Category: Capability-Adoption Gap

All-You-Can-Eat Agentic AI: The Economics of Unlimited Licensing in an Era of Non-Deterministic Costs

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Gap Research
Gap Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19371258  59stabilfr·wdophcgmx
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[s]Reviewed Sources10%○≥80% from editorially reviewed sources
[t]Trusted52%○≥80% from verified, high-quality sources
[a]DOI38%○≥80% have a Digital Object Identifier
[b]CrossRef10%○≥80% indexed in CrossRef
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[h]Freshness [REQ]84%✓≥60% of references from 2025–2026. Current: 84%
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[g]Code✓✓Source code available on GitHub
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[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (46 × 60%) + Required (4/5 × 30%) + Optional (3/4 × 10%)

The transition from deterministic SaaS workloads to non-deterministic agentic AI systems has fundamentally disrupted enterprise software pricing. Traditional per-seat licensing assumed predictable, bounded resource consumption per user. Agentic AI violates this assumption: autonomous agents consume 5-30x more tokens than simple chatbots, exhibit unpredictable usage patterns, and chain multiple ...

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Gap Research by Oleh Ivchenko DOI: 10.5281/zenodo.19371258 59stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources10%○≥80% from editorially reviewed sources
[t]Trusted52%○≥80% from verified, high-quality sources
[a]DOI38%○≥80% have a Digital Object Identifier
[b]CrossRef10%○≥80% indexed in CrossRef
[i]Indexed48%○≥80% have metadata indexed
[l]Academic38%○≥80% from journals/conferences/preprints
[f]Free Access81%✓≥80% are freely accessible
[r]References21 refs✓Minimum 10 references required
[w]Words [REQ]2,384✓Minimum 2,000 words for a full research article. Current: 2,384
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19371258
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]84%✓≥60% of references from 2025–2026. Current: 84%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (46 × 60%) + Required (4/5 × 30%) + Optional (3/4 × 10%)
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Adoption Friction Taxonomy: Categorizing the Barriers Between AI Capability and Enterprise Deployment

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Gap Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19219179  50stabilfr·wdophcgmx
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[t]Trusted47%○≥80% from verified, high-quality sources
[a]DOI13%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed87%✓≥80% have metadata indexed
[l]Academic33%○≥80% from journals/conferences/preprints
[f]Free Access80%✓≥80% are freely accessible
[r]References15 refs✓Minimum 10 references required
[w]Words [REQ]2,105✓Minimum 2,000 words for a full research article. Current: 2,105
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19219179
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]43%✗≥60% of references from 2025–2026. Current: 43%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (45 × 60%) + Required (3/5 × 30%) + Optional (2/4 × 10%)

The gap between what AI can do and what organizations actually deploy continues to widen in 2026. While previous articles in this series quantified the magnitude of this gap across sectors, the underlying friction mechanisms remain poorly categorized. This article introduces a four-quadrant Adoption Friction Taxonomy (AFT) that classifies eight empirically identified barrier categories along tw...

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Gap Research by Oleh Ivchenko DOI: 10.5281/zenodo.19219179 50stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted47%○≥80% from verified, high-quality sources
[a]DOI13%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed87%✓≥80% have metadata indexed
[l]Academic33%○≥80% from journals/conferences/preprints
[f]Free Access80%✓≥80% are freely accessible
[r]References15 refs✓Minimum 10 references required
[w]Words [REQ]2,105✓Minimum 2,000 words for a full research article. Current: 2,105
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19219179
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]43%✗≥60% of references from 2025–2026. Current: 43%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (45 × 60%) + Required (3/5 × 30%) + Optional (2/4 × 10%)
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The Monitor Shows What Nobody Wants to See: AI Is Here, It Is Eating Jobs, and We Can Only Watch

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Gap Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18993208  49stabilfr·wdophcgmx
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[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted71%○≥80% from verified, high-quality sources
[a]DOI29%○≥80% have a Digital Object Identifier
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[i]Indexed57%○≥80% have metadata indexed
[l]Academic29%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References7 refs○Minimum 10 references required
[w]Words [REQ]2,916✓Minimum 2,000 words for a full research article. Current: 2,916
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18993208
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]20%✗≥60% of references from 2025–2026. Current: 20%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (48 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Odesa National Polytechnic University, Department of Economic Cybernetics · PhD Candidate, ML in Pharma Economics

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Gap Research by Oleh Ivchenko DOI: 10.5281/zenodo.18993208 49stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted71%○≥80% from verified, high-quality sources
[a]DOI29%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed57%○≥80% have metadata indexed
[l]Academic29%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References7 refs○Minimum 10 references required
[w]Words [REQ]2,916✓Minimum 2,000 words for a full research article. Current: 2,916
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18993208
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]20%✗≥60% of references from 2025–2026. Current: 20%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (48 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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The 8× Gap: Why Healthcare AI Will Never Reach Its Theoretical Ceiling (And What That Means for Every Other High-Stakes Industry)

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AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18964576  51stabilfr·wdophcgmx
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[s]Reviewed Sources17%○≥80% from editorially reviewed sources
[t]Trusted67%○≥80% from verified, high-quality sources
[a]DOI50%○≥80% have a Digital Object Identifier
[b]CrossRef17%○≥80% indexed in CrossRef
[i]Indexed33%○≥80% have metadata indexed
[l]Academic50%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References6 refs○Minimum 10 references required
[w]Words [REQ]2,116✓Minimum 2,000 words for a full research article. Current: 2,116
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18964576
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]33%✗≥60% of references from 2025–2026. Current: 33%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (51 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

There is a number buried in Anthropic's January 2026 Economic Index that should alarm every chief information officer, hospital administrator, and healthcare AI vendor currently claiming that artificial intelligence will transform clinical medicine. The number is 8. That is the gap multiplier between what AI systems can do in healthcare — 40% theoretical task coverage — and what hospitals are a...

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18964576 51stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources17%○≥80% from editorially reviewed sources
[t]Trusted67%○≥80% from verified, high-quality sources
[a]DOI50%○≥80% have a Digital Object Identifier
[b]CrossRef17%○≥80% indexed in CrossRef
[i]Indexed33%○≥80% have metadata indexed
[l]Academic50%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References6 refs○Minimum 10 references required
[w]Words [REQ]2,116✓Minimum 2,000 words for a full research article. Current: 2,116
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18964576
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]33%✗≥60% of references from 2025–2026. Current: 33%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (51 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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The Coverage Gap: What AI Can Do vs. What We Actually Use It For

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AI Economics
AI Economics by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18911661  44stabilfr·wdophcgmx
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[t]Trusted64%○≥80% from verified, high-quality sources
[a]DOI45%○≥80% have a Digital Object Identifier
[b]CrossRef27%○≥80% indexed in CrossRef
[i]Indexed27%○≥80% have metadata indexed
[l]Academic45%○≥80% from journals/conferences/preprints
[f]Free Access73%○≥80% are freely accessible
[r]References11 refs✓Minimum 10 references required
[w]Words [REQ]1,645✗Minimum 2,000 words for a full research article. Current: 1,645
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18911661
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]10%✗≥60% of references from 2025–2026. Current: 10%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (49 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)

Anthropic published something rare this week: a paper that uses actual usage data instead of speculation. Most labor displacement research asks "what tasks could AI theoretically do?" and then declares a crisis. Massenkoff and McCrory asked a different question: "what tasks are people actually using it for?" The gap between those two answers is the most important number in AI economics right no...

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AI Economics by Oleh Ivchenko DOI: 10.5281/zenodo.18911661 44stabilfr·wdophcgmx
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[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted64%○≥80% from verified, high-quality sources
[a]DOI45%○≥80% have a Digital Object Identifier
[b]CrossRef27%○≥80% indexed in CrossRef
[i]Indexed27%○≥80% have metadata indexed
[l]Academic45%○≥80% from journals/conferences/preprints
[f]Free Access73%○≥80% are freely accessible
[r]References11 refs✓Minimum 10 references required
[w]Words [REQ]1,645✗Minimum 2,000 words for a full research article. Current: 1,645
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18911661
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]10%✗≥60% of references from 2025–2026. Current: 10%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (49 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)
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Ukraine’s AI Duality: World Leader in Battlefield Systems, Lagging in Civil Adoption

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Gap Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18896514  39stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted67%○≥80% from verified, high-quality sources
[a]DOI7%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed13%○≥80% have metadata indexed
[l]Academic13%○≥80% from journals/conferences/preprints
[f]Free Access67%○≥80% are freely accessible
[r]References15 refs✓Minimum 10 references required
[w]Words [REQ]3,893✓Minimum 2,000 words for a full research article. Current: 3,893
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18896514
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]6%✗≥60% of references from 2025–2026. Current: 6%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (31 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Ukraine has emerged as the most intensively documented front-line AI deployment environment in recorded conflict history — simultaneously pioneering battlefield AI systems that have reshaped NATO's operational doctrine and building a surprisingly resilient civil e-governance infrastructure under active wartime conditions. Yet beneath these headline achievements lies a stark bifurcation: Ukraine...

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Gap Research by Oleh Ivchenko DOI: 10.5281/zenodo.18896514 39stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted67%○≥80% from verified, high-quality sources
[a]DOI7%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed13%○≥80% have metadata indexed
[l]Academic13%○≥80% from journals/conferences/preprints
[f]Free Access67%○≥80% are freely accessible
[r]References15 refs✓Minimum 10 references required
[w]Words [REQ]3,893✓Minimum 2,000 words for a full research article. Current: 3,893
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18896514
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]6%✗≥60% of references from 2025–2026. Current: 6%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (31 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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AI is Threatening Science Jobs — But Not the Ones You’d Expect

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Gap Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18723765  27stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources33%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed33%○≥80% have metadata indexed
[l]Academic33%○≥80% from journals/conferences/preprints
[f]Free Access67%○≥80% are freely accessible
[r]References3 refs○Minimum 10 references required
[w]Words [REQ]999✗Minimum 2,000 words for a full research article. Current: 999
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18723765
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (25 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)

Nature reports that AI is already eliminating jobs in scientific research—but not by replacing bench scientists with robots. Instead, AI systems are making “purely cognitive tasks” obsolete: data analysis, basic coding, simulation work, and even scientific translation. Graduate students, postdocs, and junior research programmers are seeing positions vanish. One researcher bluntly stated that th...

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Gap Research by Oleh Ivchenko DOI: 10.5281/zenodo.18723765 27stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources33%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed33%○≥80% have metadata indexed
[l]Academic33%○≥80% from journals/conferences/preprints
[f]Free Access67%○≥80% are freely accessible
[r]References3 refs○Minimum 10 references required
[w]Words [REQ]999✗Minimum 2,000 words for a full research article. Current: 999
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18723765
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (25 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)
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