Infinity

Friction to Focus

Bridge the critical gap between understanding AI’s potential and taking effective, low-risk action.

Tags: AI strategy workflow augmentation SEA TOTE activation

AI-Native Strategic Advantage — Framing Questions

  • How do we move from abstract potential to concrete reality?

  • Where is the greatest potential, and how do we quantify it?

The Journey From Friction to Focus (6 steps)

  1. The Art of the Possible

  2. AI-Ready Knowledge Flows

  3. AI Maturity & Readiness Reflection

  4. Workflow Mapping & Prioritization

  5. From Plan to Action

  6. Building the Momentum Engine

Process

  • Module 1: Orientation & The Art of the Possible — set goals and demo a real, value-generating workflow.

  • Module 2: Framing Problems as AI-Ready Knowledge Flows — view challenges through the Friction lens.

  • Module 3: AI Maturity & Readiness Reflection — honest assessment for realistic projects.

  • Module 4: Guided Workflow Mapping & Prioritization — hands-on mapping (9-Box) + SEA heuristic.

  • Module 5: From Plan to Action: Shared State & Resource Planning — clarify who/what/how much.

  • Module 6: Building the Momentum Engine: 30-Day Activation — weekly retros to drive continuous improvement.

1) The Art of the Possible

Levels of Augmentation

  • Level 0 — No Augmentation: Normal work (pen & paper).

  • Level 1 — Assistive Tools: Summarize a transcript & extract tasks (“Fireflies Recap”).

  • Level 2 — Cognitive Support: Build a research report (“Deep Research”).

  • Level 3 — Cognitive Partnership: Compile synthetic docs (“NotebookLM”).

  • Level 4 — Cognitive Dependence: Analyze data for prediction / keep a project plan current.

  • Level 5 — Full AI: Automate an ad campaign (Meta’s “Infinite Creative”).

What examples of augmentation can you think of?

An Equation for Knowledge Work

  • See a Problem → Have a Goal → Best Response (from experience) → Learn a rule (“When x, do y × z, get r.”)

Why it matters: Knowledge Work & Outcomes

  • $15.7T potential global GDP contribution by 2030 (PwC).

  • 75% of value in customer ops, marketing/sales, software eng, and R&D (McKinsey).

  • 6 in 10 workers need training before 2027 (WEF).

  • HBS + BCG (ChatGPT access): +12.2% tasks, 25.1% faster, +40% higher quality; training is crucial.

Value Thesis — Get more of what you value out, for less of what you value in.

Where have you found value working with AI?

Two Objectives

  1. Use tools to think and explore your work.

  2. Document a perspective and plan to integrate AI for strategic advantage.

2) AI-Ready Knowledge Flows

Start with Value (and its parts)

  1. Value: What do you do that’s valuable, and why?

  2. Value Chain: What is your value made of?

  3. Value-Added Activities: How you make the value.

  4. Value Creation: Why people value this.

  5. Value Erosion: What undermines the value.

Exercise 1 — Break Down a Value Chain (worksheet)

Friction → A Signal for Opportunity

Definition: Points where progress slows, stalls, or becomes difficult; not a flaw—a signal for opportunity.
Patterns: Bottlenecks, delays, rework, knowledge gaps, undesirable work, siloed information.

Examples of Friction: CTO—proposal engineering; CFO—HR/finance compliance; CEO—value-based pricing.

Exercise 2 — Map Friction (worksheet)

Value Creation with the SEA Framework

  • Streamline: Reduce effort & complexity → Does this make the work easier?

  • Enrich: Improve quality & insight → Does this make the outcome better?

  • Accelerate: Increase speed & agility → Does this make the cycle faster?

SEA Outcomes (observed): proposals 3d→15m, market reports 6w→7m, pitch decks 12h→30m, proposals 0→80% automation, –50% compliance effort, pricing to value-based, MSA review 0, contract agreement 0, data analysis 20.

Exercise 2 (cont.) — Map Value with SEA (worksheet)

3) AI Maturity & Readiness Reflection

Identifying What is Possible (Data/Knowledge types)

  • Factual, Conceptual, Procedural, Metacognitive.

What are examples of process knowledge in your business?

Identifying What is Feasible (Familiarity & Adoption)

  • Remember, Understand, Apply, Analyze, Evaluate, Create.

How are you/your team augmenting process with AI today?

Mapping Possible × Feasible (skill levels)

  • Lower-order: Recall, Apply, Understand.

  • Higher-order: Evaluate, Analyze, Extract, Alter, Learn, Teach, Perceive, Act, Create.

Exercise 3 — Readiness (grid worksheet)

4) Guided Workflow Mapping & Prioritization — TOTE

Test (T1) → Operate → Test (T2) → Exit; use to decompose knowledge workflows.

Prompt scaffold: I create this value… for this audience… using this value chain… considering this function… in this step… with this structure… Decompose into TOTE cycles.

Best Practices — Designing Effective Systems

  • Clear goals, appropriate tests, flexible operations, explicit exit strategies.

Exercise 4 — Decomposing Workflows (worksheet)

What has worked when designing metrics?

Common Implementation Challenges

  • Goal conflict, feedback delays, measurement issues, motivation maintenance.

Use AI to Discover Best Practices & Challenges — “For [this process], help me develop effective TOTE cycles, consider best practices, and mitigate common challenges.”

Ingenuity & Momentum

  • Motivation · Momentum · Incremental Innovation — reduce barriers; aim for a lovable pilot that proves value quickly.

Ingenuity (definition & behaviors): adapt to uncertainty, make intuitive leaps, construct meaning, reframe problems, communicate nuanced insights.

5) From Plan to Action — Shared State & Resource Planning

Draft Business Case — Scaffold

  1. Executive Summary: problem → solution → expected impact (1–3 sentences).

  2. The Problem (Friction): describe current state; slow/manual/inconsistent/error-prone/siloed?

  3. The Solution (Focused Pilot): what it will do, for whom; emphasize de-risked first step.

  4. Value Proposition & Estimated ROI: quantitative + qualitative benefits (consistency/quality, compliance risk, turnaround time, employee experience, strategic capability).

  5. Stakeholder Perspectives: value for different roles.

  6. Strategic Alignment: how the pilot supports broader company goals.

Stakeholder Perspectives (roles & example questions): Operators, Orchestrators, Executives; plus examples for Head of Sales, Engineering Manager, and the whole team (point of maximum friction).

What would your stakeholders say?

6) Building the Momentum Engine — 30-Day Activation Plan

Leverage AI Augmentation for Strategic Advantage — practical, repeatable framework; focus on real friction → measurable value.

Week 1 — Validate the Framing

  • Share workflow analysis with a future Operator (“Does this capture your experience?”)

  • Identify the single biggest assumption or risk in the pilot plan.

  • Confirm stakeholder agreement on framing & value.

Week 2 — Prepare to Start

  • Update Business Case & Pilot Plan from Week 1 feedback.

  • Confirm pilot users, data/system access.

  • Create a one-pager to share.

  • Define the first, smallest step to test the riskiest assumption.

Week 3 — Execute & Establish Rhythm

  • Execute the first, smallest step.

  • Hold a Weekly Retrospective (30 min): What did we do? learn? do next?

  • Document learnings; decide if the test validated/invalidated the assumption; adjust plan.

Use AI to develop the activation plan — “Use the business case × activation plan scaffold to create the 30-day activation plan.”

Crawl, Walk, Run, Scale — Recap

  • Keep the Value Chain at the center. Start with Friction.

  • Identify SEA opportunities.

  • Systematically reduce friction while maximizing value extraction.

  • Advance maturity via feedback loops to close knowledge gaps and grow familiarity.

A systematic approach to developing AI-native competitive advantage.

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