strategy

6 IT Wins to Deliver Before the Year Ends

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As 2026 draws to a close, CIOs are focusing on six critical IT objectives: delivering on existing commitments to maintain credibility and secure future funding; demonstrating IT solutions’ reliability during peak business periods; strengthening alignment between IT initiatives and business goals; advancing from AI experimentation to realizing tangible business value; managing escalating AI costs by adopting open-source models and infrastructure; and finalizing 2027 budgets that maximize impact while ensuring financial efficiency. These efforts aim to solidify IT’s strategic role and prepare organizations for continued digital transformation in the coming year.

https://www.cio.com/article/4232788/6-it-wins-to-deliver-before-the-year-ends.html

The 7 Biggest Issues CISOs and Security Teams Face Today

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CISOs today face escalating challenges including increasing AI-enabled cyberattacks, expanding attack surfaces, and amplified stress levels, with 71% citing the complex threat landscape as their main stressor. Key issues include shifting focus from prevention to resilience and recovery, aligning security programs to organizational needs, integrating and securing AI technologies and infrastructure, addressing critical cybersecurity skills gaps, adopting agile security practices to keep pace with rapid threats, and maintaining flawless execution of fundamental security principles. Security leaders must develop tailored strategies and invest in people, processes, and AI security tools to manage these evolving risks effectively.

https://www.csoonline.com/article/4232208/the-7-biggest-issues-cisos-and-security-teams-face-today.html

Unclear AI Risk Ownership Could Leave CISOs in Familiar Scapegoat Role

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Lack of clear ownership over AI risk and governance creates a risk that Chief Information Security Officers (CISOs) will be unfairly held accountable for AI security incidents without corresponding authority to control AI systems. Experts emphasize that while CISOs should oversee AI security boundaries—including reviewing AI deployments, access controls, and monitoring—AI risk management must also involve business, legal, and technology leaders, reflecting AI’s cross-functional impact. To avoid reactive blame and governance gaps, organizations need to define and connect responsibilities across functions proactively before incidents occur.

https://www.techtarget.com/cybersecurity/news/366651977/Unclear-AI-risk-ownership-could-leave-CISOs-in-familiar-scapegoat-role

Your AI Foundation Must Extend Without Surrendering Control

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Enterprise AI success depends less on choosing the “perfect” model and more on building an extensible, sovereign data foundation that supports continuous model changes without fragmenting control. CIOs should prioritize architectures that enforce governance and controls directly at the data layer to accommodate evolving AI workloads and regulatory requirements, enabling seamless model swaps and consistent compliance. Establishing this durable data foundation allows enterprises to maximize AI investment returns while maintaining control over their critical data assets.

https://www.cio.com/article/4232664/your-ai-foundation-must-extend-without-surrendering-control.html

What Top Performers Do Differently with AI—and Why They See the Biggest Benefits

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Research shows that AI boosts productivity most for top performers who leverage it to enhance their inherent strengths, enabling them to focus on higher-value activities rather than routine tasks. While AI provides some benefits to all workers, its greatest impact comes from integrating AI within systems that amplify the skills of high achievers, influencing firms’ approaches to hiring, training, and team organization.

https://hbr.org/2026/10/what-top-performers-do-differently-with-ai-and-why-they-see-the-biggest-benefits

AI Is Making Software Cheap to Build. Is Your Organization Ready for What Comes Next?

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AI is significantly reducing the cost and time required to build software, enabling even small teams to develop complex custom applications rapidly. This shift challenges traditional enterprise IT governance and software portfolio management, as decentralized, AI-assisted development increases the number of untracked tools and elevates risks related to compliance, control, and ownership. CIOs and CTOs must prepare for a future of software abundance by focusing less on scarcity of development resources and more on managing, governing, and retiring the growing volume of AI-generated software assets within their organizations.

https://www.cio.com/article/4231346/ai-is-making-software-cheap-to-build-is-your-organization-ready-for-what-comes-next.html

Want Employees to Embrace AI? Stop Selling It as a Productivity Tool

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Stanford researchers found that employees are more likely to embrace AI when it is introduced as a tool to enrich their jobs rather than merely boost productivity. Successful AI adoption depends on managers framing AI use to enhance meaningful work, providing time and training for exploration, and aligning performance metrics to reflect new job responsibilities. Without these supports, AI initiatives risk employee disengagement and reduced motivation to learn new skills.

https://hai.stanford.edu/news/want-employees-to-embrace-ai-stop-selling-it-as-a-productivity-tool

IT Modernization: Still a Make-or-Break Project for CIOs

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CIOs continue to view IT modernization and application portfolio rationalization as critical, complex initiatives essential for controlling costs and enabling innovation, especially in the evolving AI era. Leaders emphasize a business-driven approach that balances reducing complexity with meeting current and future organizational needs, often re-evaluating SaaS tools and considering custom AI-enabled solutions. Despite challenges like cost and data migration, ongoing modernization efforts remain indispensable for creating agile, future-ready IT environments that support better efficiency, risk reduction, and alignment with business goals.

https://www.cio.com/article/4225171/it-modernization-still-a-make-or-break-project-for-cios.html

A ‘Safe-to-Fail’ Culture Can Help IT Teams Achieve Great Things

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Building a safe-to-fail culture in IT teams involves removing fear of failure by providing employees with time, resources, and clear boundaries to experiment with new technologies in secure environments. Organizations should design controlled experiments focused on specific business problems, incorporate safeguards to limit potential damage, and recognize learning outcomes to drive practical business results. This approach promotes innovation while managing risks through disciplined testing, transparency, and predefined operational and security rules.

https://www.computerworld.com/article/4223580/how-to-build-a-safe-to-fail-culture-for-it-teams-and-why-you-should.html

The CIO’s New Mandate: Rearchitecting Enterprise Work

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The article argues that CIOs must lead a shift from simply managing enterprise applications to redesigning enterprise work itself, leveraging AI agents to orchestrate work outcomes rather than just automating tasks within discrete systems. This new discipline, called Enterprise Work Architecture (EWA), involves mapping business outcomes to work activities, defining authority and execution across humans and AI, and measuring economic impact, enabling more efficient, secure, and transparent operations across integrated applications. The transformation requires CIOs to collaborate across business functions to reimagine how work flows through technology and human judgment, focusing on outcomes rather than individual applications.

https://www.cio.com/article/4230816/the-cios-new-mandate-rearchitecting-enterprise-work.html

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