Harry Narang.
AI-Native advisor & educator.
AI-Native,
In Real
Work.
Explore Harry’s site
I help leaders make AI part of how their teams work, with practical learning and a clear business purpose.
AI-Native
Advisor
Professionals
trained
AI-Native
Educator
Advisor
Speaker
Change leader

About Me (&)
My Approach
My background is in enterprise transformation. Today, I bring that experience to AI-Native work with leaders and teams.Full biography, clients & gallery ↗
01
Enterprise change, since 2013
I've worked in scaled agile digital transformation since 2013. That experience shapes how I approach change with leaders today.


My background
Enterprise change


Enterprise change, since 2013
My background is in agile product development and lean portfolio management. Since 2013, I've worked on scaled agile digital transformations in enterprises and government organizations. AI-Native work builds on that experience: understand the business, look closely at how work happens, and help people change it.
02
Close to the work
Team coaching keeps the conversation practical. A workflow on the wall tells you more than a polished strategy slide.


My practice
Team coaching


Close to the work
My consulting work includes team coaching and portfolio assessment. Those are useful starting points for AI too. Before changing a workflow, we need to see where work waits, who makes the decisions, and what people need to do their jobs. The people doing that work should help shape the change.
03
Learning people can use
I've trained professionals in enterprise and government settings. Practice gives people a way to bring a new idea into their work.

My practice
Applied learning

Learning people can use
Training is a large part of my work. My existing practice spans agile delivery and lean portfolio management, with workshops for people working inside complex organizations. For AI-Native learning, I want teams to bring a real task into the room, try a different way of doing it, and examine the result together.
04
Leadership sets the direction
A team needs to know which problem matters and who owns the next decision. AI work needs that clarity too.


My approach
Business priorities


Leadership sets the direction
My work in transformation strategy and lean portfolio management connects team activity to business priorities. When we discuss AI, I start there. Which outcome deserves attention? What is getting in the way? A shared answer helps leaders choose where to invest time and gives the team a clear purpose for its first test.
05
Make AI part of the workflow
Find a useful place for AI in work your team already does. Understand the input, then decide how people will check the result.


My focus
AI-Native work


Make AI part of the workflow
AI-Native is an area of my practice focused on how AI changes everyday work. A useful starting point might be a recurring report or a decision that needs better information. We can examine the current steps and design a small experiment, with clear responsibility for reviewing what AI produces.
06
Keep people responsible
Decide what information AI can use and where a person must review its output. Those decisions belong in the workflow.


My approach
Human judgment


Keep people responsible
A useful AI workflow makes responsibility visible. The team should know what data is appropriate to use, who checks the result, and when an issue needs a human decision. Those choices depend on the work and its consequences. They need attention before a small experiment becomes a routine process.
07
Build on what proves useful
Compare a test with the way work happens today. Use that evidence to decide what to improve and what is ready to expand.

What comes next
Your first experiment

Build on what proves useful
An experiment should help you make a decision. Agree what you will measure before the work begins, then compare the result with the starting point. The team may find a useful improvement, or discover that the idea needs more work. Either result gives you a better basis for the next investment.
AI-Native.
In Practice.
Start with the work your team does today. Explore where AI can help, test a useful change, and decide what deserves to grow.

Leadership alignment
Choose a business problem worth solving and agree what a useful result would look like.

Applied team learning
Practice with AI in the context of your team’s work and learn how to review the output.

Workflow coaching
Examine a recurring workflow, decide what should change, and test the revised process.

AI-Native conversations
Give your audience a practical way to think about AI, leadership and the work ahead.

Product decisions
Explore how AI can support research and product decisions, with people accountable for the result.

Portfolio focus
Connect possible AI initiatives to the priorities that already matter to your business.

Responsible adoption
Make data boundaries and human review part of the workflow from the beginning.

Leading the change
Help people understand what changes in their work and where they keep responsibility.

Enterprise experience
Bring a background in enterprise transformation and professional education to the conversation.
Put AI
To Work
Choose the support that fits where you are. Each engagement starts with a conversation about the work you want to improve.Explore consulting ↗Explore training ↗
AI-Native advisory
Direction
Decide where AI belongs in your business. Start with a problem worth solving and agree what a useful first step would look like.
Explore your business priorities
Compare AI opportunities with the effort involved
Choose a workflow to examine
Agree how you will measure progress
Name an owner for the next decision
For leaders deciding where to start or where to focus next.
Team workshops
Practice
Bring a workflow your team uses today. Try AI in that context and examine what changes when people put it to work.
Use examples from your team's work
Build a shared understanding of AI
Practice giving useful context
Compare outputs against a clear standard
Identify where human review is needed
Choose a practical follow-up experiment
For teams ready to learn through work they recognize.
Workflow coaching
Real work
Take a promising idea into a practical test. Work through the steps that change and the evidence you need before expanding it.
Map how the workflow operates today
Check what data the experiment needs
Define the AI and human responsibilities
Review results with the people doing the work
Decide what is ready for wider use
For teams with an opportunity they want to test in practice.
Make Your
Work
AI-Native.
Together.
What would you like to improve? Bring a business challenge or a workflow your team wants to rethink. We can find a useful place to begin.

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In Their
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MORE FROM HARRY
Agility. Experience.
Community.
On a mission to help organizations master agility. Explore Harry’s work in Agile Product Development, Lean Portfolio Management and System Transformation.
- Professionals trained
- 40,000+
- Teams transformed
- 500+
- Portfolios impacted
- 250+
- Companies
- 100+
Hear from Harry’s clients
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