The senior AI partner for CEOs who want to move the whole business.
You have strong executives. They're also running the business you have today. The AI redesign often needs its own parallel track — sustained, senior focus that your operators-in-seat may not be able to give it without dropping the day job. I work with CEOs as a fractional executive partner: a single point of accountability for AI on projects of strategic importance, so the transformation actually lands. Leaner functions, faster execution, higher-quality work, and the cross-functional change that's hardest to drive from any one seat.
Coordination, execution, and analytics collapse into the AI layer. Each function shrinks its surface area and refocuses on its real job.
Cycle times compress across the company. Decisions, content, account plans, customer responses — all move at the speed AI now allows.
Properly contextualized AI lifts the floor and the ceiling at the same time. Fewer disconnected pilots, more compounding output.
The hardest AI use cases sit between functions — and stall without a senior owner. That's the seat this work fills.
Most companies have AI in pockets. Few have someone driving the system.
Every function in your business is being pulled toward AI right now — marketing, sales, support, product, ops, talent. Letting it grow organically is easy. The hard part is making the work compound: a coherent picture of the top use cases, where AI lives in your business, who owns it, how it changes roles, and — importantly — how the same context propagates across functions.
That work needs a senior owner. Not a vendor, not a deck, not a working group. Someone with the operating background to drive the redesign, and the focus to do it inside a defined window.
Running the business you have is a full job for your executives. The AI redesign deserves a focused track of its own, running alongside theirs. The work tends to go faster when someone with dedicated focus is partnering with your leaders on the way through.
This is the seat I help fill — temporarily, collaboratively, deliberately, and only for as long as the work requires.
The shape of an AI-native business when this work lands.
These aren't aspirational. They're the specific outcomes a properly driven AI transformation can produce — and the use cases that need a senior owner to actually prioritize, sequence, and ship.
GTM Brain holding context across the stack
A finely-tuned context layer — strategy, ICP, positioning, customer journey, internal language — that propagates everywhere the AI shows up.
Audiences understood deeply
Rich personas with the attributes, triggers, and plays that drive 1:1 motion. Operationalized, not segmented in the abstract.
AEO visibility
Showing up in AI-powered answer engines (ChatGPT, Perplexity, AI Overviews) when your customers are doing their research. The new SEO, and the new battleground.
A content & account-plan factory
High-quality output produced at scale: account plans, content assets, sales collateral — all aligned to the GTM Brain instead of drifting from it.
Campaign execution at 1:1
Campaigns shaped by the GTM Brain, driving genuine 1:1 messaging across audiences instead of mass-blasted variations.
Customer insight, automatically
Stories, support patterns, and field intelligence synthesized into usable insight — without anyone having to mine the data by hand.
Unified Voice AI across touchpoints
Intelligent voice agents that sound like one brand across support, sales, billing, and talent — high quality, low latency, minimal brand drift.
Sellers equipped with agentic AI
Coaching, content creation, deal navigation, and buyer enablement — agentic capabilities available to your sellers in the moment of work.
Product moving faster
Requirements gathering, planning, and execution accelerated. Less time on overhead, more on the product itself.
A fast diagnostic, then a series of high-impact workstreams.
Most engagements begin with a 2-week diagnostic — objective setting with the executive team, fast learning, use-case mapping, and a clear read on the existing org chart, tech stack, and budget. After that, the work moves into a sequence of workstreams. Some run in parallel, some in series, and the highest-priority foundations (like the GTM Brain) get the most early investment.
Objective setting.
Executive conversation to deeply understand the corporate strategy, the business problems on the table, the goals, and the KPIs the work needs to move.
Assess where your business is.
Benchmark AI maturity against companies further along the curve. Interview leaders function by function to surface where AI is already showing up and where the unmet opportunities live. Most companies underestimate what their own teams already see.
Map the highest-ROI use cases across functions.
Identify specific transformation use cases across marketing, sales, support, product, talent, and operations. Cost, timeline, technology, ROI. The cross-functional use cases — unified voice across touchpoints, agents that span the journey, account plans that pull from every system — are the ones with the biggest payoff and the hardest internal owner.
Review the org chart, tech, and budget.
Map and understand the current resources. Who has the skillset, who needs coaching, where you genuinely need outside contractors. Understand where you've made technology investments and where the gaps are — which ones you can close, and which you can live with.
Build the GTM Brain — the context layer the AI runs on.
Give the AI a structured understanding of your go-to-market: ICP, positioning, competitive context, customer journey, internal language. That context then propagates across the company — from account planning to content to support to sales enablement to AEO. This is what separates an AI-amplified company from a company that just bought a lot of AI tools. Started early, kept current.
Create personalized account plans.
Leverage the GTM Brain to generate tailored messaging and positioning for each prospect and customer you're going after. Develop personalized assets, even videos, that move them to take action.
Stand up Voice AI agents with a unified brand personality.
Voice is the most expensive channel most companies run — and it's where AI is moving fastest. Support, sales, billing, talent: the use cases compound, and each one independently justifies the investment. The harder design problem is the unified one — a consistent brand personality across every voice touchpoint, low latency, high quality, minimal brand drift. Done right, voice agents set the tone for what the whole company sounds like. The right next workstream for your business depends on where the leverage is.
Why me, for this work.
- Two decades across GTM, product, AI, CRM, and sales enablement — fluent in product, sales, CS, and exec rooms
- Recent operator seat: marketing leadership at Thunder
- Has worked at and with the companies setting the AI pace — Salesforce, Amazon Connect, ElevenLabs
- Time working with the consulting firms that sell transformation work — so you'll know where they're worth it and where they're not
- Built for the human side of transformation: org design, decision rights, cross-functional orchestration
The AI redesign isn't really a single-function problem. It's a system-design problem that shows up in every function at once — and the hardest parts (cross-functional use cases, unified voice across touchpoints, the context layer the AI runs on) sit between functions, not inside any one.
Two decades in the rooms where this kind of work gets designed — deep in GTM, with product, around AI — and time working with the consulting firms that sell into this space, so I know where they actually create leverage and where you don't need them. If this is a 10x or 100x opportunity for your business, you want an executive at the helm who's good at the human side of these transformations.
Organizational design. Bridges across departments. Bringing your existing leaders along as thought partners rather than around them. The day-to-day work is architecting solutions, soliciting the right inputs, driving execution, reviewing the work, and orchestrating across the teams who actually do it.
That cross-functional muscle is the part that's hardest to hire from outside — and it's what decides whether the AI work compounds, or becomes another wave of disconnected pilots.
How Thunder built an AI-native GTM.
A short look at what this kind of work looks like from the inside — Carter walking through the AI-native go-to-market motion we built at Thunder.
What this is — and what it isn't.
Each engagement starts the same way: a fast diagnostic and a clear set of named workstreams. From there, the shape evolves with the work. Some wrap when the foundation is in place; many become multi-quarter partnerships as the institutional knowledge compounds. The constant is partnership — I work alongside your CMO, CRO, and other leaders, not above them or around them.
Is
- A single point of accountability for AI on projects of strategic importance
- A defined 2–4 week assessment spike, followed by named workstreams
- Collaborative by default — partnering with your CMO, CRO, and other leaders, not above them or around them
- A parallel track to your existing leadership team's day-to-day work
- Often multi-quarter — institutional knowledge compounds, and that's a feature for your business
- Executive-level access — CEO, leadership team, board if relevant
- A clear handoff at any point — to your team, your hires, or a successor
Isn't
- A signal that your existing executives aren't strong enough
- A directive seat that bypasses your leaders
- A vendor-aligned recommendation engine pointing at one AI stack
- A staff-augmentation arrangement to run pilots
- A substitute for the hard internal conversations leadership needs to have
The AI redesign is happening anyway. Better to lead it.
A 30-minute call to talk through where AI lives in your business today, where the pressure is coming from, and whether this kind of engagement fits the work in front of you.
Book a 30-minute intro call