Geoprise Technologies - Artificial Intelligence

Geoprise Founder’s Recent Book Dents Rampant AI Hype

admin — Wed, 21 Jan 2026 08:21:53 +0000

Interest in artificial intelligence fell sharply after book was published two months ago

BANGKOK, Thailand, January 21, 2026 ― Worldwide interest in generative artificial intelligence (gen AI) plunged after publication of the influential book You Are Being Scammed, according to Google Trends data. Those trends reveal that the book, written by Geoprise Founder Nelson Nones, dropped at exactly the same moment as the peak of AI hype in November 2025.

Further evidence of the book’s impact came one month later when MIT Technology Review published its series “The great AI hype correction of 2025” on December 15 declaring, “After a few years of out-of-control hype, people are now starting to re-calibrate what AI is, what it can do, and how we should think about its ultimate impact.” Today, the Google Trends data confirm that public interest in AI topics has diminished to less than half its peak two months ago.

Asked during a recent interview about why his book had such great impact, Nones replied that it debunks several key myths propping up the AI bubble. “For example, promoters of large language models (LLMs) make straight-line projections of so-called ‘scaling laws’ to convince gullible investors that artificial general intelligence (AGI) is imminent, requiring only vast investments in power plants and data centers to tip the balance,” said Nones.

“Corporate leaders latched onto the myth of AGI,” he continued, “as a way to cut costs by automating cognitive work, but the notion of AI rendering any more than a fraction of the human workforce obsolete is a fallacy, because most jobs require at least some physio-mechanical ability,” such as manual dexterity, “which no AI system can possibly perform.”

For enterprises, Nones also differentiates strategic from tactical information technology (IT) investment by testing the capability of AI technology to develop competitive advantages or significantly expand their total addressable market on the one hand, versus improve the performance of business as usual on the other. “A recent McKinsey article about ‘rewiring’ enterprises,” he says, “explains how AI agents can help a bank’s human credit managers improve their efficiency and effectiveness, but these are tactical investments in my view because the underlying loan underwriting process remains the same. By contrast, harnessing AI technology to profitably underwrite loans without involving any human credit managers would be highly strategic because it would enable banks to capture new loan demand from customers they are unable to reach through personal visits.”

The problem, according to Nones, is hallucinations that are endemic to gen AI, rendering the technology so unreliable that it cannot be trusted with the responsibilities borne by human workers, such as credit managers, upon whom organizations rely to manage risk. As a result, contrary to recent hype, Nones concludes that most enterprises will limit their adoption of gen AI technology to tactical rather than strategic applications.

Today’s developments are the latest in a series of firsts for Geoprise. In early 2018, the flagship Geoprise enterprise resources planning (ERP) application, GM-X, was the first in the world (CIO Review magazine, November 2018) to combine proven blockchain technology with strong encryption for securing information assets, and it remains the only such ERP application suite on the market today. Later that year, Geoprise was first to market with a responsive mobile-first GM-X Web user interface allowing the entire GM-X application suite to run end-to-end on mobile as well as desktop and laptop devices.

Despite its track record of being first to market with proven ERP innovations, unlike most of its competitors, and to avoid any taint of ‘AI washing,’ Geoprise has resolutely refrained from jumping onto the artificial intelligence (AI) bandwagon. Instead, Geoprise Founders have invested their time to author impactful works of thought leadership, such as You Are Being Scammed (Park Gallery, ISBN 979-8993865614, 132 pages) by Geoprise Founder Nelson Nones, to successfully educate the market about the pitfalls of deploying gen AI technology when implementing mission-critical systems of record such as ERP.

About Geoprise

Geoprise Technologies Corporation was formed in 1999 by a group of software executives with over a century of previous cumulative experience building ERP and manufacturing operations management systems and implementing them worldwide. The privately held company's mission, then and now, is to create exceptional value for its customers by harnessing the power and economy of information technology to enable lean, world-class industrial operations on a global scale. Today, Geoprise focuses exclusively on delivering its state-of-the-art GM-X ERP solution to businesses operating in North America, Europe, Asia, and the Pacific Rim. Geoprise values integrity by maintaining strict independence, intense commitment to business ethics and profound respect for intellectual property rights. For further information, visit the company's website at geoprise.com.

About Park Gallery

Park Gallery is a book publisher and imprint that is a wholly owned subsidiary of Geoprise Technologies Corporation. Its titles are available worldwide in both print and e-book formats at Amazon Books.

Testing the Ability of AI to Discover and Calculate New Reciprocal Tariffs

admin — Mon, 28 Apr 2025 07:33:16 +0000

New reciprocal tariffs imposed by President Donald Trump on April 2nd, 2025, came as a shock to many U.S. importers. The Wall Street Journal reported on April 9th, 2025 that “many companies weren’t financially prepared to absorb the additional cost of tariffs,” because none of them knew at the beginning of this year that tariffs of this magnitude were coming just four months later.

Business Impact of the New Reciprocal Tariffs

An analysis which Geoprise recently performed for one of our clients confirms that the 10% baseline tariff now in effect has already reduced their gross margins on certain imported goods by 40%, assuming that none of the extra costs are passed through to customers, and will further drive gross margins to a 1.5% loss when the suspension of Trump’s country-specific (Annex I) tariffs ends in July 2025.

Our analysis also found that all the enterprise resources planning (ERP) systems on the market today will require modification to accurately compute the new tariffs, and that no ERP vendors other than ourselves have rolled out the necessary modifications to their products. The Wall Street Journal adds that the calculation process has:

become much more complicated as Trump rapidly rolled out new tariffs—and, at times, rolled them back … a company that previously might have had only to calculate one duty rate might now have to figure out three or more levies depending on where the goods were made, whether the items contain steel or aluminum and whether the shipment is compliant with the trade pact known as the U.S.-Mexico-Canada Agreement [USMCA].

The urgency of quickly completing such modifications and incorporating them into business processes that calculate and compare landed costs of imported goods for accounting and supply chain planning purposes will presumably rise in direct proportion to the extent the tariffs are causing pain. Only the most agile of businesses will be able to do this quickly enough to minimize financial losses and seize new opportunities to gain competitive advantages.

The Promise of Artificial Intelligence

Considering recent hype, and in particular the ability to digest reams of global trade data from industry reports and official sources in near real time as well as generate program code automatically, one could hardly imagine a scenario in which artificial intelligence (AI) technology delivers greater potential time-to-live and productivity benefits than this.

Nucleus Research, a U.S. technology research and advisory firm, offers one such hypothesis that:

A full-suite, AI-driven ERP system goes beyond traditional systems of record by driving action through real-time insights … the ability of AI agents and generative AI to rapidly produce contingency plans can reduce response times to unexpected challenges by 40 to 60 percent, enabling organizations to swiftly address emerging issues and maintain operational continuity in the face of unforeseen disruptions. By investing in a modern ERP solution, organizations gain the ability to manage risk and maintain competitiveness in an evolving economic landscape.

So, we designed an experiment for proving this hypothesis.

Method of Investigation

We first performed an analysis of business requirements from official sources using the traditional Google search engine without Google’s “AI Overview” feature to locate the Web sites of the relevant government authorities. Our analysis identified fifteen business requirements as of April 15th, 2025:

In the U.S., retrieve the applicable general (most favored nation, i.e. MFN) and special duty rates from a database using the date and 10-digit harmonized tariff schedule (HTS) code associated with the imported product
In Thailand, retrieve the applicable general (MFN) and special duty rates from a database using the date and 8-digit HTS code based on the Association of Southeast Asian Nations (ASEAN) Harmonized Tariff Nomenclature (AHTN) associated with the imported product
Retrieve and apply preferential rates set out in any applicable trade agreements (for e.g., USMCA when importing goods to the U.S.; ASEAN Free Trade Agreement, i.e. AFTA when importing goods to Thailand) from a database using the date, HTS code associated with the imported product, and country of origin
In the U.S., retrieve and apply any anti-dumping, Section 301, or countervailing duties in addition to the duty rate using the date, HTS code associated with the imported product, and country of origin
In the U.S., customs value includes the cost of the imported goods shown on an accompanying invoice but excludes insurance, freight, and adjustments
In Thailand, customs value includes cost of the imported goods, insurance, and freight (CIF), plus royalty/license fees and the fair market value of goods and services supplied by the buyer free of charge or at reduced cost for use with the production and sale of the imported goods
The U.S. specifies ad-valorem, specific or compound duty rates for each HTS code
Thailand does not use compound duty rates; if a specific duty applies for an HTS code, apply whichever specific or ad-valorem rate yields the larger tax
In Thailand, ad-valorem value-added tax (VAT) is imposed based on CIF value
In Thailand, ad-valorem excise tax is imposed on certain product groups based on CIF value plus customs duty
As per President Trump’s executive order of April 2nd, 2025, additional 10% baseline reciprocal tariff imposed upon all imports from MFN countries of origin to the U.S. from April 5th, 2025 (except imports of goods described in Section 3(b) of that executive order, imports of goods from Canada and Mexico that are eligible for preferential duties under USMCA, and imports of electronics described in a subsequent executive order on April 11th, 2025)
Add Merchandise Processing Fee (MPF) in the U.S.
Add Harbor Maintenance Fee (HMF) in the U.S.
Include historical and future tax/tariff rates in the database with effective dates
De minimis customs duty exemption, if applicable, except for imports to the U.S. that no longer qualify for de minimis treatment under Section 3(h) within President Trump’s executive order of April 2nd, 2025

Next, we put AI to the test by submitting the following prompt to five well-known large language models (LLM):

Please specify the exact computational procedure for determing (sic) the correct tariff amount imposed upon a given good imported into the United States on April 15th, 2025. Then, specify the exact computational procedure for determining the correct tariff amount imposed upon the same good into Thailand on the same date. You may assume that tariff rates, harmonized system (HS) codes, harmonized tariff schedules, and country-specific tariff schedules are stored in a database which may be queried in real time. Use pseudocode snippets or formulas, as needed, to specify all computational procedures.

Our prompt had one typographical error which we purposely did not correct to observe if this would affect the LLM responses.

The five LLMs we prompted were:

OpenAI ChatGPT-4o
OpenAI ChatGPT o4-Mini
OpenAI ChatGPT 4o-Mini
Microsoft Copilot
DeepSeek DeepThink (R1)
Google Gemini

We ran all our tests on Friday, April 25th, 2025. Only Google Gemini corrected the typographical error in our prompt.

Results of the Experiment

Table 1, below, summarizes the experiment results.

In Table 1, an “omission” is defined as one of the fifteen above requirements not mentioned in the LLM response, whereas a “mistake” is one of those requirements which the LLM response mentions, but incorrectly. For example, the DeepSeek DeepThink (R1) LLM mentioned the Merchandise Processing Fee (MPF) in the U.S. but its response was judged to be a mistake because it quoted the wrong ad-valorem rate and maximum fee.

“Fitness for purpose” therefore is the percentage of requirements mentioned without mistakes.

Only one LLM, Microsoft Copilot, mentioned the tariffs which Trump ordered on April 2nd, 2025 but had not suspended by April 15th, 2025. However, at 363 words Copilot’s response was the briefest of all, omitting 60% of all requirements yet making 3 mistakes, so its fitness for purpose was 20%, the lowest of all models tested.

All the tested models achieved a failing grade as to their ability to satisfy all fifteen business requirements, where a passing grade is achieved with at least 60% fitness for purpose on a conventional academic grading scale (letter grades A, B, C or D).

Conclusion

Our experiment conclusively disproves the hypothesis that an AI-driven ERP system can rapidly reduce response times by 40 to 60 percent, and maintain operational continuity, when unforeseen tariff challenges emerge. Such outcomes would only be possible if AI-driven ERP systems could detect most of the relevant tariff policies, and devise procedures to calculate most tariff costs accurately, but our experimental evidence shows that this is not the case. Current AI technology discovers less than half the relevant policies and performs incorrect calculations for over one-third of the policies it discovers.

Meanwhile, using our RADICORE rapid application development framework, Geoprise has already rolled out modifications to its GM-X ERP application suite that manage new master data requirements and accurately compute the new U.S. tariffs which meet all the business requirements enumerated above. Our clients who are exposed to business risks in consequence of the new U.S. tariffs are already benefiting from those enhancements.

Geoprise Technologies - Artificial Intelligence

Geoprise Founder’s Recent Book Dents Rampant AI Hype

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Testing the Ability of AI to Discover and Calculate New Reciprocal Tariffs

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