leadership

Where Your Data Team Sits Matters More Than the Code They Write

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Naveen Mylarappa argues that the organizational placement of a data team significantly impacts the return on investment (ROI) of data engineering, beyond just the technical work they perform. The article highlights how data teams aligned under different departments—finance, marketing, engineering, or as standalone units—face distinct incentives and priorities, shaping how their value is perceived and how effectively they drive business outcomes. Ultimately, the key to demonstrating data's impact lies in aligning data efforts with the business goals and incentives of the department sponsoring the work.

https://www.cio.com/article/4148162/where-your-data-team-sits-matters-more-than-the-code-they-write.html

10 Things Keeping IT Leaders up at Night

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The article outlines the top ten concerns keeping IT leaders, especially CIOs, awake at night in 2026, highlighting cybersecurity threats, responsible AI deployment, and governance challenges as foremost. It emphasizes the pressure on CIOs to align technology initiatives with business outcomes, continuously drive impactful transformation, and ensure their teams rapidly upskill amid rapid tech evolution, all while maintaining flawless IT operations.

https://www.cio.com/article/4148311/10-things-keeping-it-leaders-up-at-night-2.html

CIO 100 Leadership Live Atlanta: AI Spending Enters a Reckoning Phase

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At the CIO 100 Leadership Live conference in Atlanta, technology leaders discussed a shift in enterprise AI from rapid growth to a phase emphasizing governance, data accountability, and business justification. Key themes included the need for evolved leadership skills beyond technical expertise, challenges in moving AI initiatives beyond proof of concept, the critical role of knowledge management and data governance, and the importance of integrating AI as a strategic, multidisciplinary leadership priority.

https://www.cio.com/article/4148267/cio-100-leadership-live-atlanta-ai-spending-enters-a-reckoning-phase.html

What It Takes to Level up Your Org’s AI Maturity

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In an interview with AI transformation practitioners Afshean Talasaz and Zar Toolan, key insights are shared on how organizations can advance their AI maturity from initial adoption to driving significant business impact. They emphasize the importance of a combined innovator-operator leadership mindset, detailed preparation, and aligning AI investments with long-term business strategies, supported by strong C-suite and CEO commitment. This approach helps companies move beyond treating AI as an operational tool to embedding it as a strategic asset that delivers measurable value and competitive advantage.

https://www.cio.com/article/4146645/what-it-takes-to-level-up-your-orgs-ai-maturity.html

AI Without Sovereignty Is Just Outsourced Intelligence

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In his opinion piece, Floyd DCosta argues that enterprises adopting AI often gain capability but lack sovereignty—control over how AI models and data are used—creating long-term risks and dependencies on third-party vendors. He emphasizes AI sovereignty as essential, encompassing governance, transparency, data and model control, operational autonomy, and strategic independence, warning that without it, organizations may inadvertently cede their competitive intelligence and face regulatory and operational challenges.

https://www.cio.com/article/4147102/ai-without-sovereignty-is-just-outsourced-intelligence.html

Stop Building Security Goals Around Controls

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Devin Rudnicki, CISO at Fitch Group, emphasizes that security goals should be aligned with business outcomes rather than focused solely on controls, advocating for strategies anchored in corporate objectives, real cyber threats, and industry standards. She highlights three key metrics for security programs—value, risk, and maturity—and stresses the importance of presenting risk in actionable terms for leadership, balancing innovation speed with measured risk, and using automation to free human resources for higher-value work.

https://www.helpnetsecurity.com/2026/03/18/devin-rudnicki-fitch-group-ciso-business-alignment/

The Operational Excellence Playbook for AI Transformation

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The article outlines a framework for AI transformation grounded in operational excellence disciplines like maturity modeling, risk management, cost optimization, and change management, emphasizing that organizations must first establish a strong foundational maturity before adopting AI. It highlights that successful AI adoption depends more on building a robust data layer and ontology aligned with business objectives than merely selecting advanced AI models, and asserts that experienced CIOs who have matured their IT organizations are best positioned to lead AI transformations.

https://nationalcioreview.com/articles-insights/the-operational-excellence-playbook-for-ai-transformation/

The CTO Is Dead. Long Live the CTO

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The article argues that the traditional role of the CTO as the sole technical decision-maker is obsolete in the AI era, where advanced AI systems can rapidly design and optimize complex architectures beyond human capability. Instead, CTOs must shift from gatekeepers to architects of systems, focusing on building frameworks that amplify organizational impact, lead transformative change actively, manage technology economics, and continuously adapt to new tools and workflows. This new mandate demands a disciplined, strategic leader who orchestrates AI-human collaboration to drive speed, quality, and innovation at scale.

https://www.cio.com/article/4145039/the-cto-is-dead-long-live-the-cto.html

Using AI to Pick Team Leaders Without Crossing Ethical Lines

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The featured article discusses how AI can assist CIOs in identifying potential team leaders by analyzing performance data objectively, while cautioning that humans must maintain final hiring authority to avoid legal, ethical, and bias-related risks inherent in AI-based decision-making.

https://www.informationweek.com/it-leadership/using-ai-to-pick-team-leaders-without-crossing-legal-or-ethical-lines

Who in the C-Suite Should Own AI?

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The article discusses the critical question of which C-suite executive should own and oversee AI initiatives in organizations, highlighting the differing perspectives of roles such as the CIO, COO, CFO, Chief Risk Officer, CHRO, and Chief Data Officer. This ownership decision significantly impacts a company's AI strategy, investment, and the distribution of authority and influence among senior leaders.

https://hbr.org/2026/03/who-in-the-c-suite-should-own-ai

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