AI

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

/ , , ,

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

/ , , , ,

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

‘The Collision: What AI Does to Us’

/ , , ,

MIT Sloan professor Eric So’s new book, “The Collision: What AI Does to Us,” explores how artificial intelligence is reshaping human cognition by tempting people to outsource thinking, leading to cognitive atrophy and diminished capacity for sustained focus and judgment. So advises employees to preserve their unique thinking skills, managers to reward both productivity and reasoning, executives to focus on talent development rather than cost-cutting, and educators to teach AI as a tool rather than ban it, emphasizing that AI should amplify human capabilities without replacing critical thinking.

https://mitsloan.mit.edu/ideas-made-to-matter/collision-what-ai-does-to-us

The CIO’s New Mandate: Rearchitecting Enterprise Work

/ , ,

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

6 Guidelines for Governing AI

/ , ,

Sravan Vadigepalli, leading enterprise AI strategy at Lowe’s, outlines six guidelines for governing AI systems that emphasize keeping humans involved in decision-making through principles rather than rigid rules. He stresses the need to encode corporate values as machine-readable governance layers, implement confidence-based human oversight (“trust thermostat”), and ensure context integration for AI reasoning, enabling organizations to shift from directly executing tasks to overseeing AI-driven processes with human judgment focused on exceptions. This governance approach aims to bridge the gap between AI experimentation and scalable business value by redefining roles around setting intent, managing risk, and embedding culture in AI operations.

https://spectrum.ieee.org/6-guidelines-governing-ai

Who Should Own AI? I Started with an Incomplete Answer

/ ,

AI transformation requires shared ownership across technology, security, legal, finance, and business leaders, as no single function can fully own the work. While a chief AI officer or similar executive should be accountable for strategy, governance, and organizational change, effective AI adoption depends on cross-functional collaboration to redesign workflows, manage risk, and integrate AI sustainably into operations.

https://www.cio.com/article/4229636/who-should-own-ai-i-started-with-an-incomplete-answer.html

AI Won’t Replace CIOs. It Will Expose the Ones Who Can’t Lead People

/ , ,

AI is automating much of the technical work previously handled by CIOs, exposing deficiencies in people leadership rather than replacing these executives. Senior IT leaders face increased expectations to manage complex interpersonal challenges—such as difficult conversations and resource negotiations—that AI cannot resolve, highlighting the need for stronger emotional intelligence and communication skills in technology leadership roles. Those CIOs who develop and embrace these people-focused capabilities will be better positioned to succeed in the AI-augmented workplace.

https://www.cio.com/article/4229000/ai-wont-replace-cios-it-will-expose-the-ones-who-cant-lead-people.html

If AI Makes the Decision, Who Owns the Consequence?

/ , ,

As AI increasingly shapes operational decisions rather than merely assisting tasks, organizations face a governance challenge in clearly defining who holds authority and accountability for AI-driven outcomes. Boards should focus on identifying material AI-supported decisions, mapping who can authorize, oversee, and accept consequences for these decisions, and demanding evidence that authority boundaries are respected and exceptions managed. Effective AI governance requires moving beyond inventories toward accountability frameworks that trace decision authority and ensure humans remain responsible for consequences.

https://www.cio.com/article/4226780/if-ai-makes-the-decision-who-owns-the-consequence.html

EY Global Vice Chair: AI’s Biggest Paradox Comes Down to What AI Can’t Do

/ , ,

EY Global Vice Chair Julie Teigland emphasizes that while AI excels at repetitive tasks and data processing, it cannot replace essential human judgment required to set goals, interpret context, and make decisions. She highlights that companies miss out on significant AI productivity gains due to gaps in talent development, particularly in cultivating AI fluency as a leadership skill that integrates technical operation with critical evaluation. Teigland advocates for collaborative approaches across organizations and ecosystems to efficiently scale AI technology without reinventing solutions, citing EY’s work with partners that improved operational performance and speed.

https://fortune.com/2026/09/27/ai-fluency-human-judgment-leadership/

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

/ , ,

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/

Scroll to Top