Building an Applied AI Organization

As businesses increasingly recognize the transformative potential of artificial intelligence (AI), the challenge lies in effectively integrating AI into operations to drive measurable value. Adopting AI and agentic systems—autonomous, goal-oriented AI agents that execute complex workflows—requires a strategic approach to organizational design, talent acquisition, and process transformation. This article outlines how companies can build an applied AI organization to harness the power of AI and agents, drawing on key roles and responsibilities to ensure successful adoption.

Why Build an Applied AI Organization?

AI adoption is not just about deploying new tools; it’s about reimagining how work gets done. Agentic systems, powered by large language models (LLMs) and integrated with APIs and tools, can automate repetitive tasks, enhance decision-making, and unlock new business opportunities. However, without a dedicated structure to align AI initiatives with business goals, companies risk fragmented efforts, misaligned investments, and unrealized potential.

An applied AI organization bridges strategy and execution by fostering collaboration between business and technical teams, ensuring ethical governance, and driving enterprise-wide transformation. Below, we explore the key roles that form the backbone of such an organization and how they contribute to successful AI adoption.

Key Roles in an Applied AI Organization

1. Applied AI Program Leader: Steering Enterprise-Wide Transformation

The Applied AI Program Leader is the strategic visionary who aligns AI initiatives with business objectives. This role partners with C-suite executives to develop adoption roadmaps, oversees the creation of an AI Center of Excellence, and ensures measurable return on investment (ROI).

• Responsibilities:
  • Build and lead multidisciplinary AI teams, including architects, engineers, and adoption champions.
  • Conduct enterprise-wide AI readiness assessments and develop maturity models.
  • Establish governance frameworks for ethics, risk, and compliance.
  • Manage a balanced portfolio of AI initiatives, prioritizing quick wins and long-term transformational projects.
  • Evaluate and select AI platforms and agent technologies that align with enterprise architecture.
• Impact: By providing strategic leadership, the Program Leader ensures AI initiatives deliver tangible business value while fostering a culture of innovation.

2. Applied AI Business Specialist: Reimagining Workflows

The Applied AI Business Specialist focuses on redesigning business processes to leverage AI. Through ethnographic research and process analysis, this role identifies automation opportunities and creates AI-enabled workflows.

• Responsibilities:
  • Shadow employees to document workflows and pain points.
  • Map processes to identify tasks suitable for automation versus those requiring human judgment.
  • Design detailed specifications for AI workflows, including agent capabilities and decision trees.
  • Develop business cases to justify AI investments, quantifying savings and transformational value.
  • Partner with stakeholders for change management and training.
• Impact: This role ensures AI solutions are tailored to business needs, driving efficiency and scalability while minimizing disruption.

3. Agentic Systems Architect: Bridging Strategy and Technology

The Agentic Systems Architect translates high-level AI strategies into technical implementations. This role designs agent orchestration workflows, evaluates tools and APIs, and ensures scalability and performance.

• Responsibilities:
  • Convert process designs into technical requirements and build prototypes.
  • Research and assess agent frameworks, tools, and APIs for feasibility.
  • Monitor advancements in AI capabilities to maintain up-to-date solution mappings.
  • Perform quality assurance (QA) on agent implementations.
  • Design integration patterns for agents and existing systems.
• Impact: By aligning technical solutions with business goals, the Architect ensures robust, scalable AI systems that deliver reliable performance.