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Explores the most overlooked obstacles hindering AI adoption in professional environments.
A survey by Adaptavist reveals that one third of knowledge workers are considering changing industries due to AI fears, even as most report increased efficiency from AI tools.
A speculative discussion on how companies might pivot their focus if AI development were to pause for a year, emphasizing strategic adjustments.
Cheap Chinese AI models are rapidly gaining customers in the US market, signaling a significant shift in the competitive landscape.
China's AI strategy prioritizes widespread adoption and integration into the economy rather than competing for frontier breakthroughs, viewing AI as a force multiplier for its economic ambitions.
Oracle cut about 21,000 jobs globally in the last year, representing 13% of its workforce, as the tech giant reshapes its business around artificial intelligence and incurs $1.8bn in restructuring costs.
A reflective question on why people still struggle with AI despite its ability to simplify many tasks, inviting perspectives on the psychological and practical barriers to adoption.
Omio is using OpenAI's ChatGPT and Codex to build conversational travel booking experiences and transform internal operations, moving toward an AI-native approach.
The article highlights the paradox that Generation Z, despite being the most skeptical of AI, is also its largest consumer base.
A look at which AI agents B2B sales teams are actively using in their daily workflows, highlighting real-world adoption trends.
A discussion on the state of AI adoption in companies, questioning whether off-the-shelf tools or custom solutions are more successful.
Samsung Electronics is deploying OpenAI's ChatGPT Enterprise and Codex to employees globally, representing one of OpenAI's largest enterprise deployments to enhance productivity across R&D, marketing, and manufacturing.
Companies are scaling back AI usage as the high costs strain budgets, leading some to call the situation a 'monster' they created.
Deutsche Bank India showcased three AI applications at its Bengaluru GCC, including Financial Spreading for automating financial data analysis, aiming to speed up banking operations and improve risk management, but also putting some banking jobs at risk.
The author argues that governments and companies will increasingly switch to open-weight AI models to avoid US government control over access, noting that open models are only slightly behind closed ones and move at a pace more suited to real-world bureaucracy.
Two years after Sonnet 3.5's release sparked Cursor's viral adoption, open weight models now surpass it, running on consumer hardware. This is a pivotal moment for open source AI.
An analysis arguing that companies fail at AI because they focus on the model rather than the foundational layers—process design, governance, knowledge architecture, human judgment, and feedback loops—which are the true sources of value. The article cites Nadella's 'token capital' concept, Apple's model-swappable Siri, and survey data showing a wide gap between strategy and execution.
Aatish Nayak presents a counterintuitive view: AI is powerful in individual hands, but weakens in companies due to collaboration structure deficiencies (decision-making, permissions, escalation paths, shared memory).
Reflects on the mixed impact of AI automation in enterprises, noting that efficiency gains are often used to justify layoffs while token budgets may be wasteful. Raises data privacy concerns about AI agents accessing work communication platforms.
NEA partner Tiffany Luck discusses on TechCrunch's Equity podcast how enterprises are still grappling with AI ROI, noting trends like tokenmaxxing and cost overruns at companies like Uber and Meta.