🏗️ IMSPARK: AI Investment Is Building the New Economic Engine🏗️

🏗️Imagine… The AI Boom Is Shows Up in Investment🏗️

💡 Imagined Endstate:

Imagine an economy where AI investment strengthens productivity broadly, not only for the largest firms with the deepest pockets, but for small businesses, public agencies, universities, workers, and communities that need access to the tools, infrastructure, and skills that make innovation useful.

📚 Source:

Kalyani, A., & Li, H. (2026, May 18). Is Optimism for Artificial Intelligence Boosting Investment? Federal Reserve Bank of San Francisco Economic Letter 2026-13. link.

💥 What’s the Big Deal: 

Investment can create the engine, but access determines who gets to drive. If AI investment remains too concentrated, the economy may gain speed while leaving too many communities in the passenger seat. Imagine a future where AI optimism does not just inflate balance sheets, but builds shared capability🔧. 

The AI story is no longer only about chatbots, headlines, or speculative hype. It is showing up in the hard machinery of the economy: equipment, software, servers, data centers, and research budgets🧾. The Federal Reserve Bank of San Francisco reports that spending on information processing equipment, software, and data center construction made up one-third of all U.S. business investment in the third quarter of 2025, the highest share since 1947.

That is a big signal. When companies spend this much on AI-related capacity, they are not just experimenting at the edges🧠. They are building the pipes, power, platforms, and technical infrastructure that future economic activity may depend on. But the report also adds an important caution: official statistics do not have a clean “AI sector” category, making it difficult to say exactly how much investment is truly AI-driven.

Kalyani and Li (2026) get around that problem by listening to firms themselves🗣️. They analyze earnings-call language from public companies to measure which firms are talking positively about AI. The share of AI-positive public firms rose from near zero in 2016 to almost 25% by the third quarter of 2025, with major firms such as Microsoft, Meta, Amazon, Alphabet, Nvidia, Apple, and Tesla appearing among AI-positive firms in 2025.

The real finding is sharper than “AI is boosting investment.” The growth is highly concentrated⚖️. Since early 2024, AI-positive firms accounted for all capital investment growth among public firms, while other firms collectively had slightly negative growth. But even within the AI-positive group, the largest firms did most of the work: in 2025, the biggest AI-positive firms contributed 10 percentage points of the 11% growth in physical capital investment.

That concentration matters because it shapes who controls the rails🚦. Smaller firms may benefit from renting AI infrastructure instead of building it themselves. That can reduce duplication and let more companies use advanced tools. But if the largest firms own the cloud, models, servers, and pricing power, then AI adoption may depend on terms set by a small number of gatekeepers. The report warns that market power from concentration could affect AI service pricing and slow adoption or productivity gains.

For the Pacific, this is where the national investment story becomes local🌺. AI infrastructure may be built by mega firms, but its consequences will reach island schools, hospitals, emergency managers, small businesses, researchers, and government agencies. The question is whether island communities become only customers of distant AI systems, or whether they build enough workforce capacity, data governance, and local use cases to shape the technology for their own needs.

#AIInvestment, #ArtificialIntelligence, #FRBSF, #BusinessInvestment, #DataCenters, #MarketConcentration, #PacificInnovation, #IMSPARK 

🚪IMSPARK: AI Can Open More Doors in Research and Development🚪

 🚪Imagine… AI and the Ideas Production Function🚪

💡 Imagined Endstate:

Imagine a research and development ecosystem where AI helps scientists, entrepreneurs, and policy leaders search wider, test smarter, and combine ideas faster, without pretending that creativity alone replaces human judgment.

📚 Source:

Federal Reserve Bank of San Francisco. (2026, April 15). Benjamin F. Jones | AI in Research & Development. EmergingTech Economic Research Network. link.

💥 What’s the Big Deal: 

AI can expand imagination, but innovation still requires proof. The breakthrough is not just finding more doors. It is building the capacity to open the right ones, test what is inside, and turn discovery into public value. Imagine a future where AI does not replace the researcher, but becomes the lantern in their hand 🔦. It helps reveal more doors, more patterns, and more possible combinations. 

Benjamin F. Jones offers a useful way to picture innovation: imagine a long hallway filled with doors. Behind each door might be a new material, a medical breakthrough, a better battery, a climate solution, or nothing useful at all. Research and development is the costly work of choosing which doors to open, looking inside, and deciding whether the discovery is worth pursuing🧠.

AI changes the hallway. It does not magically build the whole future by itself, but it can label doors that humans might have missed🤖. Because AI systems can absorb enormous bodies of text, code, data, images, and scientific knowledge, they can suggest combinations outside a researcher’s usual neighborhood of expertise. A chemist may search near chemistry. An engineer may search near engineering. AI can scan across disciplines and whisper, “Try that door over there.”

That matters because creativity is often combinatoric🧩. New ideas frequently emerge when existing pieces are recombined in unfamiliar ways. AI can help widen the set of possible ingredients, lowering the cost of exploration and helping researchers see connections that would otherwise stay hidden. In that sense, AI can accelerate the “ideas production function”, the process of turning research effort into new possibilities.

But the strongest part of Jones’s argument is the warning about bottlenecks🧪. Even if AI becomes excellent at generating concepts, many ideas still have to survive experimentation. A model can suggest a drug target, a material, a design, or a process, but the world still has to answer back. Does it work in the lab? Can it scale? Is it safe? Is it affordable? Can it pass regulatory review? Can it be manufactured reliably? The bottleneck may move, but it does not disappear.

That is where the hype needs discipline⚙️. AI may make some parts of R&D dramatically faster, but if experimentation, validation, clinical testing, manufacturing, procurement, or regulation remain slow, the whole system only accelerates so far. A race car still crawls if the bridge ahead is one lane. The future of AI in R&D will depend not only on better models, but on better research infrastructure around the models.

This is a human capital opportunity for the Pacific🌺. AI-enabled R&D should not belong only to elite labs and large mainland institutions. Island communities have urgent innovation needs in renewable energy, cultural preservation, and durable communications. If Pacific researchers and practitioners gain access to AI tools, data, training, and partnerships, they can search their own hallway of doors, and define which discoveries matter.

 

#AIResearch, #ResearchAndDevelopment, #InnovationEconomics, #EmergingTechnology, #HumanCapital, #PacificInnovation, #ResponsibleAI, #IMSPARK

🤖IMSPARK Preparing People for systems and the Future of Work🤖

 🤖Imagine… AI Literacy as a Basic Skill for Every Worker 🤖

💡 Imagined Endstate:

Workforce systems across the U.S. and Pacific integrate AI literacy into education, training, and employment pathways, ensuring workers can understand, use, and responsibly guide AI in their daily work.

📚 Source:

U.S. Department of Labor. (2026, February 13). Training and Employment Notice No. 07-25: Artificial Intelligence Literacy Framework. Link. 

💥 What’s the Big Deal:

Imagine a future where every worker🧑‍🏫, not just engineers, has the confidence and capability to use AI as a tool for opportunity, innovation, and resilience.

Artificial intelligence is no longer a specialized skill, it is becoming a baseline expectation across the entire workforce🧠. The U.S. Department of Labor’s AI Literacy Framework signals a major shift: workers in nearly every field will need to understand how AI works, how to use it effectively, and how to evaluate its outputs responsibly .

The framework defines AI literacy as more than technical knowledge. It includes the ability to interact with AI tools, think critically about results, and apply them ethically in real-world settings🔍. Importantly, it emphasizes hands-on, experiential learning, not just theory, highlighting that AI is something people must actively engage with to truly understand.

This represents a turning point in workforce development. Just as digital literacy became essential in the early internet era, AI literacy is now emerging as a foundational skill for employability and economic participation⚙️. Governments are encouraging education systems, workforce agencies, and employers to embed these skills into training programs at every level.

For the Pacific, this is especially significant🌊. As island economies navigate digital transformation, ensuring access to AI literacy could determine whether communities are empowered participants in the global economy, or left behind.

The deeper message is clear: the future of work is not just about adopting AI, it is about preparing people to work alongside it, question it, and lead with it responsibly🧭.

#IMSPARK, #AILiteracy, #FutureOfWork, #WorkforceDevelopment, #DigitalSkills, #PacificInnovation, #HumanCenteredAI,