Enterprise AI Product Strategy Masterclass

 In six weeks, you will evolve from AI awareness to AI authority, able to architect systems, lead teams, and prove ROI in real-world enterprise and government operations 

Let’s face it: the startup hype cycle is slowing down.

The future of AI belongs to enterprises and governments where adoption, scale, and impact truly happen.

As organizations race to operationalize AI across their core functions, the role of the Enterprise AI Product Manager is rapidly emerging as one of the most strategic and sought-after positions in the modern economy.

From 2025 onward, enterprises and public institutions will define the next era of AI transformation focusing not on prototypes, but on systems that deliver measurable business and societal value.

Enterprise AI Product Development is now mission-critical because large organizations are:

• Investing heavily to optimize operations, personalize experiences, and automate decision-making with AI. 
• Facing the challenge of turning AI from experimentation into production — under real constraints of budget, regulation, and infrastructure.
   

Unlike startups, enterprises operate with massive data ecosystems, complex processes, and high-stakes environments. These conditions make them the ideal training ground to build production-grade, ROI-driven AI solutions that must work reliably not just in a demo, but in deployment.

Learning how to manage and build AI within enterprise and government contexts equips you with the capabilities to:

• Lead cross-functional teams that bridge executives, data scientists, and engineers. 
• Align AI initiatives with business goals, governance, and compliance requirements. 
• Deliver scalable, secure, and value-centric AI systems that transform organizations.
   

These are the skills in highest demand across industries like energy, finance, healthcare, smart cities, logistics, manufacturing, and public services where AI is no longer optional, but essential to competitiveness and resilience.

• AI is powering the next wave of enterprise and government transformation.
  From Agentic workflows that automate complex decision-making to Generative AI systems that design, simulate, and optimize processes, AI is shifting from “tool” to “co-worker.”
  Those who can build and manage these systems will lead the organizations that shape the future.
   
• AI-literate product leaders create measurable business impact.
  Product Managers and executives who understand how to integrate GenAI, Computer Vision, NLP, and Knowledge Graphs can build solutions that cut costs, accelerate decisions, and deliver competitive advantage.
  These leaders bridge the gap between technical innovation and organizational value, a skill now required at every executive table.
   
• Responsible and explainable AI is a strategic necessity.
  As enterprises adopt autonomous and generative systems, the need for accountability, safety, and governance grows.
  Professionals who understand AI ethics, explainability, and compliance will be the ones trusted to deploy these powerful systems responsibly.

 1. Executives and leaders who lack AI fluency are increasingly excluded from transformation initiatives and strategic decision forums. As automation and decision intelligence become the backbone of modern enterprises, leadership without AI literacy is perceived as operational risk.

2. Organizations that fail to embed AI adaptability and generative intelligence into their products or operations will lose market share to those that can scale insight, automation, and responsiveness across their value chain.

3. The world’s most forward-moving programs, from smart cities to manufacturing optimization and public infrastructure automation are now powered by Agentic and Generative AI ecosystems.
Falling behind means losing participation in the next wave of global digital transformation and industrial competitiveness.

The Enterprise AI Product & Solution Development Masterclass equips you with the skills, frameworks, and technical literacy to build real-world AI systems that deliver measurable value, not just prototypes or pitch decks.

Over six weeks, you will learn how to design, build, and operationalize AI solutions that perform in complex enterprise and government environments.

✅ Master enterprise-grade AI product management from strategy to deployment in just six weeks.
✅ Learn to define, design, and deliver AI solutions that solve real business problems and align with ROI, governance, and compliance goals.
✅ Understand modern AI lifecycles including MLOps, LLMOps, and Edge AI deployment.
✅ Gain hands-on familiarity with Agentic AI and Generative AI systems, learning how to integrate them into enterprise workflows for automation, analysis, and decision support.
✅ Explore technical foundations across Computer Vision, NLP, and Knowledge Graphs, and learn how to select the right technique for each use case.
✅ Build your own AI MVP using accessible tools like Replit guided by enterprise-grade design principles.
✅ Access real enterprise case studies, from smart cities, energy management, aviation, and public safety, rarely shared outside government and industrial AI circles.
✅ Bridge business and technology by combining user-centered design, data architecture, and model validation into one cohesive product vision.

Dr. Adhiguna Mahendra brings a rare combination of technical depth, executive experience, and national impact to the field of Artificial Intelligence. His background spans engineering, operations, and leadership, from building real-world AI systems to shaping Indonesia’s national AI roadmap.

 Unlike typical instructors whose experience is limited to Big Tech, Dr. Mahendra’s career bridges multiple critical industries and ecosystems:

• Smart City Development: Director of Data and AI at Otorita Ibu Kota Nusantara (IKN), leading the design of national-scale smart infrastructure and autonomous systems.
   
• Industrial and Enterprise AI: Experience in oil & gas (Schlumberger), manufacturing (Vallourec SA), aviation (Garuda Indonesia), and B2B eCommerce (Ralali).
   
• Tech Startups: Former senior leader in Computer Vision and Analytics startups such as Nodeflux and Flight Focus Singapore.
   

This cross-industry perspective gives him unmatched insight into how AI systems operate under real constraints across technology, business, and governance layers.

Dr. Mahendra’s career spans from engineering to the C-suite, giving him a holistic view of how AI transforms organizations end-to-end.

He has led teams in operations, software development, product management, and AI deployment, making him one of the few instructors who has both built the systems/products and make a decision of the the procurement budgets of multimillion dollar digitalization initiatives.

His decisions have influenced multimillion-dollar technology investments and national digital transformation initiatives. As a product builder and industry practitioner, Dr. Mahendra has been part of multiple successful startup exits.

Unlike academic instructors, he has real “skin in the game,” having led AI products from conception through commercialization and nationwide deployment.

This ensures that his teaching is not theory, it’s experience distilled from real operational success and lessons learned in the field.

Dr. Mahendra is the author of “AI Startup Strategy” (Apress, 2023) and the forthcoming books “Intelligent Video Analytics” and “Intelligent IoT Analytics” (Mercury Learning/De Gruyter).
His works cover Deep Learning, Computer Vision, MLOps, and enterprise AI architecture, blending technical precision with business strategy.

He also lectures on applied AI and intelligent systems at universities and executive programs, mentoring the next generation of AI leaders.

Unlike most instructors who teach product management from the outside looking in, Dr. Mahendra has lived both sides, as the builder and the decision-maker.

He has personally developed avionics hardware and video analytics software, and later, as an executive, evaluated, procured, and deployed AI solutions at national scale.

This unique vantage point allows him to teach AI Product Management through the eyes of:

• The engineer who understands how systems are built,
   
• The product manager who brings them to life, and
   
• The executive who must ensure ROI, compliance, and real-world reliability.
   

This holistic understanding of technology, business, and policy delivers insights that most.

This masterclass is tailored for executives and senior professionals leading digital transformation, AI adoption, or innovation within their organizations.
It equips leaders with the strategic and technical fluency to make informed, high-impact decisions in the rapidly evolving landscape of enterprise and government AI.

• C-Level Executives and Business Unit Leaders
  Who oversee technology, innovation, or data strategy and seek to integrate AI across their organization’s operations, products, and decision systems to achieve measurable ROI and efficiency gains.
   
• Directors and Heads of Data, AI, and Digital Transformation
  Responsible for aligning technical teams, budgets, and business objectives, looking for actionable frameworks to operationalize AI responsibly, at scale, within enterprise or public-sector ecosystems.
   
• Senior Product, Operations, and Technology Managers
  Who want to move beyond incremental improvements and lead the design and deployment of production-grade, AI-enabled systems that deliver strategic advantage.
   
• Government Leaders and Policy Innovators
  Who are driving Smart City, infrastructure, and digital-governance initiatives and need to understand how to evaluate, govern, and scale AI within complex public systems.
   
• Founders and Corporate Entrepreneurs
  Building AI-driven products and platforms that must succeed under real constraints, limited resources, compliance demands, and mission-critical reliability.

This is not a “framework” course, it’s a transformation program for leaders responsible for designing, funding, and scaling enterprise or government AI systems.

Participants will master how to structure AI teams, architect intelligent systems, integrate them into Command and Operations Centers, and evaluate ROI through simulated, measurable outcomes.

Both external-facing (customer/public) and internal-facing (executive/operator) AI systems are covered.

Week 1: 

Goal: Build an executive-level understanding of AI as an enterprise capability, not a project or tool.
You’ll Learn:

• How AI creates business value across public and private sectors. 
• Types of AI systems: external (citizen/customer-facing) vs internal (decision-support, analytics, automation). 
• Enterprise AI lifecycle and architecture from data layer → model layer → operations layer. 
• Strategic alignment: linking AI initiatives to corporate KPIs, mission outcomes, and ROI logic.
   

Week 2: 

Goal: Understand the technological backbone of modern AI systems : from LLMs to edge deployments.
You’ll Learn:

• Architecture of LLMs, Computer Vision, NLP, and Knowledge Graphs. 
• Agentic AI and multi-agent orchestration within enterprise workflows. 
• Data governance, pipelines, and infrastructure selection (on-prem, cloud, hybrid, edge). 
• Cost structure of AI systems: compute, data acquisition, inference, and maintenance.
  

Week 3:
Goal: Learn how to structure and manage the human system that builds the AI system.
You’ll Learn:

• Team topology for AI programs: data, ML, Ops, and business fusion teams. 
• Role delineation: Product Owner, ML Engineer, Data Engineer, MLOps, LLMOps, and DevOps. 
• How to organize teams by value streams (internal vs external AI products). 
• Governance and RACI models for multi-agency or cross-department AI initiatives. 
• Leadership lessons from real deployments.
  
   

Week 4:

Goal: Translate strategy into functional prototypes that solve real operational problems.
You’ll Learn:

• End-to-end product development: from problem scoping → MVP → validation. 
• Framework for Human-AI Interaction and UX in enterprise contexts. 
• Rapid prototyping using Replit Agent, Hugging Face, TensorFlow, and real datasets. 
• Validation methods: stakeholder testing, operational benchmarking, compliance checks. 
• Combining user-centric design and engineering validation in one sprint.
   

Week 5:

Goal: Learn how AI systems transition from prototype to 24/7 operational environments.
You’ll Learn:

• Command & Operations Centers as the nerve centers of AI deployment. 
• Integrating AI with real-time systems (CCTV, IoT, ERP, SCADA, GIS). 
• Principles of MLOps, LLMOps, and continuous monitoring in critical operations. 
• Reliability, resilience, and incident response design in AI-powered operations. 
• Linking operational metrics (uptime, precision, false alarm rate) to ROI.
   

Week 6:

Goal: Quantify the business impact of AI systems using simulation and scenario-based validation.
You’ll Learn:

• Business simulation frameworks for modeling AI performance under uncertainty. 
• Scenario planning for resource optimization, risk mitigation, and decision latency. 
• Calculating total cost of ownership (TCO) and expected business ROI using real operational data. 
• Building the Executive AI Roadmap: integrating strategy, architecture, team design, and economics. 
• Capstone Presentation: participants present their AI Roadmap and Simulation Outcome for executive review.
  
   

Each participant will complete:

• Enterprise AI Roadmap (strategic blueprint for 6–12 months) 
• AI Organization Design Canvas (team structure, governance, and operating model) 
• Operational Simulation Report (scenario-based ROI analysis) 
• Prototype Application 
• Executive Presentation Deck for leadership or funding approval

Abul Khair, Product Manager, CakeResuI was quite shocked because the knowledge gap was pretty significant. Thankfully, at that time I was enrolled in Adhiguna's AI Product Management bootcamp. Honestly, it was really helpful for someone like me who had never been involved in AI before. He taught the product management part from the basics and in a quite general manner, so I feel it can be implemented by PMs from any industry as well. Thank you so much for the knowledge."

Hamidah Syahrir-Senior Product Manager, Liminal.  

"As a product manager at a company that implements AI for the development of a verification system, it is imperative not only to possess knowledge regarding AI strategy in business implementation but also to understand the application of AI that allows for performance monitoring against anomaly patterns.

What distinguishes this course from others is the integrated combination of business and technical knowledge. During the course, we learned how to validate AI products for market adoption to align with market expectations and established a strong foundation in operational machine learning, including the explainability of an AI model."

Arin Siska-Senior Product Manager, Vida

"As a product manager overseeing AI products, a deep understanding of AI product management is crucial for success. This course has been an invaluable resource for me, providing essential insights and strategies to ensure the products I manage can harness the full potential of AI while effectively addressing user needs. The course content is not only comprehensive but also tailored to the specific challenges faced by AI product managers. "

Indra Nugraha, Senior Product Manager, Mekari 

"AI product development course was a truly enlightening journey that expanded my knowledge and understanding of the vast applications of artificial intelligence. The well-structured curriculum provided a comprehensive overview of machine learning, data preprocessing, and the deployment of AI models based on cases provided. Engaging in practical projects was particularly valuable as it allowed me to translate theoretical knowledge into real-world solutions. One of the most gratifying aspects of the course was the collaborative project with industry experts to develop an AI-powered detection object system for surveillance and defense. The guidance and mentorship provided by the instructors were invaluable in refining our approach and achieving tangible results. This experience not only honed my technical expertise but also underscored the transformative potential of AI in optimizing industrial operations. "

 Rizky Munggaran, AVP AI&Machine Learning, Indosat 

"The AI Product Management material coached by Adhiguna opened up new horizons and perspectives from a different side. Technical matters were delivered perfectly, making them very easy to understand. The combination of knowledge and experiences truly produced a systematic way of thinking and ultimately had a significant influence on me in viewing a product development process."  

Ali Rahman, Founder, wefly.id

 "The AI Product Management BootCamp was hands down one of the most impactful learning experiences I've ever had! It felt like diving into a fast-paced Master's program, with a flood of new and cutting-edge knowledge. The coaching was exceptional, especially from Adhiguna Mahendra, whose deep experience truly shone through. For anyone looking to level up their entrepreneurial skills, learn how to build groundbreaking AI products, or simply stay ahead in the dynamic world of AI product development, I can't recommend this bootcamp enough. Make sure you catch the next batch! In the meantime, please wish me luck as I navigate my ambitious project! "

Mark Swapo, Product Manager, Bank Central Asia Digital

"Adhiguna has deep knowledge and experience on Al apps, he knows how to set up from zero to become a commercial app. I am deeply grateful for his guidance, which was instrumental in the development of my new AI business."    

Henry Hanafiah, President Director, Willis Towers Watson Indonesia 

"Very insightful with tons of experiences. In spite of not having a technical background, I can enjoy learning Al here. The material was already good, Adhiguna already explained examples of Al applications. "

 Okkytania E.P, Product Management & Business Development, PT Busan Auto Finance 

 "The instructor is very skilled not only from a business perspective, but also technically. "

 Sisi Florensia, Product Manager, MagLoft 

"Adhiguna is very humble and insightful with all the experience combined by tech in Al expertise, such an honour and opportunity to join this AI Product Bootcamp."

 Andy Hartanto, Cloud Support Engineer, Xsolla 

" I am very satisfied with the AI Product Management course. The course was very helpful for me to understand the MLOps process and development for both Machine Learning and AI products. This course has also equipped me to work as a product manager in a big data and Machine Learning company in Singapore."