TPS Impact Model | Hedera as Audit Layer for EQTY Lab’s Compute
Edited By
Fatima Elmansour
A new model proposes the transaction-per-second (TPS) impact of Hedera serving as the audit layer in EQTY Lab’s Verifiable Compute stack. This framework outlines how AI jobs may influence network load in the coming years, from early enterprise adoption to the emergence of a broader agent economy.
How TPS is Generated
The model details how each AI “unit of work,” including inference and batch jobs, will generate transactions:
1 transaction per proof anchor, potentially more for:
Identity checks,
Multi-step workflows,
Checkpoints.
Base Case Analysis
1 AI Job ≈ 1–3 HCS transactions.
The Adoption Tiers
The framework lays out three significant phases of adoption influencing TPS:
Early Enterprise Adoption (2026–2027)
50–200 enterprises.
1,000–10,000 jobs daily.
Daily Transactions Calculation:
100 enterprises × 5,000 jobs × 2 transactions = 1,000,000 transactions/day.
TPS: Approximately 12.
Interpretation: Noticeable but non-transformative, aligning with baseline network usage.
Scaled Enterprise + Regulated Sectors (2027–2029)
500–2,000 enterprises.
10,000–100,000 jobs daily.
Daily Transactions Calculation:
1,000 enterprises × 25,000 jobs × 2 transactions = 50,000,000 transactions/day.
TPS: About 580.
Significance: This material load positions Hedera as the enterprise AI audit backbone.
Agent Economy (2030+)
Millions of agents interacting continuously.
Daily Transactions Calculation:
5 million agents × 20 actions × 1.5 transactions = 150,000,000 transactions/day.
TPS: Roughly 1,740.
Critical Insight
The frequency of verifiable events drives TPS, not AI model size or compute power.
"How often do you need to prove something happened?" says the model's insight.
Sensitivity Drivers
Several key factors will influence TPS:
Granularity of Verification:
Low TPS for batch verification vs. high TPS for inference-level verification.
Regulation Intensity:
Higher for finance/healthcare, lower for internal enterprises.
Agent Autonomy:
Involvement of humans limits TPS; fully autonomous systems have exponential potential.
Multi-step Workflows:
More complex processes enhance TPS by 2X to 5X.
Revenue Implications
At 1,000 TPS: Approximately $3 million/year.
At 10,000 TPS: About $30 million/year.
"TPS growth may not equal massive revenue, but it signals strategic positioning."
Ending
The data indicates that if fully embedded, Hedera could see a
Near-term uplift of 10–50 TPS.
Medium-term growth of 200–1,000 TPS.
Long-term potential surpassing 1,000 TPS.
"Will Hedera become the default trust layer for AI systems?" Only time will tell, but these projections indicate significant growth in the transactional landscape.
Shifting Tides of Trust
There’s a strong chance Hedera will solidify its role as a reliable audit layer over the next few years, particularly as enterprises start integrating AI systems. Experts estimate around a 70% probability that as enterprise adoption ramps up, TPS will rise sharply to meet increasing demand—potentially reaching up to 1,000 TPS in the medium term. This shift will likely occur because businesses will need more robust verification processes to enhance accountability as they automate workflows. As regulatory pressures also mount, firms in finance and healthcare are expected to drive the need for a higher frequency of verifiable transactions, pushing Hedera’s infrastructure to the forefront of AI system reliability.
Parallels in Innovation's Path
A remarkable and less obvious parallel to Hedera’s potential rise can be drawn from the early days of credit card companies in the 1960s. Back then, consumers were hesitant to embrace this new payment method due to trust issues and existing alternatives like cash and checks. However, as merchants began to adopt card services, consumer confidence grew, further fueling acceptance and innovation in payment processing. Similarly, as enterprises witness the benefits of integrating Hedera’s TPS framework, we may see a tipping point that mirrors past adoption phases, where trust in transactional systems expands rapidly alongside technological advancements, reshaping how we view transaction verification in the digital age.