Beyond the AI Bubble: Why Agentic AI will define the next economic phase of automation

The Bubble Nobody Wants to Acknowledge

We’ve been here before.

The late 1990s had the internet boom; the mid-2010s brought crypto euphoria and RPA.

Now, it’s artificial intelligence’s turn in the spotlight, and increasingly, in the crosshairs.

In 2025, AI has become both the economic engine and the potential fault line of global growth. The Bank of England and the IMF have each warned that AI-driven valuations could expose economies to “systemic repricing risk” if expectations collapse (source: Financial Times, May 2025).

Yet amid the hype, there’s a quieter story unfolding: the rise of Agentic AI autonomous systems built not for novelty but for precision, compliance, and data integrity. And nowhere is this more visible than in the automation of e-Invoicing, validation, and reporting.

The Warning Signs of an AI Bubble

By most measures, we’re in bubble territory. Global AI investment is expected to surpass $400 billion by 2026, according to PwC and IDC, a 700% increase in just four years.

Yet, as The Atlantic noted (Sept 2025), many enterprises adopting AI “have not yet demonstrated clear productivity gains.”

The World Economic Forum recently compared today’s AI surge to a hybrid of the dot-com and railway bubbles, immense infrastructure spending justified by future potential rather than current earnings.

Much of this capital is speculative. Start-ups are valued on promise rather than profit, and entire markets are chasing model training capacity rather than proven applications.

As economist Derek Thompson wrote, “The AI bubble will pop when we realise how little it changes daily productivity.”

But that doesn’t mean AI itself will vanish. When bubbles burst, useful technologies remain — electricity, the internet, and mobile computing all emerged stronger after their speculative phases.

Information Pollution and the Value of Accuracy

There’s another risk more subtle than valuation: information pollution.

Researchers at the University of Cambridge warn that low-quality AI content is flooding digital ecosystems, creating a “synthetic noise layer” that obscures reliable data (source: arXiv preprint, Sept 2025).

In other words, we are producing more information than ever, but not necessarily better information.

This dynamic has deep economic implications. Organisations that can guarantee data integrity, not just volume, will gain an enduring competitive advantage. In finance and procurement, that means every invoice, purchase order, and delivery note must be captured, validated, and reconciled with absolute accuracy.

Is this where Agentic AI steps in?

Agentic AI: The Quiet Revolution

Unlike traditional machine learning systems that make predictions or classifications, Agentic AI can plan, act, and reason. It breaks complex workflows into smaller goals, executes each, and self-corrects along the way.

According to Booz Allen Hamilton’s 2025 briefing on AI orchestration, “Agentic systems will define the next decade of digital government operations, particularly where rules, validation, and auditability are paramount.”

In practical terms, that makes Agentic AI ideal for e-Invoicing compliance, where governments now require electronic submissions in standard formats, validated against tax and reporting rules.

These systems can:

• Extract structured data from PDFs or image invoices,

• Validate fields against supplier records, tax codes, and PO data,

• Enrich missing values (e.g., payment terms or GL codes),

• Flag anomalies for human review, (don’t forget the human element!) and

• Submit validated records directly to tax authority APIs.

Each of these actions can be orchestrated by autonomous agents that communicate, verify each other’s outputs, and escalate exceptions, removing the need for traditional OCR-heavy human checking.

Why Compliance-Driven AI Will Outlast Speculation

The AI bubble, if it bursts, will primarily hurt speculative ventures - those built on attention, novelty, or unsustainable compute economics.

By contrast, compliance-anchored applications like e-Invoicing are mandatory. Firms cannot simply opt out of government mandates in the EU, Latin America, or Asia-Pacific.

According to the OECD’s 2025 report on Global E-Invoicing Readiness, more than 70 countries have implemented or announced B2B e-Invoicing frameworks. Each requires accurate, real-time data submission to tax authorities.

That means AI systems designed for data accuracy and validation, not creativity, will continue to receive budget, even in a downturn.

The value proposition is clear and measurable:

• Error reduction: Agentic validation reduces exceptions by up to 95%, based on internal audits across early adopters in Europe.

• Faster cycle times: Straight-through processing can improve working-capital efficiency by 20–30%.

• Audit readiness: Every decision and correction is logged, enabling full traceability.

These are tangible returns. They’re not speculative, they’re operational.

Economic Resilience Through Useful AI

If, or when, the AI market corrects, capital will flow away from hype and toward utility.

Economies that have embedded AI into their compliance, taxation, and trade frameworks will be more resilient, because they will already have digital infrastructure delivering measurable value.

It’s a familiar pattern: after the dot-com bust, the survivors were those solving real problems pa, such as payments, logistics, communication. The same will be true of AI.

Governments that are mandating e-Invoicing and digital reporting are, perhaps unknowingly, creating the perfect proving ground for Agentic AI, a system of interoperable, rule-driven agents that can handle complexity with reliability.

For enterprises, the message is simple: focus on AI that makes data right, not just AI that makes data.

Looking Ahead: The End of the Beginning

It’s tempting to treat the AI boom as an all-or-nothing moment, either it changes everything or it implodes. The truth will be messier.

Some ventures will vanish. But AI that integrates, validates, and enriches the world’s financial and trade data will remain, and thrive.

Agentic AI represents the shift from experimentation to execution. It’s not the flashiest story in AI, but it may prove to be the most economically significant.

Risks, Challenges & What to Watch Out For

Even though agentic AI in regulated domains has more defensibility, it’s not risk-free. Some items to caution:

• Regulatory robustness & evolution: e-invoicing mandates may change, schemas may evolve, new semantic, tax, or audit rules appear. The AI agent must be adaptable and maintainable.

• Explainability & auditability: In regulated settings, you may need to prove why a particular validation was passed/failed. Agentic systems must maintain logs, traceability, and human-in-the-loop oversight.

• Data quality & garbage in, garbage out: If input data is messy, missing, malformed, or tampered, extraction and enrichment may propagate errors.

• Governance, compliance & bias: The system must not introduce bias or incorrect transformations — oversight and governance frameworks are essential.

• Cost & margins: Building a high-quality agent is expensive (engineering, model updates, governance). Firms must ensure sustainable business models.

• Overdependence & vendor lock-in: Organizations may become too reliant; they should architect for portability, fallback modes, and modular upgrades.

Closing Thought

The next phase of automation will reward accuracy, adaptability, and accountability. The firms that survive any AI correction will be those that built their systems on truth, not hype. ‘Trusted Data’ is of paramount importance.

If the AI bubble pops tomorrow, the organisations automating compliance, validation, and enrichment with Agentic AI will keep working; quietly, profitably, and with integrity.

Let’s Continue the Conversation

If you’re exploring how Agentic AI can strengthen data integrity and compliance in your organisation, particularly around e-Invoicing and financial document automation, I’d love to connect and share insights.

Let’s discuss how AI can create resilience, not just headlines.