AI Research Memo

Enterprise AI competition is decided inside procurement systems, not public ad campaigns The real battle is over who controls enterprise AI orchestration and workflow integration Governance, interoperability, and institutional trust now matter more than model branding

German firms adopted generative AI fast, but productivity gains are flattening The next phase is converting adoption into durable agentic AI productivity Education and policy must shift from tools to systems, governance, and measurement

The AI Tax is turning memory scarcity into a hidden cost on education Rising DRAM prices push computing access out of reach for many schools and families Without action, personal computers risk becoming a privilege again The price of memory

Data centers are not modern factories and rarely create broad local prosperity. They often raise local power costs while delivering few permanent jobs. Only strict public-benefit energy rules can rebalance the deal. The dat

The third AI stack is a political ambition, not an industrial reality China’s open-source push wins users, not hardware supremacy Europe and Korea must focus on interoperability and skills, not full-stack rivalry Between Augu

AI data centers are straining local power systems Donations cannot replace enforceable community agreements Real benefits require binding commitments to the grid In 2023, U.S.

LLM-powered tutoring is already automating routine teaching at scale The core challenge is redesigning education labor and governance around AI Without reinvestment in human expertise, automation will widen inequality Picture

AI-integrated courses can handle routine questions and free teachers for higher-value work Well-designed course bots cut response time without hurting learning quality The real policy issue is how to govern AI, not whether to use it

Digital truth can no longer be judged by human sight or sound alone Institutions must certify reality, not just detect fakes after harm occurs Education systems now play a central role in rebuilding trust in evidence In

AI is permanently erasing the entry-level roles that once trained new graduates Public reinvestment funds will fail to rescue these jobs from corporate efficiency measures Universities must urgently adopt high-intensity training models to prevent a workforce crisis

AI transparency is a public good that cannot survive without explicit funding Unfunded openness will weaken Western firms against state-subsidized competitors Paying for transparency is the only way to keep AI markets both open and competitive

Federal AI adoption depends on tools and training, not elite titles DOGE proved rapid automation can work but exposed skill gaps Lasting reform requires institutionalized AI, not rollback Getting AI into

Technological adaptability differs sharply across individuals, making averages misleading Social and economic factors determine who can realistically reskill Policy must target adaptability gaps, not average exposure When

HAIP faces pressure as national AI governance models increasingly diverge China’s state-led approach changes the incentives for voluntary global standards Without economic rewards, HAIP risks losing durability in strategic competition

HAIP increases transparency but does not yet change behavior Voluntary reporting without incentives becomes symbolic Real impact requires linking HAIP to audits and procurement By June 2025, the OECD repo

AI capital is being miscounted, shrinking the economy on paper Hidden AI assets distort policy, funding, and skills planning Fixing measurement is now a growth and governance priority Currently, most official economic reports treat

Minimum wages insure routine workers inside firms Shocks tend to push adjustment onto high-skill jobs Policy must pair the firm-level minimum wage with portable support for talent The increase in South Kore

Advanced economies push AI policy because productivity gains are visible and immediate Poorer countries lag as low returns and weak capacity dampen urgency Education policy can still slow the widening AI divide Since the em

Schools are banning AI while workplaces are adopting it, creating a growing skills gap AI literacy must be taught through teachers and curriculum, not enforced through restrictions on students The real policy failure is institutional resistance to change, not student misuse of technology

The AI fluency gap is becoming the new digital divide, reshaping who advances and who falls behind at work Only a small group of fluent users capture most of AI’s productivity gains, concentrating power and opportunity Education systems and policy must act now to make AI fluency a shared public skill, not a private advantage