Tuesday, June 30, 2026

What I Learned Judging 20 Teams at the Beyond Tomorrow Hackathon 2026



June 20 and 21, 2026 will stay with me for a while, not because I was up on a stage or delivering a keynote, but because I got to sit on the other side of the table this time. I was a Judge at the Beyond Tomorrow Hackathon 2026.


After years of architecting enterprise solutions, leading digital transformation programs, and solving real use cases and business problems with AI, stepping into a judge’s chair felt like coming full circle. It gave me a front row seat to innovation in its rawest, most honest form, where bold ideas meet limitless imagination, before anyone polishes them for a boardroom.

Sometimes the best seat in the house isn’t on stage. It’s behind the judge’s desk.

A Global Innovation Playground


The numbers alone tell you this wasn’t a small affair. The Beyond Tomorrow Hackathon 2026 pulled in developers, AI practitioners, researchers, and startup builders from every corner of the world, all tackling real problems across AI, healthcare, cybersecurity, sustainability, Web3, fintech, and smart automation.



5,830+ global submissions
Participants from 52 countries
42% working professionals, alongside students and researchers
80 finalists
20 judges on the review board
Thousands of innovators, one shared goal: build something that matters

Innovation really doesn’t carry a passport.

My Two Days, In Numbers


I spent close to eight hours judging across the two days, a little over five hours on Day 1, and around three on Day 2. Every team had a dedicated meeting slot and an assigned domain expert. Since my background is in Enterprise AI, Digital Transformation, Intelligent Systems, and Retail Business Solutions, I was matched with projects that played to that.

In total, I evaluated 20 teams, 15 with five members and 5 with six, which meant I spent those two days talking to 105 innovators. Each session ran a tight 15 minutes, 10 for the presentation and demo, and 5 for technical Q&A. The organizers kept things running like clockwork, which made even back to back sessions feel smooth rather than rushed.

It Genuinely Felt Like a Global Innovation Hub


What stayed with me wasn’t just the technology, it was who was building it. Over those sessions I spoke with AI engineers, application developers from India, postdoctoral researchers from Spain and the UK, PhD scholars from Germany, researchers from the University of South Florida, startup founders, and a wave of emerging innovators just hungry to solve something real.

For a few hours, it felt like I’d stepped into a global innovation hub where every conversation handed me a new way of looking at a problem. As the saying goes, iron sharpens iron, and being surrounded by that much curiosity pushed me to ask sharper questions myself.

The Retail Innovation That Actually Made Me Pause


I’ve sat through a lot of “AI for retail” pitches over the years, and most of them stop at recommendations and chatbots, useful, but not exactly new ground. One team broke that pattern.

They built what I’d call a shelf intelligence and smart replenishment system, an AI layer that doesn’t just talk to customers, it watches the store itself. Using computer vision on shelf cameras combined with a demand forecasting model, the system tracks real time shelf availability, flags misplaced or low stock items before a customer notices, predicts demand spikes a few days out using sales and seasonal patterns, and automatically routes restocking tasks to the nearest available store associate, prioritized by urgency. Vendor delivery windows feed straight into the same dashboard, so a manager can see, at a glance, exactly what’s running low, what’s already on a truck, and where their team’s attention is needed most right now.

What impressed me wasn’t the AI itself, it was how operationally grounded it was. This wasn’t a demo built to look good on stage, it was built to survive a Monday morning in an actual store. Here’s roughly how their prototype dashboard looked when they walked me through it:


A live shelf availability score, a forecast versus actual sales chart, real time vision triggered alerts, and a prioritized task queue for store associates, all in one console. It’s the kind of tool that quietly saves a store manager two hours a day rather than trying to wow them with a flashy chatbot. That’s the kind of retail innovation I find genuinely exciting, not reinventing the wheel, but making the wheel turn smoother.

SensEase: The Project That Stayed With Me Longest


If the retail project impressed me on the operations side, SensEase impressed me on the human side.


It’s a multi tenant mental health platform built for educational institutions, and what struck me was how seriously the team treated it, not as a wellness diary app, but as enterprise grade infrastructure connecting students, counselors, and administrators in one secure ecosystem. Students get a private space for AI assisted journaling and standardized assessments like PHQ-9 and GAD-7, along with anonymous peer support.

 Counselors get a real dashboard with appointment management, patient analytics, and encrypted video sessions. Administrators get aggregated, anonymized trends to actually plan resource allocation across campus. Under the hood, they’d built it properly too, React and Vite on the frontend, a Node and Express backend, Supabase with strict row level isolation to keep one college’s data completely separate from another’s, and real time messaging through Socket.io, all wrapped in cookie based JWT authentication that’s rare to see done right in a 48 hour build. For a hackathon prototype to take student mental health data this seriously, architecturally and ethically, was honestly one of the more reassuring things I saw across both days.

Judging Was Never Just About Scoring


People assume judging is mostly assigning numbers. It isn’t. Every score I gave came after weighing problem relevance and impact, innovation and creativity, technical implementation, feasibility and scalability, user experience, presentation, and future potential, and behind every one of those numbers was real respect for the late nights and rewrites it took to get there.

Innovation Has No Boundaries


If there’s one thing those two days made obvious, it’s this: innovation doesn’t belong to a country, a university, or a company. It belongs to whoever’s willing to ask, “what if we did this differently?” Watching students debate LLM architecture, researchers walk through AI driven healthcare tools, and founders solve operational bottlenecks gave me real confidence that the future is in capable hands.

More Than a Competition


This event connected academia with industry, researchers with practitioners, students with experienced professionals, and ideas with the possibility of becoming something real. That’s exactly what a healthy innovation ecosystem looks like.

A Proud Moment



One highlight I’ll hold onto: receiving the Certificate of Recognition and the Impact Letter from the Beyond Tomorrow Summit team for my contribution as a judge. The certificate is a nice keepsake, but what I’ll actually remember are the conversations, the ideas, the debates, the moments where a team’s eyes lit up explaining their solution.

To Every Team


By the time this reaches you, results may already be out. To the 20 teams I had the privilege of judging, and to every innovator across this event, congratulations, win or not. Great innovations are rarely built overnight, they’re built one iteration at a time. Keep building, keep experimenting, keep questioning. The world needs more problem solvers.

Thank You


A heartfelt thank you to the Beyond Tomorrow Summit organizing committee for trusting me with this role. Building a platform that brings together thousands of innovators, researchers, and entrepreneurs from across the globe takes real vision and commitment. Thank you for letting me be a small part of it.

Here’s to building a future where technology doesn’t just solve problems, it creates possibilities.

Until the next innovation challenge, keep building beyond tomorrow. 🚀 

Monday, June 29, 2026

Why Agentic AI Needs Leaders, Not Just Algorithms — A Personal Research Journey

 Let me be upfront about something.

I received an award back in June 2025. And I am only sitting down to write about it now, in June 2026 . Nearly Twelve months later. Classic case of the cobbler’s children having no shoes. I have been so deep in other things that this milestone just sat quietly in the corner, waiting for me to catch my breath.

So here I am. Finally catching my breath.

On 23 June 2025, the International Journal of Emerging Trends in Computer Science and Information Technology presented me with the Best Research Paper Award for my paper titled Strategic Leadership in the Age of Agentic AI: Redefining Executive Decision-Making and Organizational Control.

But before I talk about the award, I want to talk about the last 12 months that followed it. Because honestly, that period shaped how I see this research more than the award itself did.

The 12 Months That Changed Everything

Right after receiving the award, life shifted up a gear.

I threw myself into preparing for my Doctoral Viva Voce. If you have been through doctoral viva preparation, you know what that season feels like. It is not just revision. It is a complete reckoning with your own thinking. You revisit every assumption you made, every framework you built, every conclusion you drew, and you ask yourself whether it holds up under scrutiny that pulls no punches. Months of preparation, late nights, and more rewrites than I care to count. And I am glad to say that journey has now come full circle. I successfully completed my Viva Voce in December, and that in itself feels like a chapter closing and a new one opening at the same time.

Running parallel to all of that, I was deeply involved in two significant pieces of work. The first was analyzing and evaluating SupplAIQ, a leading AI powered supply chain platform with a strong focus on lead time analytics, intelligent decision support, and operational optimization. The second was researching and documenting AI use cases across the construction sector, exploring how intelligent systems are beginning to reshape project planning, resource management, and operational decision making on the ground.

And here is what made both of those experiences so striking. These were not theoretical exercises. SupplAIQ was a live, functioning system being used in real supply chain environments. Purchase timelines being influenced by AI recommendations. Resource allocation being shaped by intelligent forecasting. Business processes being coordinated with minimal human intervention at each step. Similarly, the construction sector work showed AI moving well beyond pilot projects, into actual site operations and procurement workflows.

Sitting with all of that, while simultaneously preparing to defend my doctoral research on the Impact of Adaptive Strategic Management on Organization Growth Powered by Digital Innovation, was one of those moments where theory and reality collide in a way that makes everything feel urgent.

It reinforced something I already believed but now felt in a much more concrete way. The governance conversation around Agentic AI is not a future problem. It is happening right now, inside real organizations, and most of them are simply not ready for it.

So Where Did This Research Actually Start?

It started with a question that kept nagging at me.

For years, AI has played a supporting role. Humans asked, AI answered. Humans decided, AI assisted. That was the dynamic we all got comfortable with.

But something has shifted underneath us.

We are no longer talking about AI that responds. We are talking about AI that acts. Systems that can scan market conditions, reprioritize workflows, coordinate across enterprise tools, allocate resources, generate recommendations, and in some configurations, execute decisions outright. All without waiting to be told what to do next.

This is what Agentic AI actually means. Not smarter chatbots. Not better search. Genuine autonomous decision making embedded inside business operations.

And the moment you sit with that properly, one question rises to the surface faster than any other.

If the AI is making decisions, who is actually responsible?

Not in a legal fine print sense. Strategically. Organizationally. As a matter of leadership and accountability.

That question became the thread I kept pulling on.

What the Research Actually Proposes

The paper does not argue that organizations should slow down their AI adoption. That ship has sailed, and frankly, the competitive pressure to move fast is real.

What it argues is that executives need to rethink their own role in an age of autonomous systems.

The old model, where leaders sit at the top of a decision pyramid and make the final call on everything, simply does not scale when AI agents are handling thousands of micro decisions a day. But stepping back entirely and letting the system run creates accountability voids that no organization can afford.

The framework I propose lands somewhere in between. It positions leaders not as referees of every AI decision, but as architects of the system itself. People who design the governance structures, set the decision boundaries, define the human approval thresholds, and build the accountability mechanisms before the AI agent ever touches a live business process.

In practical terms, that means getting clear on questions like these. How much autonomy should this agent have in this specific context? At what point must a human intervene? Who is accountable when an AI driven decision produces a bad outcome? And how do you build explainability and auditability into the system from day one, not as an afterthought?

The goal is not to slow innovation. It is to make innovation sustainable.

Strategic Leadership and Organizational Control Framework for Agentic AI

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Why This Matters Right Now

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When I first started researching this topic, Agentic AI was still a fairly niche conversation. Most practitioners had not encountered the term outside of research papers. Organisations were still figuring out basic AI adoption, let alone autonomous AI governance.

That has changed at a pace that surprised even me.

Today, every major AI company is investing heavily in autonomous agents. Enterprise platforms are embedding them into supply chains, financial systems, ERP environments, and customer operations. The SupplAIQ evaluation and the construction sector work I mentioned earlier were both front row seats to exactly that shift. What I was studying in research papers, I was simultaneously watching play out in live business decisions across two very different industries. That kind of parallel experience does something to how you see a problem. It stops being abstract very quickly.

And the gap I kept observing was always the same. The technology was moving. The governance was not keeping up.

About the Award

The IJETCSIT Editorial Board reviewed more than 480 submissions this year, from researchers, academics, and industry professionals across the globe. Papers were evaluated on originality, methodological rigour, practical significance, and potential impact on future research and industry practice.

Learning that my paper ranked among the highest scores was genuinely humbling.

Not because recognition does not matter, it does, but because it told me that the research community is beginning to take AI governance seriously as a strategic leadership problem in its own right. Not a compliance exercise. Not an IT risk question. A fundamental question about how organizations lead in an age of autonomous systems.

That feels important.

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What the Journey Actually Looked Like

Research never goes the way you expect when you first start.

You spend months building an argument, then a single peer review comment dismantles the foundation and you have to start again. You read papers that contradict each other and have to decide which thread of evidence you actually trust. You write sections that feel sharp and clear at midnight, then read them the next morning and wonder what you were thinking.

There were moments during this research where I genuinely wondered whether the question I was asking was too early. Whether the field had not caught up yet. Whether I was writing about a problem that would not feel urgent for another five years.

And then the world moved faster than anyone predicted, and suddenly the urgency was everywhere.

That is the strange thing about research that turns out to be timely. You cannot plan it. You just have to trust the question.

What Comes Next

Completing the Doctoral Viva and receiving this recognition within the same year feels like more than coincidence. It feels like a signal.

The doctoral journey, the SupplAIQ work, the construction sector AI research, all of it is pointing in the same direction. As Agentic AI becomes embedded in everyday business operations, the conversations around leadership, accountability, and organizational control will matter just as much as the conversations about AI capability itself. Probably more.

Because in the end, it is not the algorithm that decides how AI gets used in an organization. It is the people leading it. And those people need frameworks, not just features.

That is the work I want to keep doing.

Thank you for reading.

Dr. Satyasri Akula


Also Published in :  Why Agentic AI Needs Leaders, Not Just Algorithms — A Personal Research Journey | by Dr. SATYASRI AKULA | Thoughts & Reflections | Medium

More Than a Feature: A Reflection on Being Recognized by The CEO Magazine

 

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