By now, most digital and tech leaders have heard some version of the same refrain, that AI adoption is 20% about the technology and 80% about the people. But even when leaders acknowledge the .
Closing the IT and business chasm
Remoreras’s views are rooted in a long-standing conviction about the role of technology in the enterprise. Over the years, he says he became almost maniacal about solving , it changes decision-making, work design, customer experience, risk, governance, and the way employees understand their own roles. If technology and business leaders approach AI from opposite sides of the table, adoption will be slower, riskier, and less likely to produce meaningful value.
Trust as an operating system
For Remoreras, trust isn’t a vague aspiration but a core operating infrastructure, and relationships are the primary enabler of that trust. That framing matters because AI introduces uncertainty at multiple levels. Employees may wonder how their work will change, leaders may struggle to separate hype from real opportunity, and functions may disagree about ownership, risk, as a way to describe the leadership capabilities organizations will need in an AI-enabled world.
Purpose comes first because and moves the discussion beyond tools, training, and process redesign without diminishing the importance of any of them. Skills, governance, and use case prioritization all matter. But none will be enough if people don’t trust the leaders setting direction, the teams building solutions, or the organization’s intent for how AI will be used.
That’s why Remoreras’s message is particularly relevant for CIOs. Tech leaders are often accountable for the platforms and capabilities that make AI possible, but they’re also uniquely positioned to shape the relationships that make AI scalable. They can help the organization move from IT as service provider to technology as co-leader, build the connective tissue between strategy, execution, risk, and adoption, and create the conditions where business and tech leaders share ownership for outcomes. This is the leadership work AI requires, says Remoreras.
As machines become more capable, the leadership capabilities that can’t be automated become more valuable. The ability to listen, align, challenge, empathize, build trust, and lead through ambiguity becomes a strategic advantage. The future of AI won’t be determined only by which organizations choose the right platforms or move the fastest, but it’ll also be shaped by which organizations can create enough trust for people to move together.
That’s why relationships may be the hidden infrastructure of AI transformation. Not because they replace technology, but because they make transformation possible.
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