Your Crawl, Walk, Run Roadmap to Algorithmic Advantage

Severin Sorensen
4 days ago
5 min read

The broad, foundational understanding that AI exists is now a universal truth of modern enterprise. The question now becomes: "How, specifically, do we harness it to create immediate value and secure our long-term competitive edge?"

The gap between awareness and execution is where market leadership is won or lost. To navigate this new terrain, we recommend a Crawl, Walk, Run approach.

Stage 1: Crawl - Mastering the Browser-Based Prompt

The "Crawl" stage is about democratizing access to AI and building foundational fluency within your workforce. This phase centers on using readily available, browser-based Generative AI tools (like a standard, paid-tier large language model) to solve simple, high-frequency, low-stakes problems. This is where employees learn to interact with AI as a digital "thought partner" or "co-pilot."

Common Use Cases: The 10x Productivity Boost

Executive Summary Generation: Inputting a 50-page board report or a dense compliance document and instantly generating a two-paragraph executive summary. The value: Massive time savings for senior leaders and analysts.
First-Draft Content Creation: Generating initial drafts for non-critical communications such as internal memos, social media posts, or boilerplate email responses. The value: Eliminates the "blank page syndrome" and accelerates output.
Basic Data Simplification: Pasting unstructured survey responses or customer feedback and asking the model to categorize key themes and sentiments. The value: Unlocks immediate qualitative insights without needing specialized tools.

Unique Use Cases: Unlocking Creative Capacity

Reverse-Engineering Competitor Messaging: Feeding the AI a competitor's press release, product copy, and investor deck, then asking it to identify their core strategic assumptions and potential blind spots. The value: Agile, real-time competitive intelligence.
"Devil’s Advocate" Brainstorming: Asking the AI to challenge a new business strategy by forcing it to adopt a hyper-critical, worst-case-scenario persona. The value: Stress-testing strategic decisions against an unbiased, persistent critic.
CEO Mandate for Crawl: Establish an internal "AI Sandbox" with clear, responsible use guidelines. Focus on making AI accessible to all. The value: individual productivity by 20% in repeatable tasks.

Stage 2: Walk - Creating Custom GPTs and Departmental Intelligence

Once your organization is fluent in the art of prompting, the "Walk" stage begins. This involves moving beyond a general-purpose model to create Custom Generative Pre-trained Transformers (GPTs). These are specialized AI tools trained, configured, and governed by your internal data, rules, and use cases. This is the first step toward creating proprietary, institutional AI capability.

Custom GPTs, or similar departmental AI applications, become the intellectual property of a specific function (e.g., Marketing, Legal, HR), enabling higher-value, more consistent work.

Common Use Cases: Institutionalizing Knowledge

Internal Knowledge Agent: A GPT trained only on the company's full corpus of internal documents like product specifications, compliance manuals, HR policies, and historical client meeting notes. The value: Instantly answers employee questions with contextually accurate, internal-only information, drastically reducing time spent searching for data.
Brand Voice & Tone Generator: A GPT trained on all successful, on-brand marketing materials. Marketers use it to generate copy that is guaranteed to adhere to the company's precise voice, style guide, and legal disclaimers. The value: Ensures brand consistency at scale while maintaining legal guardrails.
The M&A Diligence Assistant: A GPT fine-tuned on past merger and acquisition legal documents, instantly flagging discrepancies or unusual clauses in new target company contracts. The value: Accelerates due diligence and mitigates contractual risk.

Unique Use Cases: Building a Competitive Moat

"Why We Won/Lost" Analyzer: A GPT that ingests all sales call transcripts, CRM notes, and proposal documents for the past year, generating a quantitative and qualitative report on the top three factors driving a win or loss for a specific product line. The value: Turns unstructured sales data into actionable, strategic intelligence for product and sales leadership.
Scenario Planning Simulator: A GPT configured to run simulations on supply chain disruptions or new regulatory changes based on historical company data. Executives input a specific risk factor, and the GPT generates tiered, company-specific response plans. The value: Proactive risk management and enhanced organizational resilience.

Stage 3: Run - Deploying Autonomous Agentic AI

The "Run" stage represents the true algorithmic transformation of the enterprise. Here, the organization deploys Agentic AI; complex systems that go beyond responding to a single prompt. An agent can perceive its environment, set a multi-step plan, execute tasks using various tools (APIs, databases, software), reflect on its performance, and self-correct until a complex goal is achieved. This is AI as an autonomous project manager and is the phase of systemic change, automating entire workflows, not just individual tasks.

Common Use Cases: End-to-End Automation

Automated Sales Lead Qualification & Scheduling: An Agent monitors incoming leads from all sources (web forms, LinkedIn, email). It independently researches the company and contact, qualifies the lead against a defined ideal customer profile, sends a personalized follow-up email, and books the first meeting directly onto the sales rep’s calendar. The value: Zero-touch pipeline management and immediate response times.
IT Service Desk Resolution: An Agent monitors the internal IT ticketing system. For a new ticket, it analyzes the issue, searches the knowledge base, accesses system logs (via API), attempts a series of scripted fixes (e.g., password reset, cache clear), and only escalates to a human technician if all automated attempts fail. The value: Drastic reduction in Level 1 support costs and faster resolution times.
Supply Chain Disruption Mitigation: An Agent monitors real-time global logistics data and weather reports. When a disruption (e.g., a port closure) is detected, the Agent automatically identifies all impacted orders, calculates alternative shipping routes, drafts new delivery timelines for customer service, and initiates a procurement request for alternative suppliers. The value: Proactive, near-instantaneous business continuity.

Unique Use Cases: The Next Frontier

Algorithmic Strategic Foresight: An Agent continuously monitors a vast spectrum of data such as venture capital funding rounds, academic research papers, regulatory filings, and online sentiment, to identify emerging technology and market shifts that could disrupt your core business in the next 3-5 years. It then generates a prioritized briefing deck for the executive team. The value: Outsourced, perpetual strategic intelligence.
The Dynamic Talent Agent: An Agent that monitors key employee metrics (performance, project history, engagement survey data) and external market data (competitor job postings, salary benchmarks). When a specific retention risk is flagged for a high-value employee, the Agent automatically suggests a personalized intervention plan, which could range from a customized training path to a preemptive compensation review. The value: Proactive talent retention and succession planning.

The Algorithmic Enterprise: The Ultimate Competitive Differentiator

The journey from AI awareness to Agentic execution is an iterative feedback loop where the lessons from the "Crawl" stage inform the governance of the "Run" stage. The greatest danger is adopting AI without a structured, intentional plan.

For the modern business leader, your competitive advantage will no longer be determined solely by your data, your capital, or your IP. It will be defined by the velocity and sophistication with which you can convert institutional knowledge into autonomous algorithmic action. Embrace this roadmap, empower your teams to climb the AI maturity curve, and transform your enterprise from a consumer of AI into an unstoppable, self-optimizing algorithmic enterprise.