Why This CIO Won’t Let an AI Agent Take the Blame

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Brigitte Larivière, CIO at Bombardier, emphasizes human accountability in automation by requiring a named person responsible for each AI agent deployed, ensuring clear ownership and measurement of outcomes. She prioritizes automating IT tasks—aiming for 80% automation of outsourced infrastructure work by 2027—while maintaining on-site support to directly assist manufacturing workers and fostering controlled citizen development with approved tools. Larivière also highlights cybersecurity as a critical concern amid rapid technological changes, focusing on transparency and risk management as automation and AI adoption accelerate.

https://www.digitaljournal.com/article/why-this-cio-wont-let-an-ai-agent-take-the-blame/

Microsoft Copilot Now Lets Marketers Build Their Own Apps and Dashboards

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Microsoft has introduced a new Code workspace within Copilot that enables marketers to create internal apps, dashboards, trackers, and automations using natural language without traditional programming. This feature, along with Copilot Managed Runtime, allows organizations to build, host, and control custom tools directly within the Microsoft 365 environment. The update aims to empower non-developers to create and deploy small software solutions for marketing needs, potentially reducing reliance on separate third-party applications.

https://searchenginewatch.com/microsoft-copilot-now-lets-marketers-build-their-own-apps-and-dashboards/

Stop Automating Old Processes. Design New Ones Instead.

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Companies often fail to realize enterprise-wide value from AI investments by automating individual tasks rather than redesigning entire workflows that produce business outcomes. The authors recommend a framework focused on redesigning workflows, explicitly assigning human authority, and preparing for exception handling to ensure AI improves end-to-end processes, preserves outcome quality, and manages risks effectively. Successful AI transformations require deliberate decisions about what to redesign, how humans and AI collaborate, and how to handle uncertainties, rather than mechanizing legacy work.

https://hbr.org/2026/09/stop-automating-old-processes-design-new-ones-instead

Why the Most Obvious AI Use Case Is Often the Wrong One

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Midsize law firms should focus AI adoption on work where efficiency gains are measurable and verification burdens are manageable, rather than simply targeting the highest-volume tasks. Key factors influencing ROI include the ease of verifying AI outputs and the firm’s pricing model, with fixed-fee work providing the clearest demonstration of commercial value. Firms already using AI informally must formalize their approach by selecting AI-suitable tasks that balance verification complexity and billing structure to build a strong internal business case and guide strategic investment.

https://www.thomsonreuters.com/en/institute/spotlight/midsize-firms-obvious-ai-use-cases

How CIOs Use AI to Better Manage Data Lifecycles

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CIOs are leveraging AI to enhance data lifecycle management by improving data quality, curation, and accessibility across creation, storage, usage, archival, and destruction stages. While AI can automate tasks like data cleansing and anomaly detection, leaders emphasize that high-quality, trustworthy data and human oversight remain critical, especially in regulated industries. Despite current limitations and trust concerns, organizations are integrating AI-driven tools incrementally to boost efficiency in targeted processes such as metadata tagging, data governance, and fast information retrieval.

https://www.cio.com/article/4222776/how-cios-use-ai-to-better-manage-data-lifecycles.html

Employees Use AI, but Many Say They Don’t Know Why

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A Culture Amp study found that while 85% of employees are encouraged to use AI at work and 71% feel more productive with it, only 58% understand why their companies are implementing AI, and just 60% have received examples from managers on how AI supports their work. The report also noted similar workload levels between AI users and nonusers, suggesting a gap between perceived productivity gains and actual output, and emphasized the need for leadership to provide clearer communication and strategic frameworks around AI adoption to realize true organizational ROI.

https://www.hrdive.com/news/employees-use-ai-but-many-say-they-dont-know-why/831073/

The Accidental CIO Is Disappearing, and That Might Be a Problem

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The traditional “accidental CIO,” who gained broad leadership experience through varied, unstructured roles, is becoming rare as technology careers grow more specialized and structured. This shift creates a challenge because modern CIOs need not only deep technical expertise but also extensive business, financial, and leadership experience to effectively influence enterprise strategy and navigate complex transformations. To prepare future CIOs for these expanded responsibilities, organizations should deliberately engineer diverse experiential development—such as managing P&Ls, leading major transformations, and engaging with executive stakeholders—rather than relying solely on certifications or narrowly focused career paths.

https://www.cio.com/article/4225055/the-accidental-cio-is-disappearing-and-that-might-be-a-problem.html

‘Not My Cup of Tea’ Is the Most Expensive Sentence in Your Engineering Org

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As AI commoditizes much of traditional coding work, engineers must develop stronger communication and customer-facing skills to remain relevant and add value. The article argues that organizations should break down silos, promote cross-functional collaboration, and encourage engineers to engage directly with customers to improve judgment and product outcomes, while emphasizing coaching willing engineers in these capabilities rather than expecting all to do so. This shift reflects a market repricing of roles toward engineers who can understand the broader context, navigate trade-offs, and explain technical decisions beyond their specialization.

https://www.cio.com/article/4225109/not-my-cup-of-tea-is-the-most-expensive-sentence-in-your-engineering-org.html

Risk Management Isn’t an Insurance Decision, It’s a Leadership Decision

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Powell Brown, CEO of Brown & Brown, emphasizes that risk management is a leadership responsibility that requires continuous engagement rather than treating insurance as a transactional annual renewal. Effective risk management involves understanding exposures, preparing for diverse scenarios, and integrating risk considerations into business operations to protect organizational assets amid evolving threats like cyberattacks, AI governance challenges, and geopolitical uncertainty. Brown advocates for specialized, advisory-driven risk strategies tailored to each industry to help leaders make informed decisions and strengthen their organizations proactively.

https://www.chicagobusiness.com/crains-content-studio/publishing-partner/ccb-risk-management-insurance-leadership-brown/

7 Ways to Restructure IT for Maximum Productivity

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CIOs can boost IT productivity by restructuring around business value, consolidating key teams like security and engineering, and creating cross-functional groups with end-to-end ownership of business capabilities. Emphasizing workflow optimization, domain expertise with mentoring, disciplined tool management, and collaborative problem-solving reduces friction, breaks down silos, and aligns IT efforts with strategic outcomes. Integrating AI thoughtfully into platforms and operations further enhances agility and impact across technology functions.

https://www.cio.com/article/4224624/7-ways-to-restructure-it-for-maximum-productivity.html

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