From S.O.S. to AI Strategy: A CxO Playbook for Scaling with Clarity
What’s our AI strategy?” It triggered an S.O.S. What if that urgency could be transformed into a clear, scalable AI framework?
In the last 15 days, I’ve replied to ~3 emails/day — all asking different versions of the same question:
“What’s our AI strategy? How do we go about it? What are other companies doing? What should we do? How can we get started in Agentic?”
While AI is everywhere — in slides, workflows, vendor demos, and org chatter — clarity is often missing. If you just listen to the noise, you might think the world changed overnight.
For some, it did.
For many enterprise CxOs, it’s an SOS call from their boards and bosses.
Pilots without a path to scale = theater.
Scaling without pilot discipline = chaos.
Most companies are stuck somewhere in between.
Here’s a lens I’ve found useful in quiet, high-trust conversations with leaders trying to move from buzz to blueprint:
S — Shape Your Aspiration
There are two ways to start:
➤ Approach 1: Enterprise-Wide View
Great if you’re on a transformation journey. This means imagining your 2030 company — redesigned with AI-native capabilities. Given the scale of AI’s productivity unlock, now is the time to shape that future. But it requires a conviction-backed, long-horizon view.
➤ Approach 2: Pick a Wedge. Pick a Friend.
Perfect if you want to start now.
A wedge is a workflow, domain, or use case — a small door into AI.
A friend is a business partner (CxO, BU lead) who co-sponsors the initiative.
This becomes both a mirror for your ambition and a forcing function for real alignment.
O — Orchestrate Platform, Products, and Partners
Generative and agentic AI is leveling the playing field. Most companies are starting from scratch — and the maturity gap is narrower than you think.
You need to orchestrate three components:
🔹 Platform
Your company’s AI foundation — e.g., your instance of a language model, governance, responsible AI controls, APIs, and infra to scale.
🔹 Products
Use-case solutions like a contract clause extractor, spend optimizer, AI-powered demand planner, or invoice matcher. These must be designed for use, not just deployed for show.
🔹 Partners
Three paths:
Off-the-shelf solutions
AI overlays on existing systems (like Salesforce)
Custom builds for proprietary advantage
All need orchestration — and clear roles.
Don’t analyze and paralyze on the questions below:
Is your data fluid?
Are your workflows modular enough to plug in agents?
Do your teams know what to automate vs. what to hold with human hands?
Nobody has this perfect. You build maturity by starting the orchestration.
S — Scale Everything Responsibly
Starting small is essential. But scaling is where real value unlocks — and where most struggle.
👥 Talent
You need people who can build, integrate, and evolve AI solutions — internally or with partners.
Upskilling is non-negotiable and must happen at three levels:
Executives and leaders
Practitioners and builders
Everyone else
We’ll explore these roles more in a future post.
🏛️ Organization
This is real transformation — not a lab experiment.
Product Management: You need business-led teams working with end users. It’s not about top-down features; it’s about bottom-up needs and fast iteration.
Dynamic Resource Allocation: CxOs must govern what’s working, stop what isn’t, and move resources dynamically.
Workflow Redesign: If nothing about how you work changes post-AI, you haven’t done enough. This may mean redoing contracts, shifting responsibilities, even reshaping org charts.
Shaping aspirations and launching pilots is the easy part.
Scaling without orchestration leads to chaos.
Orchestrating without scaling leaves you in theater.You need all three — Shape. Orchestrate. Scale.
🪞 Use this as your SOS-to-Strategy Mirror
Where is your organization today — and where does it need to be?
S.O.S. isn’t a strategy.
It’s a lens to navigate from reflection → action → architecture.
And like all good signals, it’s only useful if you’re listening.