Mastodawn

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

How SMEs Can Prepare for the EU’s 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.

Harvard Business Review

Simon Ives Sep 26

The paradox of AI at work: adoption is surging, but ROI is stagnant. A powerful HBR article identifies the culprit: "workslop".

It is defined as AI-generated work that appears polished but lacks substance, shifting the burden of sense-making and rework to the receiver. This isn't just inefficient; it is a failure of leadership that erodes trust and disrespects people's time.

https://hbr.org/2025/09/ai-generated-workslop-is-destroying-productivity

#AI #Workslop #FutureOfWork #HumanReverence

AI-Generated “Workslop” Is Destroying Productivity

Despite a surge in generative AI use across workplaces, most companies are seeing little measurable ROI. One possible reason is because AI tools are being used to produce “workslop”—content that appears polished but lacks real substance, offloading cognitive labor onto coworkers. Research from BetterUp Labs and Stanford found that 41% of workers have encountered such AI-generated output, costing nearly two hours of rework per instance and creating downstream productivity, trust, and collaboration issues. Leaders need to consider how they may be encouraging indiscriminate organizational mandates and offering too little guidance on quality standards. To counteract workslop, leaders should model purposeful AI use, establish clear norms, and encourage a “pilot mindset” that combines high agency with optimism—promoting AI as a collaborative tool, not a shortcut.

Harvard Business Review

Simon Ives Sep 25

In her book "Resistance to Evidence," Mona Simion frames the refusal to update beliefs on available evidence as an "epistemic malfunction." For leaders, this is not just an abstract error. It is a failure of reverence.

Ignoring data on burnout or a failing strategy signals that comfort is valued over truth. This erodes trust and makes it impossible to build a flourishing workplace where people feel respected.

https://www.cambridge.org/core/books/resistance-to-evidence/147AC15A7EA89095A820FF16B1D0525A

#Leadership #Philosophy #HumanReverence #FutureOfWork

Resistance to Evidence

Cambridge Core - Epistemology and Metaphysics - Resistance to Evidence

Cambridge Core

Simon Ives Sep 25

A gov report on AI ethics reveals the gap between policy and practice. The real work isn't writing principles, but building governance. It's the 'how-to' for embedding fairness, maintaining human oversight, and building trust. This is how leaders ensure technology becomes a humanising force, not just an automated one. It's reverence in action.

#AIEthics #Leadership #FutureOfWork #HumanReverence

https://www.qao.qld.gov.au/reports-resources/reports-parliament/managing-ethical-risks-artificial-intelligence

Managing the ethical risks of artificial intelligence | Queensland Audit Office

Artificial intelligence (AI) offers opportunities for the public sector to achieve better social, economic, and environmental outcomes. It can provide operational efficiencies, support decision-making, and enhance the government’s ability to respond to complex challenges.To realise these benefits, entities need to effectively manage ethical risks and ensure the way they use AI aligns with public sector values and community expectations.We focused on policies the Department of Customer Services, Open Data and Small and Family Business has issued that guide entities in managing ethical risks with AI. We also assessed how the Department of Transport and Main Roads, in collaboration with the Queensland Revenue Office, managed ethical risks and controls of 2 AI systems it uses.Tabled 24 September 2025.

Simon Ives Sep 22

95% of AI pilots fail. The reason isn't the tech, it's the leadership. Successful firms have shapers who prioritise human-centric strategy over mere deployment. They prove that making AI work isn't a technical challenge-it's a fundamentally human one.

https://bit.ly/3KeiU63

#HumanReverence #AI #Leadership

What Companies with Successful AI Pilots Do Differently

The overwhelming majority of generative AI programs have so far failed to deliver significant business returns. Research across industries reveals that the small percentage of companies who actually are unlocking AI’s potential are distinguished by leaders who act as “shapers,” aligning technical innovation with business strategy, fostering trust, driving adoption, and embedding AI responsibly into operations. These leaders consistently exhibit five crucial behaviors: strategic agility, human centricity, applied curiosity, performance drive, and ethical stewardship. Rather than concentrating authority in a single AI champion, successful firms need to intentionally cultivate these skills in leaders across teams and levels, so that leadership will become an accelerant, not a barrier, to AI transformation.

Harvard Business Review

Simon Ives Sep 21

The great AI paradox: 80% of companies have adopted new tools but see no real value.

The reason is simple. We are implementing technology without a philosophy. It is time for a fundamental rethink of the 'why' behind our tech strategy.

https://mck.co/4nGoEnu

#AI #FutureOfWork #HumanReverence