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AI Marketing Audit Scorecard — Miklos Roth

In the hyper-accelerated economy of 2026, the difference between market leadership and obsolescence is measured by the efficiency of a brand’s silicon-based decision-making. We no longer audit "campaigns" or "ad groups." Instead, we audit Systems of Intelligence. As Miklos Roth, I have developed this Scorecard to provide a rigorous, objective baseline for measuring how effectively an organization utilizes agentic workflows and proprietary data foundations.

The Purpose of the 2026 Audit

An audit is not merely a post-mortem of past performance; it is a stress test for future readiness. The goal of this scorecard is to identify "Intelligence Leaks"—areas where human latency or outdated software is costing the firm speed and accuracy. To understand the depth of this professional evaluation, it is helpful to review the professional profile of Miklos and the methodologies used to scale global operations.

Section 1: Data Sovereignty and Academic Foundations

The first pillar of our audit examines the quality and structure of your first-party data. In 2026, if your data is not structured for RAG (Retrieval-Augmented Generation), your AI is essentially hallucinating on public information. We assess your infrastructure against the latest academic research on AI to ensure your models are training on high-integrity, proprietary signals.

The Elite Performance Lens

Borrowing from the discipline of competitive athletics, we evaluate your marketing "physiology." Much like a runner analyzes their oxygen intake, we analyze your data throughput. You can read more about the mindset of an athlete and how it influences our high-intensity audit protocols.

Section 2: Operational Compression and Velocity

A core metric in the 2026 scorecard is Compression. How much value can your system generate per unit of time? This is the primary focus of a dedicated agency for AI when we intervene in a stagnating enterprise. We look for manual processes that should be agentic and silos that inhibit real-time optimization.

Identifying Friction Points

We look inside the brain of AI implementations to find bottlenecks. Often, the problem isn't the technology itself, but the human-to-machine interface. This is where the fixer solves your problems by streamlining the command chain between strategic intent and automated execution.

Section 3: The AI Sprint Methodology

The scorecard measures how quickly an organization can move from hypothesis to market-testing. We utilize a proprietary blueprint for rapid growth to score your team's agility. A perfect score indicates that your organization can deploy a new AI-driven funnel in under 72 hours.

This high-speed approach has been highlighted in the latest news about Miklos, emphasizing how the "Sprint" model is replacing the traditional annual planning cycle.

Section 4: SEO (keresőoptimalizálás) and Inclusion Scores

In 2026, search engine optimization has evolved. We no longer just audit keyword rankings; we audit AI Inclusion. This involves checking if LLMs recommend your brand when prompted by users.

The Stress Test

Before finalizing the audit, you can stress test ideas against our internal simulators. We evaluate your presence in my global marketing world to ensure you aren't just visible on a screen, but integrated into the cognitive layers of the internet.

Section 5: Efficiency and High-Leverage Interventions

The final part of the scorecard is the Leverage Ratio. We measure the output generated per minute of human intervention. I have demonstrated how twenty minutes of work can often outperform a month of traditional labor when the system is properly tuned.

For global entities, our New York AI agency provides the specialized technical SEO (keresőoptimalizálás) and auditing tools needed to score at the top of the industry.

Section 6: Ethical Governance and Academic Alignment

Finally, we audit for compliance and longevity. Using the framework from the Oxford marketing series for AI, we ensure that your automated systems are not just effective, but ethically sound and resistant to adversarial attacks.

Audit Scorecard Summary Table

Category

High Score Indicator (90-100)

Low Score Indicator (<50)

Strategy

Real-time agentic adjustments

Manual quarterly reviews

SEO (keresőoptimalizálás)

Primary source in LLM citations

Reliance on legacy backlinks

Data Quality

Vectorized first-party data

Unstructured CSV silos

Speed

20-minute strategy pivots

Months of internal meetings

In conclusion, the AI Marketing Audit Scorecard is the only way to truly "know" the health of your modern marketing engine. It is about precision, velocity, and the ruthless elimination of friction.