AI for Business Growth & Transformation
A landmark event exploring the transformative power of AI in Nepal's business landscape
Event Overview
We are thrilled to announce the successful conclusion of the landmark "AI Tech Peak Talk on AI for Business Growth & Transformation," held on December 28, 2025. This pivotal event, a powerful collaboration between the AI Association Nepal (AIAN) and the IT Council of the Confederation of Nepalese Industries (CNI), brought together Nepal's foremost business leaders, AI experts, and innovators. The mission was clear: to demystify Artificial Intelligence and provide a practical roadmap for its adoption to drive tangible growth, efficiency, and competitive advantage in the Nepali business landscape.
The resounding message from the event was unequivocal: AI is not merely an IT project; it is a strategic leadership imperative that will define the next decade of business success in Nepal and beyond.
Mr. Giri set the tone by emphasizing that AI transformation starts in the boardroom, not the server room. He challenged leaders to shift their mindset:
Key Leadership Shifts:
- From "What is AI?" to "What is our bottleneck?" – Identify your "burning problem"
- AI as a Leadership Project – Not an IT initiative
- Three Pillars of AI Leadership:
- The North Star (Vision): Give permission to transform
- The Cultural Umbrella: Create a safe-to-fail environment
- Resource Alignment: Reallocate top talent to AI problems
Global Success Stories:
He showcased how global leaders are leveraging AI:
- Hero MotoCorp: From traditional assembly to 'self-learning' factories
- Chipotle: Using AI to 'take the robot out of the human'
- CP Foods: Volume-based farming to precision agribusiness
- Zara: Solving the 'inventory nightmare' with AI
Nepali Case Study: Merojob Transformation
Mr. Giri presented Merojob's journey to become an AI-driven hiring platform, achieving:
- Enhanced match quality and reduced hiring time
- Successful reskilling of IT teams
- Data standardization across 1M jobseekers and 40K employers
- Measurable business impact through AI innovation
Dr. Pokharel delivered a crucial, grounding message: "No data, no AI." He debunked the myth of needing perfect data to begin, urging businesses to start with what they already have.
Core Principles:
- AI starts with data, not technology
- Every organization already has useful data
- AI learns from past actions and outcomes
- Start with whatever data you have (transactions, records, invoices)
From Information to Insight:
AI enables leaders to move from reactive to proactive:
- Pattern Recognition: Late payments → early risk signal
- Trend Analysis: Sales dip → demand shift detection
- Issue Identification: Frequent delays → process problems
Data enables AI to move leaders from "what happened" to "what is likely to happen next."
Turning Effort into Efficiency:
The same data used for reports can power daily operations:
- Banks: Customer data speeds up KYC checks
- Operations: Past queries help respond faster
- HR: Hiring data supports consistent screening
"Organizations that start using data today will lead in the AI era tomorrow."
Mr. Bhattarai demystified the technical infrastructure with a powerful analogy: "You don't build a power plant to turn on a light."
The Cloud Revolution:
- Shift from CapEx (buying hardware) to OpEx (pay-as-you-go)
- Access to AWS, GCP, Huawei Cloud, Runpod, Hyperstack
- AI is now cheaper, easier, and faster to use
- Scale from small experiments to global systems
The AI Factory Model:
| Component | Role | Nepal Context |
|---|---|---|
| Data | Raw Material | Start with what you have |
| Cloud | Factory Building | Secure, scalable storage |
| Compute | Machines & Power | Rent on-demand |
| AI Agents | Skilled Workers | Your digital workforce |
AI Agents: Nepal's Digital Workforce:
AI Agents are autonomous programs that understand goals and execute tasks:
- Customer Service Agent: Answers questions 24/7
- Market Research Agent: Analyzes local trends
- HR Agent: Schedules interviews consistently
- Compliance Agent: Checks regulations automatically
"AI is becoming a utility, not a luxury. Just like electricity powers machines, AI now powers decisions. Businesses win by using AI wisely, not building everything themselves."
Mr. Sigdel highlighted that sustainable AI must be responsible AI, built on four foundational pillars:
🏛️ Fairness
Avoids bias in critical decisions like hiring, lending, and pricing.
🔍 Transparency
Provides clear explanations for AI decisions.
⚖️ Accountability
Ensures human oversight and clear roles.
🛡️ Safety & Privacy
Protects user data and ensures security.
Why Businesses Should Care:
⚠️ Risks
- Biased models hurt customer trust
- Black-box decisions lead to regulatory issues
- Data privacy breaches damage credibility
- Poor deployment wastes investment
💡 Opportunities
- Improve decision-making with fair data
- Reduce operational costs
- Build customer trust through transparency
- Attract global investors
AI Failure Case Studies:
Amazon Hiring Tool (2014-2017): Downgraded women's resumes due to historical bias
Apple Card (2019): Offered lower credit limits to women despite shared finances
COMPAS Algorithm: Predicted higher re-offending risks for Black defendants
Why Trusted AI Matters for Nepal:
- AI adoption is starting but understanding lags behind
- Data quality and regulatory gaps pose risks
- Nepal can leapfrog by embedding ethics early
- Build AI that works for people, with people
Ms. Bhatt brought theory to life with tangible AI applications across Nepal's key economic sectors.
🌾 Artificial Intelligence in Agriculture:
AI-powered sensors, drones and satellites
AI algorithms for planting, fertilizing & harvesting
Weather patterns, soil quality & growth analysis
Optimize schedule and reduce water waste
Real Example: Agrix Tech Plantix – Used in India, Brazil, Nigeria, Vietnam (18+ languages)
🏥 AI Use Cases in Medical Sector:
Medical imaging & early detection
Disease risk & outcome forecasting
Precision treatment & drug recommendations
Hospital operations & resource management
📊 McKinsey Research Insights:
Ms. Bhatt shared compelling data from McKinsey's Frontline Sales Survey (Oct 2026):
- 46% increase in pipeline value from AI adoption
- 45% increase in qualified leads
- 48% efficiency gains in sales operations
- 35% higher client satisfaction
"The use cases are vast, proven, and applicable across Nepal's key economic sectors. From agriculture to healthcare, AI is ready to transform Nepali businesses today."
Conclusion & The Path Forward
The AI Tech Peak Talk was more than a seminar; it was a clarion call for action. The insights from our distinguished speakers provided a comprehensive blueprint:
Start with Leadership Vision
Build on Your Data
Leverage Cloud Ecosystems
Commit to Ethical Principles
In today's rapidly evolving landscape, the risk isn't in experimenting with AI,
it's in waiting while competitors move forward.
Leaders who embrace this transformation will capture market share,
those who hesitate will fight to stay relevant.