Guest Editorial: Long Island’s AI Grants Should Buy Results, Not Just Subscriptions

Forty-nine Long Island business owners recently finished an intensive artificial intelligence training program. Each received a $5,000 grant to put a plan into practice. That is a promising investment in local companies. The next question matters more than the graduation ceremony: What will actually change in those businesses?

The LIA-AI Growth Academy brought together the Long Island Association Foundation, Stony Brook University, and funding from Google.org. The five-month program helped firms explore uses of AI for marketing, customer relationships, finance, and productivity. The first class celebrated its completion at Stony Brook on September 24. Those are genuine accomplishments, especially for owners who cannot hire a dedicated technology team.

But there is a trap in the next stage. A business buys a chatbot subscription, writes a few marketing posts, and counts the purchase as adoption. The work may feel faster while customers still wait for answers, invoices require the same number of corrections, and the owner spends evenings checking machine-made claims.

Small companies on the South Shore cannot afford that kind of false efficiency. One misplaced price quote can erase the gain from dozens of AI-generated social media posts. A wrong appointment detail can frustrate a loyal customer. The smallest enterprises need a way to find out whether a new tool improves the outcome that pays their bills.

The academy’s graduates can make a simple experiment out of every grant-funded use case. Choose one recurring task before selecting a product. Record how long it takes now, how often mistakes occur, and what a successful result looks like. Then try an AI-assisted version on comparable work for a few weeks.

A home-services operator might measure the time from an inquiry to a correctly priced estimate. A retailer could track whether customer questions receive accurate replies without the owner stepping in. A professional-services firm could tally research time alongside the corrections its staff must make. These are illustrative tasks, not claims about particular academy participants.

The critical step is counting the checking. When an employee uses AI to draft a customer email in three minutes but then spends seven minutes correcting fabricated details, the tool has saved very little. When a worker catches a bad assumption before a quote goes out, the firm has prevented a loss. Both facts belong on the scorecard.

Evidence from beyond Long Island reinforces the need for clear measures. A May 2026 Census Bureau analysis found that fewer than 20% of firms with four or fewer employees reported using AI, compared with 37% of firms employing at least 250 people. Those figures measure reported use, not profitable integration. They underscore why purchasing a tool cannot stand in for changing a small business’s daily operations.

Because the academy’s grants came from philanthropic funding, participants do not owe the public a disclosure of their private finances. The program could nevertheless publish voluntary, aggregated results at 30, 60, and 90 days: tasks redesigned, staff time recovered after checking, error rates, and owners’ judgments about customer value.

That would give future Long Island small-business cohorts something more useful than a catalog of approved apps. They would gain evidence about which workflows earn their place in a busy company and which ones waste scarce time.

Stony Brook and the Long Island Association have done the hard work of making AI accessible to small businesses. Their next contribution can be showing, in practical terms, which uses actually pay off.

Gleb Tsipursky, PhD, a behavioral scientist, CEO of Disaster Avoidance Experts, and author of The Psychology of AI Adoption at Work: From Resistance to Results (Georgetown University Press, 2026) https://disasteravoidanceexperts.com/aibook