Nick Gushchin
Co-founder of the Swiss AI Chatbot Factory, Advisor to AI Startup CloEE
Zürich, Switzerland
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I’m a tech entrepreneur and AI builder based in Zurich, where strategy meets code.
After 18 years in executive banking, I taught myself Python and transitioned from managing large organizations to building AI systems that run on logic, not hierarchy. Over the past three years, I’ve delivered more than 20 AI projects across healthcare, banking, industrial automation, and customer experience - designing solutions that actually survive contact with reality.
My mission is to build client-centric AI factories - scalable agentic systems that transform how businesses operate, scale, and compete. I focus on practical AI engineering: modular architectures, automation orchestration, and measurable ROI.
On stage, I talk about what happens when AI leaves the lab — the financial bubble, the architecture of resilient AI systems, client-centric implementation, and hard-earned lessons from real AI failures.
I bridge strategy and execution - turning AI potential into reliable, auditable business systems that deliver beyond the demo.
Area of Expertise
Topics
Give Work to AI: How Agentic AI Powered the Humanless. Swiss AI Chatbot Factory
The future of work isn’t just about humans using AI—it’s about AI becoming the workforce. In this talk, I unveil a groundbreaking approach to business automation: an AI-powered chatbot factory where AI agents act as developers, designers, and operators. With just two human founders, this factory builds and deploys chatbots within minutes, proving that AI-driven enterprises can scale without expanding human teams.
I will share the architecture, automation strategies, and real-world challenges behind the Swiss AI Chatbot Factory, highlighting how AI-first businesses can be structured, optimized, and monetized. From self-managing AI teams to workflow orchestration, this session explores the next frontier of AI-driven entrepreneurship—where companies operate with minimal human intervention, and AI takes on real, productive roles.
From Ticket Chaos to Strategic Efficiency: How AI Is Transforming Internal IT Support
In this session, I’ll show how Artificial Intelligence can take internal IT support to the next level — by automating ticket triage, routine workflows, and even physical asset management. You’ll see real examples of AI in action: chatbots resolving first-line issues 24/7, smart routing that cuts resolution time in half, and AI co-pilots helping developers fix problems before they escalate. I’ll walk you through a practical, step-by-step roadmap for implementation, highlight key KPIs to measure success, and share lessons learned from real-world adoption — including mistakes to avoid. This talk is ideal for IT leaders, support managers, and anyone looking to transform their internal support from a cost center into a strategic advantage.
Why AI Is Useless for Compliance
...and Why You Still Need It
A strategic view on the current limitations of AI in legal compliance — and how to use it wisely.
While AI systems are rapidly transforming business operations, their application in legal compliance remains deeply constrained. From the inability to interpret legal nuance to the lack of transparency in decision-making, today's AI is often misaligned with the core demands of regulatory work: accountability, context, and traceability.
This session offers a clear, expert-driven perspective on the state of AI in compliance — beyond the hype. Drawing on real-world cases and strategic frameworks, I outline the current technological boundaries, discuss key risks for organizations and regulators, and propose actionable approaches to using AI safely and effectively in complex legal environments.
Attendees will gain:
- A grounded understanding of what today’s AI can and cannot do in compliance
- Strategic considerations for implementing AI tools responsibly
- Case-based insights into where AI has failed — and where it adds value
- A framework for human-centered, auditable, and compliant AI integration
This talk is designed for: compliance leaders, general counsel, regulatory professionals, and executives seeking clarity — and confidence — in how AI can support (but not replace) human judgment in high-stakes domains.
Client-Centric AI Factory for Business: The Future of AI Implementation
Moving from “AI for AI’s sake” to scalable, measurable client value.
Most AI projects fail not because the technology isn’t ready — but because the business isn’t centered around the client problem.
Too many organizations chase “AI transformation” without defining success in real-world, client-centric terms. The result? Pilots that never scale, tools that don’t integrate, and “AI initiatives” that create more dashboards than value.
Drawing on my background leading large-scale digital transformations and my current work at the Swiss AI Chatbot Factory, I’ll share how to build AI systems that deliver measurable, repeatable outcomes — not experiments. We’ll explore the architecture of a Client-Centric AI Factory: a model where automation, data, and AI agents are orchestrated around the client journey, not internal silos.
You’ll see how this approach turns AI from a cost center into a scalable business engine — one that learns, adapts, and compounds value over time.
The AI Financial Bubble: When Intelligence Meets Speculation
Why the smartest tech boom might end like every bubble before it — and what real builders can do differently.
The world is experiencing an AI gold rush — and just like every rush before it, most of what glitters isn’t gold. Startups with no real models are raising millions. Enterprises are “going AI” without solving a single business problem. Valuations are skyrocketing, while actual productivity gains remain stubbornly flat.
Drawing on 18 years of executive experience in banking and financial strategy, I’ve seen this pattern before — from fintech bubbles to digital transformation hype cycles. Today’s AI boom follows the same speculative logic: capital chases trends faster than value creation can keep up.
In this talk, I’ll dissect the anatomy of the AI financial bubble — how speculative capital, media hype, and short-term incentives created a self-reinforcing illusion of exponential progress. But this isn’t a doomsday talk — it’s a reality check for serious builders. I’ll share a clear framework for identifying genuine value in the AI market, separating signal from noise, and building products that can outlive the hype cycle.
You’ll see what happens when “intelligence meets speculation” — and learn how to position yourself on the right side of the coming correction.
Architecting Robust AI Systems for Entrepreneurs
How to build startup-level AI architectures that actually scale — without a data science army.
In 2025, building AI systems isn’t just for Big Tech anymore. With today’s tools and frameworks, small teams — or even solo founders — can create production-grade AI systems. The real challenge is not building something that works, but building something that keeps working.
Drawing from my experience leading enterprise-scale operations and now building AI-first infrastructures at the Swiss AI Chatbot Factory, I’ll share a practical blueprint for creating reliable, maintainable AI architectures that scale with minimal human overhead.
This talk focuses on the architectural thinking behind sustainable AI startups: modular design, automation chains, agent orchestration, and fallback logic. You’ll see how to avoid the common traps of “prompt spaghetti,” vendor lock-in, and untraceable LLM behavior — and instead design systems that are transparent, testable, and business-aligned.
How not to fail with AI
Real-world AI failures — and what they teach us about building systems that actually work.
Everyone loves to showcase AI success stories — but the truth is, most AI projects fail. Quietly. Expensively. Repeatedly.
Models that never reach production. Chatbots that frustrate users instead of helping them. Automation pipelines that break under real-world complexity.
Over the past three years, as an AI builder working on more than 20 AI projects — from healthcare and chatbots to banking and industrial automation — I’ve seen firsthand how even well-funded, well-planned systems can fail in unexpected ways.
In this talk, I’ll share real AI use cases that didn’t go as planned — what failed, why it failed, and what we learned in the process.
From misaligned objectives and brittle prompt engineering to missing data context and weak orchestration between human and machine workflows — every case reveals a deeper pattern behind why AI underperforms when it leaves the lab.
This isn’t about pessimism — it’s about engineering realism. You’ll see how failure analysis can become a design tool, helping teams build AI systems that are reliable, auditable, and adaptable to change.
Nick Gushchin
Co-founder of the Swiss AI Chatbot Factory, Advisor to AI Startup CloEE
Zürich, Switzerland
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