Find the Signal
Map the AI landscape, data readiness, and organizational gaps before making a single investment.
What Happens in This Phase
- Stakeholder interviews across leadership, engineering, and operations to surface competing priorities and hidden assumptions
- Data landscape mapping: what exists, what is accessible, what is reliable — and what gaps will block AI adoption
- AI capability audit: current tools, integrations, vendor contracts, and internal skill gaps across the organization
- Competitive analysis: where peers are investing, what is producing returns, and where the market is heading
- Challenge articulation: naming the real problems behind the AI interest, not just the symptoms leadership reports
What Gets Uncovered
Misaligned Investments
Budget flowing into initiatives that sound strategic but lack clear business outcomes or technical feasibility.
Hidden Data Assets
Existing data sources that could accelerate AI initiatives but sit untapped in siloed systems or legacy platforms.
Organizational Gaps
The distance between AI ambition and execution capability — in skills, processes, and decision-making structures.
Vendor Noise vs. Reality
Which vendor claims hold up under scrutiny and which are marketing dressed as strategy. Honest capability assessment.
AI Discovery Checklist
20 questions every enterprise should answer before starting an AI initiative. Covers strategy, data, talent, governance, and investment readiness.
Ready to Find Your Signal?
Share your AI challenge. The first conversation is always about understanding where you stand — not selling a solution.