Is IT Ready for Change Because of the CIO, or Because of How It Is Set Up?

The question behind “future-ready”

Most advice on preparing IT for disruption starts with the CIO: be more agile, empower the team, invest in learning, lead with purpose. None of it is wrong. The question is whether it is where readiness comes from.

The pressure to get this right is real. In Gartner’s survey of 2,002 CIOs and technology executives, fielded in mid-2026, only 13% said their enterprise has realized significant or transformational value from AI so far [1]. Employers expect 39% of workers’ core skills to change by 2030 [2]. An IT organization that cannot change will feel both.

Which leaves the question this piece is about. When an IT organization adapts well, is that the CIO’s style, or the way the organization around the team is set up?

What the evidence credits leaders with

Leaders matter. Russell Reynolds’ 2025 survey of more than 1,000 executives found that three conditions (a change-ready culture, high-impact talent and clarity) account for 56% of the difference between stalled transformations and those that deliver lasting results. It states that “leadership behavior sets the foundation for change” [3]. Gallup finds that whether a direct manager actively champions AI was the strongest predictor of employee AI use, apart from technical integration [4].

But look at what leaders are credited with: setting conditions. Culture, talent, clarity, the example a manager sets.

McKinsey’s 2025 survey of operating model redesigns makes the same point from the other side. Redesigns that succeed change how work gets done, including decision rights, cross-team processes and technology, rather than only reporting lines, and they tie leadership incentives to the new model [5]. ZS puts it plainly: behavior is shaped by systems such as incentives, governance, workflows and social norms, and transformations stick only when leaders redesign those systems, not just the people within them [6].

Read together, the evidence does not say style is irrelevant. It says style reaches the team through what it puts in place.

Where readiness actually sits

Readiness for change is not a trait of the CIO, or of the team. It sits in six places at once (culture, talent, structure, process, metrics and technology) and in how each pulls on the others. Here is what recent evidence says about each, and where each tends to break.

Culture

Russell Reynolds names a change-ready culture as the strongest driver of transformation success [3]. Culture here is not a slogan. It is what people expect to happen when they try something new and it fails. A CIO can say “experiment”. The culture is what follows the first failed experiment.

Talent

With 39% of core skills expected to change by 2030, readiness depends on whether people can move into new work, not only learn about it. Out of every 100 workers, employers expect 29 to be upskilled in their current roles and 19 to be reskilled and redeployed within the organization [2]. Gartner’s vanguard CIOs are 2.4 times more likely to have plans to redesign roles for a human-agent workforce, yet only 4% of CIOs have such plans [1].

Structure

Structure decides how much attention each manager can give. Gallup links larger spans of control to lower manager engagement, and advises organizations flattening their structures to weigh the effect on managers and teams. Manager engagement fell from 31% in 2022 to 22% in 2025 [4]. If managers are the channel through which change reaches teams, a structure that overloads them narrows that channel, whatever the CIO’s style.

Process

McKinsey finds that successful redesigns rewire decision rights and cross-team processes [5]. Gartner’s vanguards are 2.3 times more likely to have guidelines for when a pilot should not move to production, yet only 31% of CIOs have them. They are 2.6 times more likely to have guidelines for abandoning low-value AI already in production, which only 17% have [1]. A team that cannot stop a pilot is not ready for the next one.

Metrics

Teams adapt toward what is measured. In Gartner’s 2025 survey of data and analytics leaders, only 22% of organizations had defined, tracked and communicated business impact metrics for most of their use cases [7]. Read another way: when a team is measured on delivery and uptime rather than outcomes, it can be ready for change and still be rewarded for not changing.

Technology

Technology sets what is possible. Organizations reporting successful AI initiatives invest up to four times more, as a share of revenue, in foundations such as data quality, governance, AI-ready people and change management than those with poor outcomes [8]. Two of those four foundations are about people and change, not technology.

How the facets hold each other in place

The facets do not act alone. As I read the evidence, a gap in one can cancel progress in the others. Upskilling without redesigned roles produces skills nobody uses. Empowerment without clear decision rights produces frustration. A stop rule without outcome metrics has nothing to stop on.

This is why style alone underdelivers. A CIO who empowers, inspires and models learning can still be pushing against a setup that rewards something else.

What this means

For CIOs

• Treat your style as an input, not the answer. Ask what each facet rewards, allows and blocks.
• Write the stop rules. Few CIOs have them, and the vanguards are far more likely to.
• Redesign roles alongside training, so new skills have somewhere to go.
• Protect manager capacity. Check spans of control before flattening.
• Change the scorecard before asking the team to change behavior.

For Transformation Leaders

• Assess readiness across all six facets, not through a leadership or culture survey alone.
• Find the facet that cancels the others, and start there.
• Tie leadership incentives to the new way of working, as successful redesigns do.

The question to leave with

Style still matters. It is how a CIO earns the standing to change the setup. But readiness lives in the setup.

So, for your organization: if the CIO changed tomorrow, would the IT team be more or less ready for change than it is today?

Sources

1. Gartner, “Gartner Survey Finds Only 13% of CIOs Say Their Enterprise Has Realized Significant or Transformational Value from AI”, 19 October 2026. https://www.gartner.com/en/newsroom/press-releases/2026-10-19-gartner-survey-finds-only-13-percent-of-cios-say-their-enterprise-has-realized-significant-or-transformational-value-from-ai
2. World Economic Forum, Future of Jobs Report 2025, “Skills outlook”, 7 January 2025. https://cn.weforum.org/publications/the-future-of-jobs-report-2025/in-full/3-skills-outlook/
3. Russell Reynolds Associates, “The Three Conditions That Matter Most for Transformation”, 18 May 2026. https://www.russellreynolds.com/en/insights/articles/the-three-conditions-that-matter-most-for-transformation
4. Gallup, “Global Employee Engagement Continues Decline”, 7 April 2026. https://www.gallup.com/workplace/708071/global-employee-engagement-continues-decline.aspx
5. McKinsey & Company, “The new rules for getting your operating model redesign right”, 25 June 2025. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/the-new-rules-for-getting-your-operating-model-redesign-right
6. ZS, “Your people are ready for change. Your operating model isn’t”, 11 August 2026. https://www.zs.com/insights/change-management-ai-transformation
7. Gartner, “Gartner Survey Finds One-Third of CDAOs Cite Measuring Data, Analytics and AI Impact as Top Challenge”, 20 February 2025. https://www.gartner.com/en/newsroom/press-releases/2025-02-20-gartner-survey-finds-one-third-of-cdaos-cite-measuring-data-analytics-and-ai-impact-as-top-challenge
8. Gartner, “Gartner Says Organizations with Successful AI Initiatives Invest Up to Four Times More in Data and Analytics Foundations”, 16 April 2026. https://www.gartner.com/en/newsroom/press-releases/2026-04-16-gartner-says-organizations-with-successful-ai-initiatives-invest-up-to-four-times-more-in-data-and-analytics-foundations