For millions of professionals today, artificial intelligence has become a defining career inflection point. The gap between those who know how to work with AI and those who do not is widening rapidly, with McKinsey & Company reporting that 55% of business leaders now see AI fluency as a baseline workplace skill.
Yet most professionals across marketing, operations, finance, HR, and other functions still use AI mainly for drafting, quick research, or basic assistance. Very few know how to build workflows, automate tasks, or create AI-powered systems.
It was this reality that prompted Mohan Lakhamraju to reflect on what he has been hearing on the ground. In a recent LinkedIn post, he shared that over the past few months, many friends, relatives, and professionals have asked him how to keep up with the rapid developments in AI, particularly the rise of agentic AI.
Alongside this, he also observed a strong and growing intent among professionals to understand how to stay relevant and work effectively alongside AI agents in a practical, hands-on way.
Addressing this growing need among professionals, Great Learning has introduced AI Native Professional: Workflows and Agents for Productivity, an online program designed to help them move beyond basic AI usage and develop the ability to design workflows and deploy AI agents for practical applications.
About the Program
The AI-Native Professional: Workflows & Agents for Productivity is a structured 6-week online program designed to help professionals transition from simply using AI tools to effectively building AI-powered workflows and systems.
The program follows a practical, no-coding approach that enables functional professionals to develop fully operational AI solutions, including multi-step automations and end-to-end content pipelines.
Through hands-on learning and workflow-driven implementation, participants are equipped to improve productivity, save over 10 hours per week, and redirect their efforts from repetitive operational tasks toward higher-value strategic initiatives and business growth.
Who This Program Is Built For?
The program is designed for functional professionals with no coding background who currently spend significant time on repetitive knowledge work and want to use AI to reclaim that time for higher-value activity. It is specifically well-suited for those working in:
- Marketing & Communications
- Business & Operations Analysis
- Operations & Program Management
- Sales, Customer Success & Revenue Operations
- Finance, Consulting & Project Management
- HR & People Operations
No prior AI experience beyond basic familiarity is assumed. What the program does require is a willingness to build something real and apply it.
The Faculty and Learning Experience
The program is led by Dr. Pavankumar Gurazada, Director of Academics for Artificial Intelligence at Great Learning and Adjunct Faculty at Northwestern University and the University of Arizona.
He holds a Ph.D. in Applied Machine Learning with expertise in deep learning and MLOps, serves on the board of Constems AI, and is the author of Marketing Analytics, published by Oxford University Press, a postgraduate textbook used across leading business schools.
Beyond core instruction, the program includes live expert sessions with industry practitioners:
- The Research Sprint, focused on document analysis, research workflows, and reducing hallucinations using tools such as NotebookLM
- The Content Production Pipeline, where participants learn how AI can be used to create scalable multi-channel content workflows while maintaining consistency and quality
- Agents in the Real World, featuring practical demonstrations of workflow automation and AI agent deployment using tools like Activepieces
- The AI Fluency Career Guide, which helps professionals understand how to showcase AI-driven work and position themselves effectively in an evolving job market
Together, these sessions provide participants with exposure to real industry applications, practical frameworks, and implementation strategies that extend beyond theoretical AI learning.
What will you learn?
The 6-week structure is deliberately progressive, with each week building directly on the last. Here's how it unfolds:
Week 01: Foundations and Prompting
The program begins with the fundamentals of structured prompting. Participants learn how to create reusable prompt frameworks across ChatGPT, Claude, and Gemini to generate consistent, high-quality outputs for recurring professional tasks.
Week 02: Research and Analysis
Participants learn how to build searchable knowledge bases using NotebookLM and Perplexity. The focus is on improving research accuracy, reducing hallucinations, and generating outputs backed by verifiable sources and internal documents.
Week 03: Content Creation and Multi-Tool Pipelines
This module introduces multi-tool workflows that combine platforms such as DALL·E, Gamma, Google Vids, HeyGen, and Lovable. Participants learn how to transform a single input into multiple content formats, including project briefs, presentations, and social media assets.
Week 04: No-Code Automations
Using tools such as Activepieces, Google Sheets, and Gmail, participants build trigger-based automations that can monitor workflows, summarize information, and automate repetitive operational tasks without coding.
Week 05: AI Agents
Participants build and deploy functional AI agents capable of synthesizing information, automating recurring tasks, and generating scheduled outputs such as competitive briefs. The module also introduces the broader AI agent ecosystem and emerging tools shaping the future of work.
Week 06: Responsible AI and AI Evolution
The program concludes with participants presenting a fully functional multi-step AI system designed to solve a real workplace challenge. The focus is on practical implementation, responsible AI usage, and applying AI systems in real professional environments.
Tools You'll Master
The program provides hands-on experience with a carefully curated set of AI tools and platforms, organized across key professional workflows:
- Logic and Drafting: OpenAI, Claude, Gemini
- Research and Synthesis: NotebookLM, Perplexity
- Connectivity and Automation: Google Workspace, Activepieces
- Multimodal Content Production: Gamma, Google Vids, Claude
- Agents and App Building: Claude, Lovable
What Learners Will Learn and Build During the Program?
The program is designed with a strong hands-on focus and a clear outcome-oriented approach. Over 6 weeks, participants move beyond theory to build practical AI systems that can be applied directly in their day-to-day work.
By the end of the program, participants will have developed:
- Functional AI agents capable of automating recurring tasks, synthesizing information, and supporting real business workflows.
- A multi-format content pipeline that can transform a single input into project briefs, presentations, social content, and other reusable assets.
- A searchable knowledge base built using personal or organizational documents, designed to generate reliable, citation-backed outputs with reduced hallucinations.
- AI-powered workflows are integrated with commonly used workplace tools such as email, spreadsheets, and collaborative platforms.
- A personalized prompt library containing tested and reusable prompts tailored to specific professional roles and use cases.
- No-code automations powered by trigger-based systems to streamline repetitive processes and improve day-to-day productivity
Every deliverable is designed to function as a practical system that participants can continue using in their professional workflows even after the program concludes.
Industry-Oriented Capstone Project
One of the most deliberate design choices in the program is the Capstone Project.
Rather than assigning a generic case study, the program asks each participant to identify a recurring task from their own professional life, build an AI-powered solution around it with mentor guidance, and then put it into practice as a measurable productivity improvement.
This approach reflects a broader philosophy in the program's design: the best proof of AI fluency isn't knowing what the tools can do in theory, it's demonstrating what you built with them in practice.
The Credential
Participants who successfully complete the program will receive the AI-Native Professional: Workflows and Agents for Productivity certificate from Great Learning.
The credential is designed to validate practical proficiency in building AI workflows, deploying AI agents, automating professional tasks, and applying AI tools in real business environments. It reflects hands-on learning across AI workflows, no-code automation, content pipelines, and AI-powered productivity systems developed during the program.
The Investment
The program offers flexible payment plans available through a Program Advisor. The time commitment is 3-4 hours per week across six weeks, structured to work around existing professional responsibilities, not replace them.
Next Step
The professionals who will define the next decade of knowledge work aren't necessarily the ones with the deepest technical expertise. They're the ones who know how to direct AI systems, how to build them, configure them, and connect them to real business problems. That skill is still early enough to be a genuine differentiator. It won't be for long.
The AI-Native Professional: Workflows & Agents for Productivity program from Great Learning is a practical, well-structured path to getting there, built by practitioners, for practitioners, with the explicit goal of helping professionals create AI-powered systems they can continue using long after the program ends.
Ready to get started?
Explore the AI-Native Professional: Workflows & Agents for Productivity program at Great Learning and enroll now to learn more about the upcoming cohort.
