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Business & Ethical AI

Pieces on AI’s impact on business processes, ROI, leadership decisions, plus the risks, ethics, and reliability of these technologies.

379 articles • Page 2 of 26

EY survey: 47% of companies bypass AI governance despite policies

EY survey: 47% of companies bypass AI governance despite policies

An EY survey suggests that almost half of companies may be skipping AI safety checks even though most have formal rules in place. Many leaders admitted they struggle to find unauthorized AI systems in their networks and worry their teams lack the skills to keep up with needed controls. The gap seems to exist because executives feel pressure to launch AI tools quickly, making it hard to follow all rules closely. Experts recommend more frequent and detailed checks inside the development process, instead of occasional reviews. This governance problem may now be a common risk for companies, not just a special ethical issue.

Anthropic's 2026 report details how it cuts off AI model misuse

Anthropic's 2026 report details how it cuts off AI model misuse

Anthropic's September 2026 report describes how the company's security team detects and blocks people trying to misuse its Claude AI models for things like cyberattacks, scams, and weapon-making. The company uses automated tools to review every request and quickly flag possible problems, which are then checked by analysts. The report lists several areas of harm that were stopped, including malware and surveillance attempts. Anthropic's methods may help other organizations defend against AI misuse, and sharing of threat information might be important for keeping AI services safe. The report also suggests that as AI-enabled attacks rise, strong, built-in protections could become necessary for large AI platforms.

Gallup: 27% of US Workers Fear AI Job Loss in 2026

Gallup: 27% of US Workers Fear AI Job Loss in 2026

Gallup reports that 27% of U.S. workers now worry that technology may make their jobs obsolete, and this fear appears to be increasing. Experts suggest that this anxiety could harm workplace morale and retention if not addressed. Clear communication about how AI might affect specific roles and offering reskilling opportunities may help calm workers' fears. Piloting AI changes in a small way first, and measuring employee concerns, might make transitions smoother. Employers are advised to start with transparent information, support managers, and focus on both people and technical outcomes.

Palantir, Nvidia, Booz Allen cut Anthropic, OpenAI use over data retention

Palantir, Nvidia, Booz Allen cut Anthropic, OpenAI use over data retention

Palantir, Nvidia, and Booz Allen have reduced their use of Anthropic and some OpenAI models because of concerns about how long customer data is kept. These companies may want stronger promises from vendors that no customer data will be stored or used for training. Nvidia is moving more work to its own internal models to keep data private. Some clients appear to want strict guarantees before allowing sensitive data to be used with outside AI models. The trend suggests more companies might ask for zero-data-retention rules, but it is unclear how this will affect AI model quality and business in the long run.

Anthropic CEO urges AI slowdown; OpenAI, xAI back safety call

Anthropic CEO urges AI slowdown; OpenAI, xAI back safety call

Anthropic CEO Dario Amodei wrote an essay in September 2026 asking AI labs to slow down work on advanced AI, and OpenAI's Sam Altman and xAI's Elon Musk quickly supported this idea. Amodei's plan suggests slowing some AI training, letting outside experts closely check AI systems, and making shared safety rules. Anthropic, OpenAI, and Google have been having private talks about making safety standards, but details are still being discussed and nothing is final. The US government may require some safety steps in the future, but for now, companies are trying their own measures, and it is not clear yet if a formal industry group will be created.

Walmart's AI creates store friction despite efficiency goals

Walmart's AI creates store friction despite efficiency goals

Walmart's new AI system may help with some tasks, but workers report it also creates problems on the sales floor. Employees say the AI sometimes misses important jobs like cleaning spills or restocking expired items, and they often have to fix its mistakes. Some reports suggest the AI's timelines and alerts do not fit real-life work, causing stress and more work for staff. Experts suggest testing AI in a few stores first and teaching workers how to use it better. The overall result appears to be a mix of faster planning but also new challenges for store employees.

OpenAI Hack: Kill Switches Limit Data Exposure in Prompt Injection Attack

OpenAI Hack: Kill Switches Limit Data Exposure in Prompt Injection Attack

An attack on OpenAI's model-hosting system may have exposed some sensitive data due to a prompt injection hidden in a third-party PDF. The team responded quickly by shutting down the affected API route, rotating keys, and preserving evidence. There appears to have been no code execution, but some confidential fine-tuning data was leaked in outputs. Rapid use of kill-switches and short-lived tokens may have helped limit the exposure. Engineers have now added new safety checks and updated response procedures to reduce risks in the future.

OECD warns on AI 'skill clones,' urges ethics for employee replicas

OECD warns on AI 'skill clones,' urges ethics for employee replicas

The OECD warns that using AI to clone employee skills in the workplace may risk privacy, labor rights, and personal control. Experts suggest companies should get clear, revocable consent from workers and limit how these skill clones are used, with human oversight on important decisions. Policies may require companies to show employees what data is used, explain the purpose, and allow workers to challenge incorrect or harmful use. Organizations are advised to keep training and decision data separate and to audit these systems regularly. There may also be new rules about who owns these AI clones, how workers are paid for their use, and making sure clones are deleted when employees leave or withdraw consent.

HBR: Empathetic Leadership Makes or Breaks AI Adoption

HBR: Empathetic Leadership Makes or Breaks AI Adoption

The article suggests that empathetic leadership may be essential for successful AI adoption, as employees experience new technology changes both socially and technically. Machines cannot fully replace the trust and empathy that humans build at work, especially in leadership situations like mentoring or complex decisions. While some research finds AI might lower burnout and raise productivity, there may also be a growing sense of disconnection among teams. Experts recommend that companies create spaces for personal connection and carefully measure both productivity and team well-being. Overall, the evidence appears to show that workplaces are more likely to thrive with AI when human connections are protected and valued.

Firms adopt AI ethics playbooks for employee skill cloning

Firms adopt AI ethics playbooks for employee skill cloning

Firms are starting to use clear ethical rules, or playbooks, for AI systems that copy employee skills, but there are many rules about privacy, consent, and fairness. Current advice suggests companies should treat each AI skill clone with care, asking workers for clear permission and explaining how their data will be used and protected. Experts say it is important to track how the systems work, let humans double-check decisions, and spell out how workers will be rewarded or protected. The rules and best practices may keep changing as new laws and guidelines come out from groups like UNESCO and the OECD.

Every Unveils 33 AI Questions for Executives, Offers Roadmap for Adoption

Every Unveils 33 AI Questions for Executives, Offers Roadmap for Adoption

Every has released a guide called "33 Questions Executives Ask About AI - Answered," which gives advice to company leaders about using AI. The guide covers strategy, convincing skeptics, choosing tools, and making sure leaders are involved. Natalia Quintero suggests a 60-day plan to help companies get more value from AI, including setting clear goals and sharing early successes. Mike Taylor describes eight levels of AI adoption, and says good documentation may help companies move faster. Leadership involvement and picking the right tools also seem important for successful AI use, but the guide does not guarantee one solution for everyone.

McKinsey: 80% of leaders measure AI ROI with pre-deployment baselines

McKinsey: 80% of leaders measure AI ROI with pre-deployment baselines

The text suggests that measuring AI impact in companies still feels experimental, but about 80% of leaders who set pre-deployment baselines report meaningful improvements after using AI. Experts recommend recording key workflow metrics before and after AI is added to see clear changes in speed, quality, and reliability. Small test sets may catch early problems, but larger tests and ongoing monitoring appear needed to track real results over time. Continuous measurement is important because workflow changes or model updates might reduce early gains.

Walleye Capital mandates AI fluency for all 400 employees

Walleye Capital mandates AI fluency for all 400 employees

Walleye Capital, a $10 billion hedge fund, now requires all 400 employees to use generative AI tools daily. The company introduced training, usage dashboards, and public leaderboards to encourage adoption, and employees may earn rewards for developing useful tools. Reports suggest that AI helps staff work faster on tasks like drafting and data processing, and performance expectations appear to have risen. There may be no planned layoffs because of the policy, as leadership sees AI as a way to help employees, not replace them. The program's success seems to depend on both technology and fostering a culture that supports experimentation with AI.

Every Unveils 33 AI Questions for Executives, Publicly

Every Unveils 33 AI Questions for Executives, Publicly

Every has released a public document answering 33 common questions executives have about AI, which was previously only for a small group. The guide may help organizations by sharing lessons on strategy, governance, talent, and tool choices, suggesting that success comes from linking AI to clear business goals and changing workflows before adopting new technology widely. The advice in the document appears to match what large consulting firms suggest, such as focusing on a few valuable projects first and tracking real business results, not just experiments. The release might help close gaps in how companies govern and measure their AI efforts, and gives leaders tools to check and improve their own progress.

EU AI Act Updates Rules for Using Internal Company Data

EU AI Act Updates Rules for Using Internal Company Data

The EU AI Act, which began taking effect in 2024 and will be fully applied by 2026, requires companies to disclose if they use internal data like Slack chats and videos for AI training. U.S. rules are less clear and may vary by state, but existing laws on privacy and employment still apply to workplace AI. Regulators suggest that companies should clearly tell employees what data is used, its purpose, who can access it, and give options to opt in or out. Sensitive conversations, such as those about HR or unions, may need extra protection or should be excluded unless approved. Technical steps like encrypting data, blocking risky records, and regularly deleting old data also appear important to meet these new requirements.