Introduction

The Six Dimensions

1. Technical Infrastructure

Your technology foundation determines whether AI agents can operate reliably at scale.

What we assess:

• Data architecture and accessibility - Is your data integrated across systems, or siloed in ways that limit what agents can accomplish?

• API readiness and system interoperability - Can agents connect to the tools and platforms they need to complete tasks?

• Computing resources and scalability - Can your infrastructure handle unpredictable workloads and multi-agent coordination?

• Integration capabilities with existing enterprise systems

Why it matters: Agentic AI requires enterprise-grade foundations, not just feature velocity. Agents that perform well in isolated tests often fail when they need to access data from multiple systems, handle concurrent requests, or maintain consistent performance under load.

---

2. Data Readiness

AI agents are only as good as the data they can access and act upon.

What we assess:

• Data quality, completeness, and consistency across sources

• Real-time data availability for agent decision-making

• Data governance policies that enable (rather than block) AI access

• Historical data assets that can inform agent training and context

Why it matters: Many organizations discover their data is messier than they thought only after deploying agents that produce inconsistent or incorrect results. Assessing data readiness before deployment prevents costly rework and protects your reputation.

---

3. Governance & Risk Management

Autonomous agents require new approaches to oversight, compliance, and risk control.

What we assess:

• AI governance frameworks and policies

• Compliance readiness for your industry's regulatory requirements

• Risk assessment processes for autonomous decision-making

• Audit trails and explainability capabilities

• Security protocols for AI systems handling sensitive data

Why it matters: As agents move from assisting humans to acting autonomously, the stakes increase. Organizations need governance frameworks that provide appropriate oversight without creating bottlenecks that eliminate the efficiency gains agents are supposed to deliver.

---

4. Process Maturity

Well-defined, documented processes are the foundation for effective agent deployment.

What we assess:

• Process documentation quality - Are your workflows clearly mapped and up to date?

• Gap analysis between documented and actual practices

• Identification of processes suited for agent automation (repetitive, data-intensive, rule-based)

• Exception handling procedures and escalation paths

Why it matters: Agents need clear instructions and well-defined boundaries. Organizations with mature, documented processes can deploy agents faster and with fewer errors than those where institutional knowledge lives only in employees' heads.

---

5. Workforce Readiness

Success requires your people to be prepared to work alongside AI agents.

What we assess:

• Current AI literacy across the organization

• Readiness for role evolution as agents handle routine tasks

• Leadership preparedness for managing hybrid human-AI teams

• Change management capabilities and organizational culture

• Training infrastructure for ongoing skill development

Why it matters: The most sophisticated AI deployment will fail if your workforce sees agents as threats rather than tools, or if managers don't know how to supervise human-AI collaboration. People readiness is often the dimension organizations underestimate most.

---

6. Strategic Alignment

AI investments must connect to business outcomes that matter.

What we assess:

• Clarity of AI strategy and connection to business objectives

• Executive sponsorship and organizational commitment

• Use case prioritization based on business impact and feasibility

• Success metrics and ROI frameworks

• Long-term vision for the digital workforce

Why it matters: Organizations that deploy AI without clear strategic alignment often end up with impressive technology that doesn't move important business metrics. Starting with outcomes - not technology - ensures your AI investments deliver real value.