May Habib

AI Deployment - How to Leverage AI Across Your Business

CEO and Co-Founder of Writer

Why a full stack approach makes for turn key LLM and generative AI deployment.

Full Stack Approach and Why it Matters

How to think about your business data, leverage what you currently have, and make your data work for you.

Data-Data-Data

How to get started with generative AI, move out of testing phases and into actual deployment across the business.

Move Out of Testing

Hear about some of the best use cases for generative AI today and future use cases for tomorrow.

Real World Applications of AI Today

Arming senior leadership teams with the AI literacy, practical skills and strategic acumen needed to guide their companies into the AI era.

September 2026 Cohort

AI Strategist // Trainer // Futurist

Mark Laurence

Founder and lead consultant at generative AI consultancy Ten Past Tomorrow.

NZTE Private August 2026 Cohort

October 2026 Cohort

“We're going to get to AI systems that are better than almost all humans at almost all tasks... That's the thing I think we're quite likely to get in the next two or three years." - Dario Amodei (CEO, Anthropic. However… ”Only 8% of employees reported they feel GenAI is already transforming their organisation.” - Deloitte - State of Generative AI in the Enterprise report, Q4 2025. Quite frankly, the gap between AI advancement and AI adoption that those two stats speak to is just too large. It’s no longer just a gap. It’s a chasm. And add to that… “In organisations where AI is openly embraced, the chance of developing 'AI Experts' and 'AI Practitioners' is halved when direct managers discourage its use, either directly or indirectly.” - Section School - The AI Proficiency Report. Merging those three storylines and you get a headline that says that senior leadership is the bridge that connects AI aspirations to organisational reality, and ultimately the trajectory of its integration at every level. In other words; true organisation-wide AI adoption doesn’t begin with technology or tools. It begins with leadership. AI literate and AI skilled senior leadership.

Close the AI capability gap: Exec-level training for senior leadership teams

Master AI prompting fundamentals

Evaluate and select AI tools strategically

Discover how to truly scale AI usage throughout your business

Develop a 5-step AI transformation roadmap

Lead AI change management

Implement AI governance and privacy practices

Senior leadership teams wanting to collectively, confidently, knowledgeably, skilfully and ethically lead an AI-forward company.

SLT teams who sense AI is far more than a technical challenge, that it demands leaders step forward to lead comprehensive strategic change.

Leadership teams excited by making a genuine commitment to fundamentally reshape their people, processes and businesses.

Students will learn the AI literacy to evaluate AI ideas, surface risk, and make sound judgments without becoming technical specialists.

Modernizing Business Analysis

Angela Wick

25+ years practicing, shaping, and teaching analysis, product, and requirements.

AI Literacy for Business Analysts

AI usage, productivity, and implementation risk often come from poor assumptions about what AI can and cannot do. It also stems from poor analysis and organizational dynamics in which stakeholders ask for solutions that are either too specific or too generic, and pressure teams to deliver them, rather than solving real problems.Analysis professionals have a huge role in this dynamic that can change everything!Analysts are increasingly expected to participate in AI decisions, yet most training focuses on tools or stays abstract. This course fills the gap in understanding AI capabilities: Not from a technical point of view, but from a capability point of view; business uses and patterns of functional usage.You will build a grounded understanding of AI capabilities, limits, and failure modes, and learn how requirements shift toward hypotheses, experiments, and continuous outcomes in AI-enabled work.This course explores the skills of:🎯 Identifying the right AI use cases for specific business scenarios🎯 Distinguishing between deterministic and probabilistic systems and deciding where each should be applied in a workflow🎯 Questioning and communicating AI use case fit and risks

Giving BAs AI Fluency & Literacy to Use, Analyze, and Recommend AI Solutions

Major AI capability types and their appropriate uses

GenerativeAI is just one piece of AI, and much more than "chat".

What AI is good at and where it fails

Generative AI and its Data Sources (Public vs. Private)

How requirements shift to hypotheses and experiments

Where humans must remain accountable in AI-enabled systems

Business Analysts, Product Owners, Business Systems Analysts, Systems Analysts, Business Process Analysts, and similar roles.

BA Leaders redefining roles for AI-enabled teams

Business Leaders, Project and Product Professionals pulled into AI initiatives without clear accountability

Learn to turn ambiguous customer problems into production AI systems, and become the engineer who can own outcomes end to end.

DeepTech Entrepreneur, Technology Leader

Oracle

Yatra

Apparel Group

ANKUR NARANG

Three decades building HPC and AI systems processing billions of transactions

AI & ML Leader, Venture Partner - DCX

Adda247

Hike

Mobileum

Kush Khurana

AI product and deep-tech builder, Visiting Professor at Ashoka University

BTech & MTech IIT Mumbai. AI Lead

Tata Consultancy Services

Unify

Madhusudan Kumar

BTech & MTech IIT Mumbai. AI Lead with solid Agentic Experience

Cohort 1

AI companies don’t just need engineers who can build models or agents. They need people who can take an ambiguous customer problem, understand the workflow, design the right AI solution, integrate it with existing systems, deploy it reliably, and prove business value.That is the job of a Forward Deployed AI Engineer.Most AI courses teach you how to use a model, build an agent, or work with a framework. This course teaches you how to own the full journey from customer discovery to production deployment.You’ll learn how to work through messy data, legacy APIs, unclear requirements, security constraints, unreliable AI behavior, changing stakeholder needs, cost, latency, and adoption challenges.Through hands-on builds, architecture exercises, enterprise scenarios, and a capstone, you’ll learn to operate at the intersection of AI engineering, software architecture, customer discovery, product thinking, and business outcomes.The goal: become the engineer who can make AI actually work inside a real organization.

Become the AI engineer who turns real customer problems into production systems

Turn ambiguous customer problems into solvable AI opportunities

Architect production-grade enterprise AI systems

Build AI solutions that work beyond the demo

Evaluate, secure, and operate reliable AI applications

Own customer deployment, adoption, and measurable business value

Operate end-to-end like a Forward Deployed AI Engineer

Software, AI/ML, or data engineers who want to move from building components to owning end-to-end customer AI deployments.

Solutions architects, technical consultants, and implementation engineers moving into customer-facing AI and Forward Deployed roles.

Technical product managers, founders, and startup engineers who need to turn ambiguous business problems into deployable AI systems.

See your venture clearly, find what is holding it back, and choose the next move—so AI creates leverage instead of more work.

Systems Architect · Founder, Sysdom AI

THE WORLD BANK GROUP

Carnegie Mellon University

Han Kay

Systems Architect · Carnegie Mellon (MISM) · Triple Master's (MBA, MS) · 30+ yrs

AI gives founders two possible futures. It can multiply company capacity—or multiply the coordination work returning to the founder. If you're building an AI-native or agentic company, adding agents is the easy part. The harder problem is turning their output into leverage without becoming the integration layer for every handoff, decision, and next move. The missing layer is the system the agents operate inside. That is Systems Intelligence.This four-week working lab turns Systems Intelligence into founder practice. Across four focused 90-minute sessions, you will map your venture, identify the active constraint beneath the surrounding noise, commit one bounded next move, and complete a founder-directed operating cycle.Sysdom.ai is the included, supported working environment. It organizes venture context across the Product/Service, Customer, Cash, and Skills Engines, preserves evidence, and records the chosen move. You remain responsible for direction, consequential decisions, and approval boundaries.Leave with a clearer venture state, explicit decision boundaries, one completed cycle, and a repeatable way to increase agent capacity without increasing founder coordination.

AI amplifies everything. Including what’s broken.

See your venture as one system

Build an evidence-backed venture map

Find the constraint behind the noise

Choose one bounded next move

Set founder and agent decision boundaries

Start a guided operating cycle

Bring research, a prototype, operating signals, prior decisions, or a serious plan. No website, revenue, or technical setup required.

Bring one real venture—and some evidence

Founders building a venture who feel complexity outpacing their mental model. You have pieces but no unified operating system.

Founders who hit their first real bottleneck and realized working harder isn't solving the structural problem underneath.

Founders whose AI tools and agents produce more output while every important decision and handoff still routes back through them.

Agentic AI

Coding with AI

AI Workflows

Claude Code

OpenClaw

Vibe Coding

AI Evals

AI Transformation

RAG & Search

AI for PMs

AI for Engineers

AI for Designers

AI for Marketers

AI for Founders

Product Sense

Product Discovery

User Research

Prototyping

Growth

Analytics

Tech Foundations

Strategy

Influence

Leadership

Career Growth

Machine Learning

LLM Ops

Context Eng

Security

System Design

Figma

Design Systems

Visual Design

Design Strategy

Automation

Content Marketing

Demand Gen

Go-to-Market

Product Marketing

Positioning

Social Media

Brand

B2B Marketing

SEO & AEO

AI for Leaders

AI Governance

Communication

Management

People Operations

Exec Presence

Storytelling

Goal-setting

Personal Brand

Fundraising

Everyone

Operators

Data Scientists

Business Analysts

User Researchers

Customer Success

Project Managers

HR Professionals

Sales People

Lawyers

Finance

Investors

Real Estate

Educators

Creators

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

AI Deployment - How to Leverage AI Across Your Business

What you'll learn

Why this topic matters

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May Habib