The Information Landscape.

The CIPD has launched new AI resources, developed with Innovate UK BridgeAI, to help employers use artificial intelligence responsibly and plan for changing workforce skills. This initiative matters for organisations because research shows that successful AI adoption depends on treating it as a people-centred transformation rather than a purely technical task, requiring cross-functional governance and employee co-creation to avoid low engagement or "shadow AI" use. The policy implications include findings that will inform updates to the CIPD’s Profession Map and the development of ethical AI frameworks and an AI skills framework to guide businesses on workforce readiness.

A recent survey reveals that 29% of employees, including 44% of Gen Z workers, have actively sabotaged their organisation’s AI rollout by entering proprietary data into public tools, using unapproved systems, or refusing to adopt the technology, primarily due to fear of job loss and poorly executed implementation strategies. This behaviour matters for organisations because it undermines AI initiatives, introduces significant security risks, and ironically increases the likelihood of layoffs for those who resist adoption, as 60% of executives are considering cutting employees who refuse to use AI. The findings highlight a critical policy need for organisations to address FOBO (fear of becoming obsolete) through transparent communication, clear role redefinition, and inclusive rollout strategies that prioritise employee protection over mere leverage.

HBR’s latest study finds that generative AI use is widening beyond basic task support, with people adopting it for a broader range of activities as tools such as vibe coding and agentic workflows gain traction. For organisations, this indicates AI is moving deeper into everyday work rather than remaining a niche productivity aid, so leaders need to plan for wider employee use, governance and skills support. The article also suggests the regulatory focus is shifting from simple deployment to oversight of more autonomous AI use, with implications for accountability, risk management and the controls needed around human review and decision making.

The UK government has published non-statutory guidance on responsible AI in recruitment, covering sourcing, screening, interviews and selection. It says organisations should put in place AI governance, transparency, fairness, accountability and contestability controls, and assess risks such as bias, digital exclusion and discriminatory advertising before procuring or deploying these tools. For organisations, the guidance means AI use in hiring should be subject to impact assessments, data protection checks and human oversight, with applicants clearly informed when AI is being used and given routes to challenge decisions. It also reinforces the need to align recruitment systems with UK GDPR, including consideration of Article 22 where automated decision-making may apply, and to prepare for scrutiny from regulators such as the ICO and the EHRC.

The Institute of Directors has published board-level guidance on responsible AI governance, setting out questions directors should ask to ensure AI is identifiable, auditable, measurable and subject to clear accountability, oversight and regular review. It matters for organisations because AI adoption now affects risk, strategy, workforce impacts, data protection and stakeholder trust, so boards are expected to oversee AI use across in-house, vendor and embedded systems rather than leaving it solely to technical teams. The guidance also points to policy and regulatory implications, including the need to monitor changing legal requirements across jurisdictions, map AI controls to applicable standards and maintain formal governance structures, such as named board and executive responsibility, acceptable-use policies and risk assessments.

The British Chambers of Commerce says the UK workforce is not prepared for rapid AI adoption, citing a parliamentary briefing that found only 21% of adults can explain AI meaningfully and just one in five workers feel confident using it. It argues that AI is already associated with net job losses in some firms and that weak reskilling efforts are leaving organisations exposed to labour market disruption, fewer entry-level routes and higher risk of workforce exit. For organisations, the report highlights a need to move beyond short online training and to invest in deeper workforce redesign and capability building. It also points to a policy response, echoing the IMF, that treats AI as a macro-critical transition requiring labour market institutions, portable benefits and transition support to help workers move between roles and stay skill-ready.

The UN Global Dialogue on AI Governance, convening in Geneva on 6,7 July, will address the safety risk and global inequity caused by the AI language gap, where current systems are less safe and useful for users of low-resource languages due to market failures and geopolitical competition focusing on dominant languages. For organisations, this matters because unchecked linguistic bias undermines AI safety, accessibility and trust, creating operational vulnerabilities and ethical liabilities that require targeted R&D investment in multilingual datasets and human annotators. Policy and regulatory implications include potential mandates for model developers to disclose language coverage explicitly, alongside UN-led efforts to strengthen multilingual capacity through transparency requirements and interoperable governance frameworks that ensure AI benefits all nations rather than just technologically advanced ones.