New on Phronesis: why process engineering tools fail AI design, and what a phronetic governance architecture actually looks like:
https://enterprisephronesis.substack.com/p/dmaic-is-not-a-governance-framework
#AIGovernance #HRTechnology
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Your organisation has an AI governance framework. It has almost certainly never governed AI.
What it governs is software procurement. The gap between governance posture and architecture is where enterprise AI risk accumulates - in the deployments that succeed, not the ones that fail.
New in Phronesis: four structural requirements of genuine governance. Operational and buildable today.
Legacy back-office tech isn't a technical debt problem; it's a human flourishing problem. It actively repels the talent you need to build the future and strangles the curiosity required for innovation. Your ERP is your culture, codified. Choose wisely.
BCG's new piece points to "agent-led orchestration" as #AI's next step. When AI executes, the uniquely human contribution becomes strategic and ethical oversight. A profound shift for leaders.
#AIStrategy #Leadership #FutureOfWork
https://www.bcg.com/publications/2025/ai-is-outpacing-your-workforce-strategy-are-you-ready
An piece in HBR posits that AI is not a source of sustainable advantage, but a great leveller. By design, it learns from everyone's innovations and makes insights cheaper for everyone else.
This raises a question for leaders: if AI makes data-driven strategy a commodity, what becomes priceless?
The answer must be the inimitable, human elements of our organisations: culture, trust, and our unique ways of working together.
https://hbr.org/2024/09/ai-wont-give-you-a-new-sustainable-advantage
Generative artificial intelligence (gen AI) has the potential to radically alter how business is conducted, and there’s no doubt that it will create a lot of value. Companies have used it to identify entirely new product opportunities and business models; to automate routine decisions, freeing humans to focus on decisions that involve ethical trade-offs, empathy, or imagination; to deliver customized professional services formerly available only to the wealthy; and to develop and communicate product and other recommendations to customers faster, more cheaply, and more informatively than was possible with human-driven processes. But, the authors ask, will companies be able to leverage gen AI to build a competitive advantage? The answer, they argue in this article, is no—unless you already have a competitive advantage that rivals cannot replicate using AI. Then the technology may serve to amplify the value you derive from that advantage.
A thoughtful BCG piece suggests we're focused on the wrong thing with AI and innovation. Giving everyone tools creates variation, but value comes from selection and amplification. This requires a culture and a system built on trust and respect for employee ideas, not just top-down directives. It reframes the workplace as a living system, not a machine.
https://www.bcg.com/publications/2025/how-every-employee-can-become-an-innovator
We are asking the wrong questions about AI. Instead of "How do we automate jobs?", we should ask, "How do we augment our people?".
The shift from role-based tasks to skills-based work is not a technical problem, but a cultural one. The article notes that HR's true role is to be the architect of this transition, fostering the psychological safety and trust required for people to partner with technology. This is how we create a flourishing workplace.
https://hrexecutive.com/the-augmented-human-why-hr-is-the-architect-of-an-ai-powered-future/
The EU AI Act isn't a tax on innovation; it's a leadership test.
Most see a compliance hurdle. See instead a rare opportunity to build a competitive moat made of trust. Proactively embedding fairness and transparency into high-risk AI is how technology becomes a humanising force.
#AI #Leadership #HumanReverence #FutureOfWork
https://hbr.org/2025/09/how-smes-can-prepare-for-the-eus-ai-regulations
The EU AI Act, which will take effect fully in August 2026, is transforming how companies of all sizes build and deploy AI systems. Applications of AI labeled as high risk—including common tools like CV screeners—will soon face strict compliance requirements including documentation, bias mitigation, and human oversight. For small and medium-sized enterprises (SMEs), the stakes are even higher: limited resources make compliance harder, and delays could mean falling behind on AI. But SMEs can turn regulation into advantage. By acting with strategic partnerships and adopting compliance-by-design, they can build trust and stand out. Early movers won’t just meet the rules—they’ll shape them, gaining credibility and momentum as global standards evolve.
Will have to read this one today -> Governor Newsom signs SB 53, advancing California’s world-leading artificial intelligence industry.
We often deploy AI tools with a narrow focus on efficiency, forgetting that technology shapes culture. The default outcome? AI reinforces the organisational silos that disconnect our people and undermine strategic goals.
True value emerges when leaders treat AI not as a departmental toy, but as an enterprise-level instrument for unity.
https://hbr.org/2025/09/dont-let-ai-reinforce-organizational-silos
Artificial intelligence is boosting efficiency in many organizations, but too often it reinforces functional silos rather than breaking them down. Departments adopt AI tools independently, generating fragmented gains that don’t add up to strategic impact—and can even conflict with one another. There are three common pitfalls. First, the “technology-first” trap, in which departments deploy AI solutions without linking them to enterprise goals, creating disconnected fixes. Second, duplication and contradiction: when separate data sets drive opposing conclusions, as in one bank where risk management flagged customers as too risky even as marketing targeted them for growth. Third, undershot targets: isolated AI wins don’t translate into overall customer satisfaction or competitiveness. To counter these risks, leaders should build a “hub and spoke” AI Center of Excellence, anchor AI use to shared enterprise purposes, and incentivize cross-functional collaboration with collective KPIs. Done right, AI can unify organizations and drive transformation.