The AI Pulse
Issue #82 — 29th June 2026
Editor: Professor Alan Brown
This week's AI Pulse is supported by AI Week, the ten day event from 12-23 October bringing together leaders from across the UK's public, private, and third sectors to explore what AI means for digital leadership. We're now open for talk submissions. If you have a perspective worth sharing, we want to hear from you. Click here to find out more and submit your talk proposal.
Highlights in this edition include:
AI for Good
Artificial Intelligence and the Future of Citizen Participation (OECD) - The opportunities and challenges of the adoption of AI tools to improve citizen participation based on 50 AI use cases from 22 OECD Member and partner countries.
Rethinking EU AI policy: why public subsidies for AI should deliver real wellbeing (Oxford Internet Institute) - Oxford researchers are pushing the EU to shift its AI policy focus from simply minimizing harm to requiring that publicly funded AI projects actually improve people’s lives and wellbeing.
Bias and Ethics
Employees Aren’t Questioning AI Advice Enough (Harvard Business) - A Harvard study found that people using AI for decisions often skip reading why the system made its recommendation—especially when financial incentives are at stake or when explanations might reveal troubling biases, suggesting organizations need stronger safeguards beyond just offering transparency.
‘You can’t make billions without hurting people’: Cory Doctorow on Elon Musk, the AI bubble and bosses’ cruel fantasies (The Guardian) - Cory Doctorow argues that AI’s appeal to executives isn’t about delivering on promises, it’s about the fantasy of control and cutting human costs, even as the technology consistently underperforms.
AI promised to democratise academic publishing – the evidence says otherwise (LSE Impact) - AI tools promised to help researchers from non-English-speaking countries compete on equal footing in academic publishing, but new evidence shows they’re actually widening the gap instead of closing it.
Meta halts worker tracking for AI training due to privacy fears (BBC Technology) - Meta has stopped monitoring employees’ computer activity for AI training after raising privacy concerns, a practice it quietly began just two months ago to gather real-world data for its models.
Cyber Security
AI-powered cyber attacks may be just months away, warn Five Eyes (Computer Weekly) - Five Eyes intelligence agencies are warning that advanced AI models could power sophisticated cyber attacks within months, not years, and is urging governments and businesses to prepare now as hostile nations race to weaponize the technology.
Why AI tokens will send your enterprise cloud bill sky-high again (ZDNET) - AI token pricing is starting to feel a lot like the early cloud era wher costs can spiral quickly, and companies still don’t have a reliable way to measure what they’re actually getting in return for all that spending.
Data & Decision Making
Teach Your AI How You Make Decisions (Harvard Business) - Harvard Business Review argues that companies must now make their tacit decision-making processes explicit by codifying employee judgment on risk, quality, and tradeoffs so that AI agents can scale that expertise consistently across the organization.
Designing Decision Rights for AI (MIT CISR) - MIT researchers propose a practical framework for deciding when to hand decisions to AI versus keeping humans in the loop, based on how much ambiguity and risk are involved.
Capturing Central Europe’s AI opportunity (McKinsey) - McKinsey analyzes how Central European countries can leverage AI adoption to boost economic competitiveness, identifying key sectors where targeted investment could accelerate growth and close the innovation gap with Western Europe.
The missing prerequisite: why data quality must come before Government AI (UKAuthority) - The UK Government is racing to adopt AI across public services. But there is a problem that no amount of investment in algorithms can fix: some of the underlying data is not good enough to support it.
Innovation & Collaboration
Three Approaches to Measuring and Managing AI ROI (MIT Sloan Review) - Three practical frameworks (function-focused, enterprise-wide, or coordinated) that help leaders figure out if their AI spending is actually paying off or just burning budget.
Why open infrastructure will define the AI era (Infoworld) - AI is pushing developers toward pay-per-use platforms, but just like in past tech revolutions, open infrastructure is likely to win out because betting on proprietary lock-in rarely ends well for innovation or cost control.
Productivity & Efficiency
The AI bubble has further to run despite the looming crash (The Guardian AI) - Despite looming fears of a crash, the AI bubble keeps expanding as tech giants rake in massive profits and investors scramble not to miss out, with both groups desperately delaying the inevitable reckoning.
State of UK AI Adoption 2026 — aibl’s Mid-Market Research (aibl) - aibl surveyed 755 UK mid-market leaders across six functions to map how British companies are actually adopting AI, moving beyond hype to understand what’s working on the ground.
UK backs new AI labs to make technology cheaper, more reliable and easier to use (GOV.UK) - The UK is funding new AI labs at Oxford and UCL to develop more affordable, dependable technology that everyday businesses and public services can actually put to work.
The AI world is getting ‘loopy’ (TechCrunch AI) - AI agents are now operating in continuous “loops” where swarms of them run autonomously in the background without needing constant human input, marking a shift from one-off tasks to ongoing, self-managed workflows.
How to implement modern AI SEO services to scale your content velocity without losing quality (Thedatascientist) - Modern AI SEO tools are helping content teams produce more articles faster while keeping quality high to balance search rankings, reader value, and a consistent brand voice.
Regulation and Compliance
Balance AI innovation and risk with ‘minimum viable governance’ (MIT Sloan) - MIT Sloan is championing "minimum viable governance" for AI for a flexible middle ground that scales oversight based on actual risk rather than applying one-size-fits-all rules, helping organizations innovate responsibly without getting bogged down in excessive bureaucracy.
Sustainability
Leveraging AI and digital tools for SME sustainable finance (OECD) - How AI and digital tools can help address bottlenecks across the financing lifecycle, from sustainability data generation and reporting on the SME side, to origination, credit assessment and portfolio monitoring within financial institutions.
Improving the speed and energy-efficiency of AI agents (MIT) - MIT’s new “Murakkab” system automates how AI agents are designed and deployed, slashing both computing costs and energy use.
UN chief urges AI companies to ‘come clean’ about the pollution they generate (Fastcompany) - UN Secretary-General António Guterres is calling on AI companies to publicly disclose the environmental cost of training and running their models, pushing for transparency around the industry’s rapidly growing energy consumption and carbon footprint.
Nvidia wants to cut data center water use, but that’s not the same as fixing AI’s water problem (TechCrunch AI) - Nvidia’s new cooling system reduces water consumption within data centers, but the real issue remains untouched: AI still depends heavily on fossil fuel power plants that guzzle far more water to generate electricity.
User Experience
Transforming Manufacturing at Pfizer: The Hard Part Was Not the Technology (MIT Sloan Management Review) - Pfizer's manufacturing overhaul revealed that cultural barriers, especially mistrust between digital experts and factory floor teams, posed a bigger challenge than implementing the technology itself.
Workforce & Skills
How agents are transforming work (OpenAI) - A new OpenAI research paper shows how AI agents are transforming work, enabling longer, more complex tasks.
Prevent organizational amnesia in the age of AI (CIO) - Companies rushing to replace workers with AI risk losing critical institutional knowledge. Without capturing what departing employees know, organizations end up with AI systems that simply automate confusion at scale.
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