Forms, retired.
What if applying for a government service was just a conversation? I led the launch of the first transactional AI assistant plugged directly into government systems. People chat, and the application gets submitted.
For over a decade I've shaped the digital services people rely on to live, work and travel in Dubai. Today I lead product for platforms that handle millions of transactions a year, and I'm betting on AI that doesn't just answer questions, but actually gets things done.
I started in Cairo in 2001, designing and building websites. Then I ran the projects. Then the programs. Then the operations behind a government platform used by millions. Then the product itself.
That path shapes how I work. I know what a screen needs to feel like, what a program needs to land on time, and what a system needs to survive a busy Monday morning. So I build products that work on launch day and keep working every day after.
Today I'm Director of Product Management at emaratech, leading a team of 12 across product and quality. My MBA research looked at how AI and big data drive innovation and operational excellence. My day job is proving it in public services.
"The best government service is the one you barely notice. You say what you need, and it's done."
What if applying for a government service was just a conversation? I led the launch of the first transactional AI assistant plugged directly into government systems. People chat, and the application gets submitted.
I lead how a 200+ service government platform is delivered and operated, reshaping it while it keeps serving millions of people without missing a beat.
Behind every simple service is a web of agencies. I spearheaded a service integration hub that lets them work together, so the customer never has to stitch it together themselves.
A pivotal part of taking services fully digital under Dubai's paperless strategy, from the customer journey through to the back office.
Automated back-end processing so staff spend time on judgement, not repetition, and cleaned up the data underneath so decisions rest on something solid.
Supported service delivery for border control and smart gates at one of the world's busiest airports, where every second at the gate counts.
Part of the teams behind Best Entity Achieving Dubai Plan (2021), Best Entity in Efficiency and Governance, and the grand award for Leading Government Entity, with public satisfaction between 80 and 90%.
Government is complicated. The experience shouldn't be. Every roadmap I build starts from what someone is trying to get done, and works backwards.
AI is exciting. Shorter queues, faster approvals and fewer errors are the point. I measure new tech by the business and customer impact it delivers.
The best teams make good calls when I'm not in the room. I invest in empowered teams, and I mentor the next generation of product leaders.
You may have seen our work showcased on global stages like GITEX.
Short essays by me on building public services people barely notice, measuring AI honestly, and leading product teams.
Most government forms ask people for things the government already knows.
Your name. Your date of birth. Your address. The number on the ID card that was issued by the same government now asking you to type it in. We have built a whole discipline around making forms easier: clearer labels, smarter validation, fewer screens. All of it helps. But it treats the form as a given, and the form is usually the problem.
When my team launched an AI assistant that lets people submit a government application entirely through conversation, the headline number was the time it took: down from 14 minutes to 2. What made that possible wasn't clever language technology. It was a change in the question we were asking. We stopped asking "how do we make this form easier to fill in?" and started asking "what do we actually need to hear from this person that we don't already know?"
The answer is almost always: very little.
Before redesigning a form, I now ask three things.
What's left after those three questions is usually a short conversation, not a form. And a conversation is how people naturally explain what they need.
None of this is a design problem alone. Prefilling data means integrating systems. Verifying at the source means agreements between entities that each own their own data and carry their own risk. I've spent years on exactly that kind of work, including a service integration hub that connects more than 40 government entities, and the technology is rarely the hard part. Trust is.
That's why I'd encourage any team to start small. Pick one high-volume service. Remove the fields you already know. Measure completion time and error rates before and after. The results make the case for the next step far better than any strategy document.
The best government service is the one you barely notice. You say what you need, and it's done.
Forms were a reasonable answer when systems couldn't talk to each other. Now they can. The question for every public-sector product team is no longer how to design a better form, but how to need one less often.
What's the most unnecessary field you've ever been asked to fill in? I'd love to hear it.
The first number everyone asks about an AI assistant is how many people used it. It's the least useful number we have.
Usage tells you people were curious, or that you promoted it well. It doesn't tell you whether their lives got easier. An assistant can have millions of conversations and still leave people stuck, confused or quietly returning to the old channel.
When we launched an AI assistant that lets people complete government applications through chat, we had to decide what "working" meant before launch day, not after. Here's the framework I use now, and recommend to any team putting AI in front of the public.
The primary measure is completion, not conversation. Of the people who started a task with the assistant, how many finished it? And how long did it take compared with the channel it replaces?
For us, the headline was time: 14 minutes by form, 2 by conversation. But time only counts if the task is actually completed. A fast conversation that ends in "please visit a service centre" is a failure dressed up as efficiency.
This is the guardrail. What share of applications submitted through the assistant are later rejected, returned for missing information or corrected by staff?
If speed rises but rejections rise too, you haven't removed work. You've moved it to the back office, and made the applicant wait longer for a worse answer. I'd rather launch slower with a rejection rate at or below the old form's than launch fast and quietly overload the team behind the service.
The third layer is the one most dashboards miss. How often do people ask for a human? How often do they abandon mid-conversation? What do they say in satisfaction surveys after completing a task?
People forgive a new channel for being new. They don't forgive it for wasting their time or making them feel unheard. Trust is slow to build and fast to lose, especially in government services, where people often have no alternative provider.
The most important rule is the simplest: never report these numbers alone. Speed without quality, or quality without trust, invites a team to optimise one number at the expense of the others.
Before launch, agree a target for each layer, and the number that would make you worried. For us, the warning sign would have been a rejection rate above the old form's baseline. That one number would have outweighed any growth in usage.
Cost per application matters too, and it will follow. But leading with cost sends the wrong signal to the team, and to the public. Lead with outcomes for people, and the savings arrive as a consequence.
If you're measuring an AI service today, which of the three layers is the hardest to track? I suspect it's trust.
Every government service is designed twice: once by the people who run it, and once by the person trying to use it. Too often, only the first design gets written down.
Inside an organisation, a service looks like a process. There's an intake step, a verification step, an approval, a payment, an issuance. Each step has an owner, a system and a rule behind it, and every one of them is there for a reason.
From the outside, the same service looks completely different. It looks like a parent trying to renew a document at 10pm, unsure which photo is accepted. It looks like a small business owner visiting three offices because each approval lives with a different entity. The process is logical. The experience is exhausting.
One of the most reliable patterns I've seen in public services is that the customer journey mirrors the organisation's structure. Separate departments become separate steps. Separate systems become separate logins. Separate entities become separate visits.
Nobody designs it that way on purpose. It happens because each team optimises what it owns. The result is a journey where every step works and the whole still fails.
That's why, when I build a roadmap, I start from what someone is trying to get done, and work backwards to the systems. Not the other way round.
A few habits make the difference.
The hardest fixes are rarely on the screen. Removing a visit might mean integrating with another entity. Removing an upload might mean verifying a document at its source. Contributing to a fully paperless service, and later to a hub linking more than 40 government entities, taught me that back-end decisions shape front-end experiences more than any interface does.
So when someone asks whether a piece of integration work is "technical" or "customer-facing", my answer is: both. If it removes a step for the person, it's the most customer-facing thing you'll ship all year.
Government is complicated. The experience doesn't have to be. Starting with the person is how you keep the complexity on your side of the counter, not theirs.
When did you last see a journey from the outside? It's worth doing this month.
The most important skill I've learned as a product leader isn't saying yes to the right things. It's saying no to good things, and keeping the relationship intact afterwards.
Every roadmap is a set of choices about what not to do. Teams are finite, releases are finite, and every "small addition" is paid for by something else, usually quietly. The danger isn't the big, obviously wrong request. It's the reasonable one, from someone senior, arriving at the worst possible moment.
A flat no, even a correct one, tends to go badly. The person asking hears that their problem doesn't matter. They escalate, or they find a workaround, or they simply stop bringing problems to you. You win the decision and lose the partner.
Over the years I've landed on a simple rule: a good no always carries three things.
Before any of that, ask why. What problem is behind the request? What happens if it isn't solved this quarter? Often the answer changes the conversation completely. The feature they asked for turns out to be one way of solving something you can solve faster, or that's already planned under a different name.
Saying no well is also how you protect your team. A team that absorbs every request never finishes anything properly, and people burn out on work that was never going to matter. When a leader holds the line, with reasons and respect, the team learns that focus is allowed.
It's also a skill I try to build in the product managers I mentor. The best ones don't avoid hard conversations. They walk in with the trade-off already mapped, an alternative in hand and a date they can commit to.
People accept no far more easily than they accept being left without a plan.
What's the best no you've ever received? The ones done well are rarer, and more memorable, than we think.
From keeping a major government platform running to deciding where it goes next. Operations taught me what breaks; product lets me fix it at the root.
Large-scale programs from the first bid to final handover, and designing solutions that turned a customer's pain points into something they could deploy.
My first product role, then consulting and professional services for software clients on two continents.
Where it started: designing and building for the web, and learning that good craft still needs a good plan.
MBA, University of Gloucestershire, with research on AI and big data in innovation and operational excellence · Level 7 Diploma in Executive Management, Qualifi · Diploma in Project Management, University of Cambridge · B.Sc. Engineering, Ain Shams University
A working concept: renew a permit in a fictional city just by chatting. As you talk, the 14-screen form it replaces fills itself in, mostly from records you never have to retype.
Try the demoAn impact calculator for leaders. Enter a service's volume and timings, and see the hours returned to the public, the staff capacity freed, and a summary ready to share.
Try the calculatorList the steps of any public service. The X-ray flags where people get stuck, from repeat data entry to counter visits, and sketches a simpler journey.
Run an X-rayScore a backlog with RICE, see it ranked and mapped from quick wins to money pits, and get challenged on the numbers that look too good to be true.
Open the studioThe questions I ask when I mentor aspiring product managers, with what I listen for in each, a 3-minute timer and feedback on your answer.
Start practisingRenew a permit in a fictional city just by chatting. As you talk, the 14-screen form it replaces fills itself in. Try it below.
Home business permit renewal, the traditional way: one screen per question.
Pick a service size or enter your own numbers. The calculator shows what moving applications from forms to conversation gives back to people, and to the teams behind the service.
List the steps a person goes through today. The X-ray shows where the friction hides, and what a simpler journey could look like.
The quick scan uses simple rules to spot common friction, so treat it as a starting point for a conversation, not a verdict.
Score a backlog with RICE: reach, impact, confidence and effort. The studio ranks it, maps value against effort, and questions the numbers that look too good to be true.
I mentor aspiring product managers, and these are the kinds of questions I like to ask. Pick one, answer it as you would in the room, and get feedback on how you structured your thinking.
One strong answer, not the only one. Try answering first, then compare.
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AI in public services, a product team ready to scale, a stage that needs a speaker, or someone to mentor. I'd love to hear what you're working on.