For teams
Support for leaders who need AI to become part of real operating practice: use-case discovery, workflow redesign, team enablement, trust measurement, and adoption rituals.
AI adoption research, strategy, and rollout
Jyothi Venkat AI Studio
I help product and research teams turn AI experiments into trusted workflows through adoption research, workflow design, training, and practical AI systems.
20 years
Research, strategy, and engineering
0 to 1
Research teams, workflows, and AI systems
Global
OKX, X / Twitter, Yahoo, Unilever, Clorox
What this domain is for
A focused home for AI adoption, research transformation, and public AI builds.
This site brings together the AI-specific parts of my work: advisory services, hands-on systems, research operating models, and writing about how teams actually adopt AI.
For builders
Examples of the systems I have shipped or documented, including research agents, persona tools, knowledge bases, workflow monitors, and AI-native research architecture.
Services
Practical support for moving from AI pilots to durable team workflows.
Adoption research
Find where AI actually fits.
Map behaviors, trust barriers, unmet needs, and high-friction work so AI investments are grounded in how the team operates.
Workflow design
Turn use cases into working systems.
Redesign handoffs, review points, decision rituals, and quality checks so AI becomes part of how work gets done.
Enablement
Train teams around real work.
Create practical training, role-specific playbooks, prompt patterns, and adoption rituals that help teams use AI with judgment.
Experience evaluation
Measure usefulness and trust.
Evaluate AI workflows against confidence, reliability, comprehension, decision quality, speed, and repeat usage.
Research transformation
Modernize the research operating model.
Help research teams adopt AI responsibly across synthesis, repositories, reporting, participant workflows, and stakeholder communication.
Fractional and advisory
Add senior judgment without a full-time hire.
Support leaders as a fractional, interim, or advisory partner for AI rollout, product strategy, and research transformation.
Operating model
Useful AI adoption is a behavior change project with technical fluency.
Most AI programs fail when they stay at the level of tool access and generic prompt training. The work has to connect human behavior, risk, incentives, workflows, and system design.
01
Diagnose the current workflow.
Interview, observe, and map how work happens today, including where AI can help or harm.
02
Design the future workflow.
Define use cases, guardrails, handoffs, human review points, and adoption rituals.
03
Train, launch, and measure.
Roll out with practical enablement and measure usefulness, trust, quality, and repeat usage.
Selected work
Public builds and frameworks from the AI research practice.
Research ops
UX Research OS
An end-to-end research operating system with AI agents for competitive analysis, brief generation, synthesis, and tracking.
Open project
Architecture
AI Native Research Architecture
A systems view of how research teams can turn evidence into product action with AI-native workflows.
Open projectAvailable now