\u202freported not receiving any AI training on the job in the past year. Only 17% of surveyed organizations currently offer training programs to people whose jobs are\u202fimpacted\u202fby AI.\u200b<\/strong><\/em><\/p>\n Trust is even more fragile. Almost two-thirds of responding workers (58%) said AI presents ethical challenges at work. McKinsey, in its 2026 “AI Trust Maturity Survey,<\/a>” reported that responsible AI maturity continues to improve, yet strategy, governance and agentic AI controls lag behind, with only about a third of organizations reaching a maturity level of three or higher (in a 0-4 scale) in these dimensions.<\/p>\n In practice, this means employees don’t trust AI outputs, and managers don’t know where it should augment work versus replace steps. Skills data is outdated, workflows remain fragmented across disconnected systems, governance becomes reactive and measurement becomes fuzzy. <\/p>\n This leads to organizations not being ready to operationalize the change AI brings. Trying to scale AI on top of fragmented people and work architecture is a recipe for failure. Instead, there’s a need to pay closer attention to the technology systems supporting the interplay between people and work. \u200b\u200b<\/p>\n<\/section>\n For years, people systems\u2014also known as human capital management (HCM)\u2014were viewed primarily as administrative infrastructure for payroll, workforce management, compliance, recruiting and HR operations. Important? Absolutely. Strategic? Sometimes.<\/p>\n The main challenge has been outcomes orientation. Instead of focusing on specific business key bets and aligning teams and individuals toward their execution, many organizations created functional silos of objectives, and technology fragmentation followed. As a result, people systems have mostly been HR’s responsibility.<\/p>\n AI underlines the importance of understanding the workforce. In my role in a HCM technology provider, I hear enterprise leaders needing more precision in understanding the following as key levers for a successful partnership between humans and AI:<\/p>\n \u2022 What skills exist across the workforce<\/p>\n \u2022 Where capability gaps are emerging<\/p>\n \u2022 Which roles are evolving fastest<\/p>\n \u2022 How work patterns are changing<\/p>\n \u2022 Where employee sentiment is shifting<\/p>\n \u2022 How scheduling, productivity, compliance and experience intersect<\/p>\n In short, people systems need to be seen as a platform, which increasingly becomes the scaling layer between humans and AI.<\/p>\n<\/section>\n After the first phase of AI adoption, the CIO and IT leader roles are evolving again to become co-owners of organizational transformation. They will build environments where people and AI can operate together with greater confidence, adaptability and alignment. That means CIOs and IT leaders increasingly need to partner with HR leaders, operations leaders and business executives to answer questions related to people and work. <\/p>\n Organizations that thrive with AI adoption will connect it to their people and processes at scale to offload friction and make work more coherent. This is where people platforms can play an important role.<\/p>\n Forbes Technology Council<\/u><\/a> is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?<\/u><\/em><\/a><\/p>\nIt’s About The People <\/h2>\n
The AI Scaling Layer <\/h2>\n
\u200bCIOs Co-Owning AI Workforce Readiness <\/h2>\n
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