Physical AI & Industrial Intelligence GTM Leader with 18+ years architecting revenue at the intersection of Agentic AI, OT/IT convergence, and Industry 4.0 — from the factory floor to the boardroom.
▸ Available for VP GTM · SVP Revenue · CRO roles in Physical AI & Industrial IoTBefore Physical AI had a name, I was doing it. My earliest enterprise work put me inside OT environments — plant floors, SCADA systems, DCS architectures — long before the industry consensus that AI could operate reliably in the physical world. That early exposure gave me something most GTM leaders in this space simply don't have: genuine OT fluency.
The through-line of my career has always been the same problem: brilliant industrial technology with no commercial story. Engineers who could build systems that predict equipment failure, optimize energy consumption, or autonomously adjust production parameters — but couldn't translate that capability into a narrative that moved a VP of Operations or a CFO to sign. Bridging that gap is my superpower.
Today I operate at the exact convergence of Agentic AI, Industrial IoT, and OT/IT infrastructure — building the GTM architectures, category narratives, partner ecosystems, and sales motions that transform Physical AI platforms into scalable revenue engines. I'm looking for my next stage: a VP GTM, SVP Revenue, or CRO seat at a company building the industrial AI infrastructure of the next decade.
Building end-to-end go-to-market strategies for Physical AI platforms — ICP definition, category narrative, sales motion design, and revenue architecture from zero to scale in industrial markets.
Bridging the historic divide between Operational Technology and Information Technology — building narratives and commercial motions that resonate with both plant floor OT buyers and enterprise IT decision-makers.
Translating Agentic AI capabilities — autonomous inspection, predictive operations, real-time process optimization — into ROI frameworks and commercial narratives that drive enterprise industrial buying decisions.
Designing and executing IIoT revenue programs across manufacturing, energy, and oil & gas — from first POC through full platform deployment and partner-sourced pipeline expansion.
Elevating OT security and AI reliability into board-level conversations — creating the "cyber-physical resilience" narrative that unlocks CISO access, increases deal size, and differentiates from pure analytics vendors.
Establishing new Physical AI and Industrial IoT categories through narrative architecture, partner ecosystem development (SIs, OEMs, hyperscaler co-sell), and industry analyst engagement.
Leading end-to-end GTM architecture for a Physical AI platform targeting industrial, energy, and manufacturing sectors. Designing category entry strategy integrating Agentic AI agents, edge inference, and OT/IT convergence into a unified commercial motion.
Inherited an unstructured GTM motion with inconsistent quota attainment and undefined ICP. Rebuilt the entire commercial architecture around Physical AI and OT/IT convergence, achieving $40M+ ARR growth in 30 months.
Led the technical commercial arm of an Edge AI platform targeting industrial automation and smart factory segments. Built ROI frameworks and solution architectures that translated complex AI capabilities into plant floor buying decisions.
Launched an IoT platform from zero commercial traction into discrete manufacturing and oil & gas verticals. Built the foundational GTM motion — ICP, messaging, partner program, and sales playbook — that the organization scaled for years after.
Inherited a Physical AI and Industrial IoT platform with strong engineering depth but zero commercial traction. The ICP was undefined, the sales team lacked OT fluency, there was no category narrative, and the partner ecosystem was nonexistent. Quota attainment was below 60%.
Every metric improved. The GTM rebuild didn't just fix quota attainment — it established a repeatable, scalable commercial engine that the organization could grow on for years.
"Physical AI is not sold — it is adopted. The GTM leader's job is to reduce the distance between a plant manager's instinct and an AI platform's capability. When that gap closes, the revenue follows."
— Muhammad Yunas
The convergence of Agentic AI, Industrial IoT, and OT/IT infrastructure is reshaping global manufacturing, energy, and operations. The GTM leaders who understand both worlds will define the winners.
Request Full Article →A formal strategic memo outlining market context, competitive landscape, 5 GTM imperatives, and resource implications for Physical AI category leadership in 2026–2027.
Request Document →A detailed practitioner case study documenting ICP redefinition, category narrative architecture, sales motion redesign, partner ecosystem development, and measurable results across 30 months.
Request Case Study →
Agentic AI moving from pilot to production in industrial environments is the defining GTM challenge of 2026. Most enterprise buyers understand the concept — very few have a clear path from POC to operating at scale across a plant floor. The companies that solve this with a structured, OT-first commercial motion will own the category.
Alongside that, the cyber-physical resilience conversation has reached board level — and most Physical AI vendors are still treating it as a technical footnote. That's a massive GTM opening for any company willing to lead with resilience alongside autonomy.
And finally: the OT/IT convergence window is closing faster than most realize. The industrial buyers who are actively evaluating Physical AI platforms today will make consolidation decisions in the next 18–24 months. The companies that build GTM leadership now will be the ones writing the category definition. The rest will be integrators in someone else's ecosystem.
I'm available for VP GTM, SVP Revenue, and CRO conversations at high-growth Physical AI, industrial autonomy, and Industrial IoT companies. If you're building the industrial AI infrastructure of the next decade — I want to talk.