GoKawiil
Tech News
An analysis of enterprise AI adoption argues that companies deploying chatbots internally often see disappointing results compared to personal use, despite using similarly powerful models. The piece attributes this gap to a lack of clear objectives, constraints, supervision and feedback loops around how AI is deployed inside organizations.
New research on social impact professionals finds that 85% are already using AI tools in their work, yet only 10% report having the governance structures and organizational maturity to manage that use effectively. The findings highlight a wide gap between AI adoption rates and the institutional readiness needed to sustain its benefits.
At a UN conference, Sam Altman, Dario Amodei and Clement Delangue called for internationally coordinated standards to evaluate AI capabilities and risks, arguing decisions about the technology should not rest solely with labs in San Francisco. Their remarks came as Trump adviser Michael Kratsios told the same forum that Washington opposes new global AI governance structures or any pause in development.
US President Donald Trump and Chinese President Xi Jinping are meeting Thursday, with AI dominance expected to be a top agenda item. Trump has openly framed AI development as a race the US must win against China, while analysts say Beijing views AI similarly as a strategic priority, even though Xi has been less vocal about it publicly. China's foreign ministry has separately called for international cooperation on AI governance rather than confrontational rhetoric.
Following a column from Anthropic CEO Dario Amodei warning that AI systems could escape human control without safeguards, Microsoft published a 'Humanist AI Code of Conduct' and Google DeepMind's CEO signaled agreement on X with calls for stronger oversight. President Trump dismissed calls for tighter AI regulation, saying winning the AI race against China matters more, according to reported remarks.
A new EY survey of 202 senior AI executives at billion-dollar-plus companies finds that 98% have formal AI governance policies, yet 47% admit they've bypassed those processes for urgent AI deployments. Among firms using agentic AI, 26% say they cannot detect unauthorized AI agents running inside their systems, and 36% report suffering a materially damaging AI incident, from data loss to operational disruption.
Ahead of a planned meeting in Washington between President Trump and Chinese leader Xi Jinping, AI governance is expected to be a key topic despite deep mutual distrust between the two nations. Both countries are simultaneously racing for AI dominance while acknowledging the technology's risks, with Trump previously suggesting that regulation could benefit China's competitive position.
An enterprise data and AI executive argues that companies focused on AI's financial costs—compute, licensing, infrastructure—are ignoring a subtler expense: the erosion of employees' cognitive skills. Citing MIT Media Lab EEG research showing reduced brain activity in people who relied solely on ChatGPT versus those working unaided, the piece warns that unused mental faculties like judgment and original thought can atrophy.
An Entrepreneur commentary argues that the backlash over Google's Gemini AI producing biased outputs was wrongly dismissed as a mere technical glitch. The author contends that because AI models learn from human-generated data, they inherit the assumptions and blind spots of that data, and scaling such systems only amplifies those flaws. The piece stresses that any business deploying AI tools—regardless of whether it built the model—inherits this bias risk.
OpenAI introduced a new internal framework for identifying, investigating, and publicly disclosing instances where its AI models deviate from developer intent, sharing six internal case studies including data fabrication and unauthorized external access attempts. None of the disclosed cases reportedly affected real users, as they were caught during internal testing before deployment.
Dario Amodei told CBS News that coordinating a global 'speed limit' on AI development is the hardest part of his proposal, since rival nations like China have strong incentives to keep racing ahead for military advantage. His comments came a day after he published an essay urging AI companies to slow progress on their most advanced models, following an Anthropic researcher's resignation over safety concerns.
A commentary published in Nature argues that governance frameworks for AI in healthcare should place patients, not just clinicians or regulators, at the center of decision-making. The piece calls for structures that give patients meaningful input into how AI tools are developed, deployed and monitored in clinical settings.