Alena Shurtakova designs operating models for the AI era – where technology, people, and decision-making collide. Her work focuses on how organizations grow, scale, and change by redesigning the systems that govern execution, accountability, and learning.”
Understanding AI-Enabled Operating Models
Imagine a company as a city: strategy acts as the map, teams form neighborhoods, processes serve as roads, meetings function like traffic, data powers everything like electricity, and rules operate as laws. Introducing AI resembles adding a new infrastructure layer to this city. Without proper planning, it leads to chaos, including confused roles, bottlenecks, and slowed decisions.
Alena’s blueprints address key questions, such as who owns AI-involved decisions, what to automate versus keep human-led, how to reorganize workflows without friction, what to ship in order to avoid installing unused AI tools, and how to scale changes across thousands of employees.
Core Areas of Alena’s Expertise
Alena brings over a decade of experience designing and implementing operating models in complex organizations – well before AI became a central management challenge. Her work has focused on helping organizations grow, scale, and change under a wide range of pressures, including rapid expansion, structural complexity, regulatory constraints, and performance breakdowns.
These include decision-making and governance for approvals and execution, organizational design for roles and teams, as well as workforce systems for staffing and productivity
She helps to turn operating model blueprints into repeatable actions and genuine implementation beyond presentations. Her efforts yield tangible results: reduced meeting waste, clear ownership, accelerated execution, and scaled teams without collapse. This work remains largely invisible externally but drives visible internal outcomes.
Why It Matters
AI projects rarely fail because of the technology. They fail because decisions get stuck, roles are unclear, and execution collapses under scale.
Most operating models were built for stability, not for rapid growth, constant change, or AI-driven decision speed. When organizations try to layer AI onto these structures, they create friction, risk, and wasted investment.
What actually matters is whether the operating model can absorb change: who decides, how fast decisions move, how work is coordinated, and how accountability holds as scale increases. Without fixing these foundations, AI becomes noise rather than leverage.
Credentials and Recognition
Alena has over ten years of experience designing and implementing operating models across three continents. She has worked with organizations ranging from Series C startups to large global enterprises across technology, retail, financial services, utilities, and healthcare.
Her work has supported organizations with up to 100,000 employees, enabling 3× growth and double-digit productivity improvements. More recently, she led large-scale cultural and operating model transformations for a $4B U.S.-based healthcare organization.
