12 AI use case prioritization frameworks

Welcome executives and professionals. Enterprises often struggle to identify AI use cases with the highest potential and prioritize them to drive maximum impact.

The wide range of agentic AI, AI agents, and generative AI applications is a blessing and curse, which can make it hard to know where to invest.

Existing frameworks from top firms can help address this.

BCG - Outlines how BCG assesses generative AI opportunities (slides 6-12), factors affecting task automatability, and cost reduction potential.

Framework here.

Deloitte - Details how it qualifies the suitability of existing use cases for agentic AI, and prioritizes agentic AI use cases, including its “Differentiability index.”

Framework here.

OpenAI - Impact/Effort method (page 27) details how customer success teams prioritize AI use cases for enterprises efficiently and effectively.

Framework here.

Google - Uses a matrix to plot potential AI use cases based on expected value, actionability, and feasibility to guide prioritization decisions.

Framework here.

Capgemini - Measures how amenable areas are to gen AI and identifies roadblocks or gaps in adoption to guide delivery (page 14).

Framework here.

PwC - Evaluates AI use cases for value and feasibility (page 8) using industry benchmarks, best practices, and cross-industry experiences.

Framework here.

Anthropic - Shares how AI teams select optimal use cases (page 16), leveraging data, success metrics, and ROI to scale AI strategy.

Framework here.

Gartner - AI Opportunity Radar enables enterprises to map AI ambitions, helping executives explore, prioritize, and commit to use case opportunities.

Framework here.

Microsoft - Shows how CIOs link cost control to value narratives (page 23), drive transformation and earn broader executive buy-in.

Framework here.

WRITER - Agentic AI ROI is a four-part model measuring the real business impact of AI applications across use cases and initiatives.

Framework here.

KPMG - AI investment assessment, factoring hardware, software, manpower, and projected outcomes to guide decision-making.

Framework here.

Scan AI - A 7-step process identifies agentic AI use cases, aligning with core value streams, persona-centric design, and digital footprints.

Framework here.

MORE DETAILED MUST-READS

• Playbooks for AI Leaders (18 playbooks)

• AI Agent Playbooks (16 playbooks)

• AI Agent, Agentic AI Use Cases (2195)

• Agentic AI Case Studies (40 cases)

• AI Strategy Playbooks (16 playbooks)

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