GenAI & Agentic AI · AI-native institute · Enrolling now

Modern Business Analyst with GenAI & Agentic AI

The traditional BA was measured by documents produced. The modern BA is measured by outcomes: turn ambiguous enterprise problems into valuable, testable, governed and deployment-ready human–AI solutions — and be the BA for the AI solution, not just a BA who uses AI.

100K+

alumni community

1,000+

hiring partners

4.8/5

avg class rating

partner centres

Digital Edify centres

Where our AI-native BA alumni work

Microsoft

Amazon

Salesforce

ServiceNow

Deloitte

Infosys

Accenture

TCS

Wipro

Capgemini

Cognizant

HCL

Microsoft

Amazon

Salesforce

ServiceNow

Deloitte

Infosys

Accenture

TCS

Wipro

Capgemini

Cognizant

HCL

Direct answer

What does a modern Business Analyst do?

A modern Business Analyst turns an ambiguous business need into a specification an AI-enabled system can be built and accepted against. The classic craft — stakeholders, process, requirements, acceptance — still holds. What is new is that the thing being specified may reason, act and get things wrong: so the analyst also specifies the agent’s boundaries, the human approval, the evidence that closes a story, and the conditions under which the system must stop and ask.

The complete specification chain Twelve links, one traceable thread.

01UNDERSTAND

•Stakeholders — Power/Interest & RACI
•As-is process reality (BPMN)
•Data reality & system landscape
•Problem frame & KPI baseline

02SPECIFY

•Requirements — BRD / FDD / RTM
•10-section Agent Specification
•Human-in-the-loop control points
•Acceptance criteria & evidence

03PROVE

•Versioned evaluation sets & red-team
•UAT & go / no-go recommendation
•Adoption & change (ADKAR)
•Benefit — value scorecard & ROI

The distinction that defines this course · 2026

“Using AI as a BA” and “being the BA for an AI solution” are different jobs.

Job 1 · Use GenAI for Business AnalysisProductivity

Use AI to prepare, compare, draft, structure, synthesise and review BA work faster — every output subject to human verification.

•Interview preparation & probing question sets
•Stakeholder-feedback clustering & workshop summaries
•Process-draft, user-story & acceptance-criteria suggestions
•Test-scenario ideas & change / training-content drafts

Job 2 · Perform BA on AI-enabled solutions★ The durable differentiator

Discover, qualify, design, specify, validate and govern GenAI features, RAG assistants, tool-using agents and agentic workflows.

•Define an agent’s goal, tools, boundaries & permissions
•Design human approval, escalation & autonomy
•Specify evaluation, observability & operational controls
•Keep a named human accountable for every outcome

Autonomy is a dial — not a switch

Assist

Drafts & suggestions for a human.

Recommend

Proposes an action with rationale.

Approve-to-Act

Waits for explicit human approval.

Supervised Action

Acts under active human oversight.

Bounded Autonomy

Acts within evidenced limits.

Who should join

Built for people moving into AI platform delivery.

Working & Agile BAs Functional consultants QA & UAT professionals Product & project professionals Domain experts & career starters Future AI POs & FDEs

Prior experience: no coding required. You build enough data, API and RAG fluency to collaborate credibly with engineers — you’re assessed on whether your solution is valuable, clear, buildable, testable and governable, not on writing production code.

What you will be able to do

Specify the solution — and govern the AI inside it.

Elicit & model requirementsWorkshops, interviews, Power/Interest & RACI, BPMN maps, user stories and acceptance criteria.

Ship the document chainBRD, FDD and RTM with end-to-end traceability from stakeholder need to accepted outcome.

Use GenAI for BA workDraft, cluster, synthesise and review analysis artifacts faster — with human verification built in.

Qualify AI opportunitiesDecide when a rule, workflow, dashboard, GenAI feature or agent is the lightest sufficient solution.

Write the Agent SpecificationA complete 10-section Agent Spec: scope, tools, boundaries, HITL gates and escalation rules.

Design human-in-the-loop controlSet the autonomy dial, approval points and the conditions under which the system must stop and ask.

Prove it with evaluationVersioned evaluation sets, red-team reports, UAT and a defensible go / conditional-go / hold / no-go call.

Govern value after go-liveADKAR adoption, kill-switch and incident doctrine, AI register, value scorecards and conservative ROI.

Course curriculum

Twelve modules. One enterprise value lifecycle.

The Modern Business Analyst in an AI-Native Enterprise

Foundation

Build the operating model of a modern BA before entering solution work.

Topics

•What Business Analysis is & why organisations need it

•Traditional, Agile, Digital & Agentic BA

•BA vs PO, PM, Scrum Master, Solution Architect & FDE

•Application & product lifecycles

•Waterfall, Agile & Hybrid; Scrum & Kanban

•Outcome ownership vs document ownership

EvidenceRole & Responsibility MapDelivery-Approach Decision NoteDecision & Assumption Log

GenAI, Agentic AI & Enterprise AI Foundations for BAs

Develop a durable mental model for AI-enabled enterprise solutions.

Topics

•AI, ML, DL, Generative AI & LLMs

•Tokens, context windows, structured outputs, hallucinations

•Deterministic software vs probabilistic AI

•Agent anatomy: model, instructions, context, memory, tools, policies, feedback

•RAG & enterprise grounding; APIs & tool execution

•Assist → Bounded Autonomy; HITL / HOTL / HIC; MCP & A2A awareness

EvidenceBA Prompt LibraryGenAI vs Agentic BriefAgent-Anatomy DiagramAutonomy Recommendation

Enterprise Discovery & Stakeholder Intelligence

Hands-on

Move beyond the first feature request and discover the actual operating problem.

Topics

•Discovery purpose, scope & entry criteria

•Stakeholder registers incl. AI actors as digital workers

•Power–interest, influence–impact & AI-aware RACI

•Personas, empathy maps, JTBD & agent capability profiles

•Interviews, laddering, Five Whys, contextual inquiry

•Trust-calibration questions, never-do rules & boundaries

EvidenceStakeholder RegisterAI-Aware RACIPersona + Agent Capability ProfileDiscovery Synthesis

Problem Framing, Outcomes & AI Opportunity Prioritization

Convert discovery evidence into a measurable and defensible opportunity.

Topics

•Symptoms vs root causes; problem & opportunity statements

•Current-state baselines, objectives, OKRs & KPIs

•Automation suitability: rules, workflow, RPA, analytics, ML, GenAI, agents

•AI Opportunity Canvas & Autonomy & Escalation Canvas

•Value–feasibility–risk scoring; MoSCoW, WSJF, RICE, Kano

•Crawl–Walk–Run roadmaps & portfolio sequencing

EvidenceProblem Statement + KPI BaselineOutcome TreeAI Opportunity CanvasAutonomy & Escalation CanvasRoadmap

Process Analysis & Human–AI Workflow Design

Hands-on

Understand how work actually happens, redesign it, then decide where agents belong.

Topics

•Process-analysis principles & SIPOC

•BPMN 2.0: swimlanes, handoffs, gateways, events

•An explicit lane for the AI agent

•Value Stream Mapping, DOWNTIME waste, Fishbone, Pareto

•As-Is & To-Be; eliminate–simplify–standardise–automate–delegate–elevate

•Single-agent, router, planner–executor & reviewer patterns; approval gates

EvidenceSIPOCAs-Is BPMNValue Stream MapTo-Be BPMN w/ Agent Lane & HITL GatesTask-Decomposition Matrix

Agile Requirements, Backlogs & Agent Specifications

Translate business understanding into a complete, traceable solution contract.

Topics

•Business, stakeholder, solution & transition requirements

•Epics, features, user stories; 3Cs & INVEST

•Given–When–Then + negative, permission, boundary, exception criteria

•Deterministic acceptance vs behavioural AI criteria

•The full 10-section Agent Specification; tool contracts & permissions

•RAG requirements: sources, freshness, permissions, citations, fallback

EvidenceLean BRDFR/NFR CatalogueUser-Story Backlog10-Section Agent SpecRequirements Traceability Matrix

Data, Integration & Solution Literacy for BA–FDE Collaboration

Hands-on

Enough technical fluency to collaborate credibly with engineers and FDEs.

Topics

•Systems of record, engagement, intelligence & action

•ERDs, data dictionaries, quality, lineage & master data

•SQL concepts for analysis & validation

•APIs, endpoints, methods, status codes & JSON

•REST, webhooks, events, queues; OAuth, service accounts, RBAC

•RAG source/ingestion/chunking/retrieval/permission/citation architecture

EvidenceAnnotated ERDData DictionaryIntegration InventoryInterface ContractTechnical-Refinement Checklist

Prototyping, Conversational UX & Walking Skeletons

Make assumptions visible before full development.

Topics

•Sketches, wireframes, mockups & interactive prototypes

•Figma awareness; traceability wireframe → requirement

•Conversational & agentic UX; approval queues & escalation inboxes

•Confidence, rationale, citations & action previews

•Suggested / approved / executed states; boundary cards & activity feeds

•Thin walking skeleton; representative & adversarial inputs; planted-error drills

EvidenceAnnotated WireframesClickable FlowHITL UX SpecificationBoundary CardWalking-Skeleton Run Log

Testing, UAT, Evaluations & AI Safety

One unified quality approach for deterministic apps and probabilistic AI.

Topics

•Shift-left quality, test levels & the test pyramid

•Cases from acceptance criteria; happy, negative, boundary, exception

•UAT planning, execution & sign-off

•Versioned eval sets, data cards; normal, edge, adversarial, fairness slices

•Deterministic, human & LLM-as-judge graders; prompt injection & tool misuse

•Planted-error supervision UAT, catch-rate & action-specific autonomy sign-off

EvidenceTest & UAT PlanVersioned Evaluation SetRubric & Grader DesignRed-Team ReportAutonomy-Level Sign-Off

Change, Trust, Training & Adoption

Hands-on

Prepare people to work safely and effectively with AI-enabled workflows.

Topics

•Why adoption determines value; change-impact assessment

•ADKAR as planning & diagnostic framework

•Sponsor, manager, champion & super-user roles; message houses

•Role-based training & 70–20–10; guides, job aids, microlearning

•Training users to supervise AI; approval / override / escalation drills

•Over-trust, under-trust & calibrated trust; adoption & sentiment metrics

EvidenceChange-Impact AssessmentADKAR PackCommunication MatrixSupervision Drill PackAdoption Scorecard

Go-Live, Observability, AgentOps & Production Support

Support progressive, observable and reversible deployment.

Topics

•Go-live as a business event; readiness across six dimensions

•Go, Conditional Go, Hold & No-Go; pilot, phased, parallel, shadow

•Deployment ladder: offline → shadow → limited → expanded → bounded

•Rollback & manual fallback; day-one runbooks & Super Care

•Logs, metrics, version-stamped traces; alert & drift design

•Full / degraded / scoped kill switches; Contain → Communicate → Diagnose → Correct → Learn

EvidenceReadiness BoardGo/No-Go RecordDeployment LadderKill-Switch SpecificationProduction Runbook

Value Realization, Governance & Continuous Improvement

Keep the solution valuable and controlled after go-live.

Topics

•KPI hierarchies & value scorecards; leading, lagging & trust metrics

•Feedback loops, benefits reviews & failure clustering

•ROI, TCO, conservative benefit claims & cost per successful task

•Governed releases, re-evaluation & autonomy promotion/reduction

•NIST AI RMF & ISO/IEC 42001 awareness; AI registers, owners & risk tiers

•Evidence chains, fleet-readiness & the pathway to AI Product Owner / FDE

EvidenceKPI & Value ScorecardConservative ROI/TCOGovernance ChecklistAI Register EntryEvidence Chain

Honest scope — each module builds analyst, consultant and platform-owner fluency with a working implementation slice and portfolio evidence; development and scripting depth belongs to the Forward Deployed AI Engineer bridge.

Tools you'll master

The analyst & consultant toolkit, one real engagement.

Real-time projects

You don't watch videos. You run engagements.

Three full-production projects, each threaded through the entire curriculum. By the project, you've built the whole stack around them.

Hero project

Digital Edify Agentic CRM — the continuous project

One enterprise scenario threaded through every module: run discovery workshops, map as-is/to-be BPMN, write the BRD/FDD/RTM chain, specify the agent, evaluate it, and defend a go/no-go — end to end on the Digital Edify Agentic CRM.

01Discovery pack — stakeholder map, as-is BPMN and problem frame with KPI baseline
02Traceable BRD / FDD / RTM chain from need to accepted outcome
0310-section Agent Specification with HITL gates and autonomy sign-off
04Versioned evaluation set, red-team report and a defended go/no-go in viva

BPMNBRD / FDD / RTMAgent SpecGo / No-Go

Enterprise

AI Opportunity & Autonomy Canvas

Qualify a candidate AI opportunity against value, feasibility and risk — score suitability, set the autonomy dial, and practice the judgment to defer or reject one that a rule or workflow serves better.

SuitabilityAI ReadinessBusiness CaseGuardrails

Design & prove

To-Be Human–AI Workflow & evaluation set

Redesign the process as a BPMN with an explicit agent lane, HITL approval gates and escalation triggers — then prove it with a versioned evaluation set, red-team report and UAT before recommending go-live.

Agent laneHITL gatesEval setRed-team

Project

Your implementation engagement in a controlled project environment.

Pick a real partner workflow. Run the engagement end to end — workshops, to-be design, backlog, UAT and a governed AI rollout plan — and defend it before a review panel.

Download the real world project

Full scope, sample deployment contexts, project milestones, and grading rubric — PDF, 14 pages.

Production-style capstoneCareer support included

Your instructor

Taught by engineers who shipped agentic AI to production.

Manikanta Kona

Founder, Digital Edify · Enterprise AI Architect

Enterprise AI · Agentic solutions · Requirements & evaluation · Governance

"An agent in production is where analysis earns its keep — the spec, the guardrails and the evaluation evidence are what separate a demo from a deployment. That judgment is what we teach."

Enterprise

AI PLATFORMS

100K+

ALUMNI COMMUNITY

4.8 /5

AVG. CLASS RATING

Manikanta is the founder of Digital Edify and brings 15 years of enterprise platform architecture from AT&T, Salesforce, Cox Communications, and Broadcom — where he led enterprise platform and AI rollouts for Fortune-500 banks, telcos, and insurers. Most recently he architected production agentic-AI deployments that replaced traditional triage tiers with autonomous case-handling.

His classes get you two things other programs don't give you: a founding architect who's shipped enterprise AI from inside the Fortune 500, and a curriculum updated monthly — so when hiring managers ask about agent specs, evaluation sets or HITL design, you've already built it. M.S. in Engineering, Purdue University.

Ravi Krishna

Chief Technologist, Digital Edify · Implementation & Delivery Lead

Discovery workshops · BPMN · BRD / FDD / RTM · UAT · Delivery governance

"Implementations don't fail in configuration — they fail in discovery. Workshops that surface the real process, requirements developers build without rework, and UAT that proves it: that's what I teach."

10 yrs

IMPLEMENTATION & DELIVERY

1,000+

HIRING PARTNERS

4.8 /5

RATING

Ravi is Chief Technologist at Digital Edify, where he leads the implementation and delivery practice. After years running enterprise transformation programs, he now teaches the analyst's craft — discovery engagements run phase by phase, process workshops that get to real decisions, and UAT that stands up in front of a steering committee.

His delivery modules are built from real engagement post-mortems, not slide decks. Expect to leave with working workshop kits, requirement and UAT templates, and a delivery-governance playbook you can run on day one.

HIRING PARTNERS · INDUSTRY VOICES

What employers say about Digital Edify grads.

Real feedback from talent leaders at the enterprise partners hiring our AI-native BA graduates.

Digital Edify graduates bring practical portfolio evidence and a structured approach to AI-enabled delivery.

Aakash Mehta, Partner Programme Lead

We've worked with Digital Edify alumni who bring useful project context and evidence-led delivery practices.

Anita Sharma, Senior Manager, Deloitte

The BA programme is comprehensive — discovery, specification, plus AI agent evaluation. Grads come pre-trained for enterprise.

Rahul Bhatt, Solutions Lead, Mphasis

Their BA track produces analysts who write production-grade specifications and evaluation flows on day one. Genuinely rare.

Deepak Pillai, Senior Architect, TCS

What sets Digital Edify apart is the agent-specification layer baked into the BA track. Our enterprise clients ask for exactly this profile.

Suresh Menon, Practice Lead, Accenture

Their BA fundamentals are rigorous, and the capstone with real workshop artifacts is what closes interviews for us.

Vikram Iyer, Director, Infosys

Digital Edify's BA grads get requirements to accepted twice as fast in the first 90 days. Our internal metrics back this up clearly.

Lakshmi Nair, VP Engineering, Wipro

Best BA + AI Agents pipeline we've sourced from in India. Their projects are production work, not toy code.

Karthik Subramanian, Engineering Director, Cognizant

Strong discovery and process foundation. Their graduates bring useful project context to enterprise engagements.

Arun Joshi, Practice Director, Capgemini

We've worked with Digital Edify alumni across analytics and AI delivery teams, where practical fundamentals and clear evidence matter.

Sanjay Verma, Talent Director, IBM

ITOM + Predictive Intelligence is exactly the talent gap we've been struggling to close. Digital Edify is filling it for us reliably.

Anjali Desai, Practice Head, LTIMindtree

Their BA track delivers analysts who navigate discovery, specification and evaluation on customer engagements unsupervised.

Ramesh Iyer, Senior Manager, Tech Mahindra

Digital Edify graduates have joined digital delivery teams with practical analysis, process and agent skills.

Geetha Pillai, Talent Acquisition Lead, Cyient

Digital Edify grads who blend agent specification with evaluation evidence land production-ready on day one. Rare combination, well-trained.

Priya Reddy, Talent Lead, Microsoft

Program certifications

An Agent‑Ready credential, not a participation trophy.

Digital Edify · Institute Certificate

Modern Business Analyst with GenAI & Agentic AI

Presented to

Spandana Bala

For successfully specifying, evaluating and governing a deployment-ready human–AI solution — discovery, BRD / FDD / RTM, a 10-section Agent Specification, versioned evaluation set and a defended go/no-go — on the continuous Digital Edify Agentic CRM project, awarded on a defended portfolio and viva.

Manikanta Kona

CEO · Digital Edify

AGENT
READY
2026

Skills-focused institute credential

Five stackable phase certificates plus the final Modern BA credential — named to the specific artifact chain you built and defended path — names that hiring managers already scan for on resumes.

Project artifact included

Every certificate carries your project name, the partner org, and a link to the deployed agent-specification artifact — proof, not a promise.

Enhanced skill validation

Graded on the artifact chain: discovery, specification, agent spec, evaluation deployment, safety and monitoring. No pass/fail — a level 1‑5 band.

Verifiable on a public URL

Each credential has a public verification page recruiters can check in 10 seconds — no PDF back‑and‑forth.

Job roles

Roles this program prepares you for.

Business Analyst (GenAI) Elicit, model and validate requirements with AI-accelerated discovery and documentation.

AI Business Analyst Specify, evaluate and govern AI-enabled solutions — agent specs, eval criteria, guardrails.

Sr / Lead Business Analyst Own discovery and traceability on major programs; mentor analysts on AI-native practice.

Product Analyst Turn product questions into evidence — funnels, adoption, experiment design and insight.

AI Product Owner (path) Backlog ownership, acceptance criteria and value measurement for AI-enabled products.

Functional Consultant Run discovery and process design on enterprise platform engagements — vendor-neutral.

Process Lead / Process Analyst Own BPMN process architecture and the human–AI redesign of core workflows.

UAT / Business Acceptance Lead Design acceptance evidence, run UAT and sign off go / no-go with confidence.

Change & Adoption Specialist ADKAR-based adoption, training users to supervise AI, and value tracking after go-live.

Forward Deployed AI Engineer (bridge) The technical bridge route — add Python, SQL, APIs and cloud to become an FDE.

What employers should see in your portfolio: that you can take an engagement from discovery to value — map the process, write requirements developers build without rework, run the workshop, accept against criteria, and govern AI use cases with guardrails and metrics.

Job placement support

Your first BA offer isn't a lottery ticket. It's a built process.

GitHub, LinkedIn, resume — and most importantly, warm intros into our enterprise hiring partners. Our placement team works your search like an account, not a helpdesk.

01 / PORTFOLIO

A portfolio, not a graveyard.

Guidance on assembling a consulting portfolio — process maps, workshop artifacts, backlog and UAT evidence, and your AI rollout plan — reviewed 1:1, not via template.

02 / RESUME PREP

Rewrite, don't proofread.

A one-page resume rebuilt around the artifact chain you shipped, the agent you deployed, and the business outcome. Reviewed against role-relevant portfolio and interview criteria.

03 / LINKEDIN + INTROS

Where most opportunities actually live.

Profile tuning plus direct warm introductions into our hiring-partner network — Infosys, TCS, Deloitte, Accenture, Cognizant, NTT Data, Capgemini. You leave with recruiter contacts, not a generic "good luck."

BA alumni

Hundreds of BA careers launched — here are eight.

Spandana Bala

AI Business Analyst

Hyderabad · India

Now at · Infosys

Naveen Vedala

Business Analyst

Hyderabad · India

Now at · TCS

Tejashwini Addla

HRSD Specialist

Hyderabad · India

Now at · Deloitte

Tharunesh Dillikar

Lead Business Analyst

Seattle · United States

Now at · Accenture

Mujahed Mohammed

Sr Business Analyst

Hyderabad · India

Now at · Accenture

Bhargav Kumar Murala

Business Analyst (GenAI)

Hyderabad · India

Now at · Capgemini

Sai Manasa Leburi

ITOM Engineer

New York · United States

Now at · NTT Data

Rahul Dhamma

AI Product Analyst

Hyderabad · India

Now at · Cognizant

Our locations

Come chat with us — over coffee, or over Zoom.

One flagship campus in Hyderabad, plus online classes running on Indian and US timezones.

Flagship campus

Hyderabad

2nd Floor, Hitech City Road · Above Domino's · Opp. Cyber Towers, Jai Hind Enclave · Hyderabad, Telangana

Call

+91 8142998866

US desk

+1 256 388 7766

Hours

Mon–Sun · 7 AM–9 PM

Online class

Global

Weekend and evening classes running on IST and PST. Every online class ships the same continuous Agentic CRM project, review gates and final viva as the on‑campus track.

Timezones

IST & PST

Format

Live + 1:1 mentorship

Admissions

ENROLLING NOW

FAQ

Questions we actually get — answered honestly.

Straight answers on prerequisites, the platform, certifications, and placement. If something's missing, book a 20-minute advisor call — no slides, no pitch.

Do I need a technical or coding background?+

No. There is no production-coding prerequisite. You build enough data, API and RAG fluency to collaborate credibly with engineers and FDEs — you’re assessed on whether your functional solution is valuable, clear, buildable, testable and governable, not on writing production code. An optional foundational phase supports learners who want extra business, data and technology literacy first.

Isn’t this just a documentation-heavy BA course with "AI" bolted on?+

No — that’s the whole point of the distinction. Beyond using GenAI to do BA work faster (Job 1), you learn to be the BA for an AI solution (Job 2): discovering, qualifying, specifying, validating and governing agent behaviour. Job 2 is the durable differentiator, and most of the program lives there.

Do I actually specify agents, or is it theory?+

You produce the artifacts. Across the program you write a complete 10-section Agent Specification, design a To-Be workflow with an agent lane and HITL gates, build a versioned evaluation set with a red-team report, and make a real go / conditional-go / hold / no-go recommendation with an autonomy sign-off — all on the continuous Digital Edify Agentic CRM project.

What’s the time commitment?+

Cohort schedules and expected weekly commitment are confirmed by an advisor before enrolment.

Will I get a certificate recruiters care about?+

You earn five stackable phase certificates plus the final Modern Business Analyst with GenAI & Agentic AI credential — awarded on a defended portfolio and viva, not a multiple-choice quiz. The credential names the specific artifact chain you built, which is exactly the evidence hiring managers and FDE squads ask to see.

Can this lead to AI Product Owner or Forward Deployed AI Engineer roles?+

Yes. This is the functional and analytical pathway into the FDE ecosystem — you graduate strong in discovery, opportunity qualification, workflow, specification, evaluation and value. Progression to AI Product Ownership is direct; the FDE route adds a technical bridge (Python, SQL, APIs, Git, cloud). We’re honest that the course alone doesn’t make you a production AI/Data/DevOps engineer — those need the corresponding specialist track.

Online, weekend, or on-campus?+

All three. On-campus in Hyderabad; live online cohorts with recordings through the Digital Edify LMS; and weekend cohorts for working professionals. Every format runs the same continuous project, review gates and final viva.

What if I fall behind?+

We’d rather pause your cohort than push you through. You can freeze your seat and rejoin the next cohort without paying again, and artifact clinics run every week for anyone who needs to catch up on a deliverable.

How does this differ from an IIBA or CBAP certification?+

A CBAP-style credential certifies knowledge of a body of knowledge. This programme is built around producing artifacts: a discovery pack, a BPMN model, an Agent Spec, a human-control design, an evaluation set and an acceptance record. It complements a knowledge certification rather than replacing it, and we make no claim of equivalence.

Do I need to be technical?+

No production coding is required. You do need enough fluency in data, APIs, retrieval and evaluation to specify agent behaviour and challenge an architect’s answer. An optional foundational phase covers that literacy first if you want it.

What comes after this programme?+

The designed next rung is AI Product Owner, where you move from producing evidence to deciding what gets funded and how much autonomy it earns. Some analysts instead go deeper into Quality Engineering, or across into Forward Deployed AI Engineering.

Is the credential accredited or a regulatory qualification?+

No. It is a Digital Edify programme credential — not an external licence, a certification equivalence or a regulatory approval. It states what you built, defended and were graded on, verifiable on a public page.

Still have a question? Talk to an advisor — no slides, no pitch.

One million AI‑native professionals by 2027.
Let's put you in that number.

Book a 20‑minute advisor call. We'll map your current role to the right program, talk honestly about timelines, and walk you through a real class's project.

Modern Business Analyst with GenAI & Agentic AI

What does a modern Business Analyst do?

“Using AI as a BA” and “being the BA for an AI solution” are different jobs.

Built for people moving into AI platform delivery.

Specify the solution — and govern the AI inside it.

Twelve modules. One enterprise value lifecycle.

The Modern Business Analyst in an AI-Native Enterprise

GenAI, Agentic AI & Enterprise AI Foundations for BAs

Enterprise Discovery & Stakeholder Intelligence

Problem Framing, Outcomes & AI Opportunity Prioritization

Process Analysis & Human–AI Workflow Design

Agile Requirements, Backlogs & Agent Specifications

Data, Integration & Solution Literacy for BA–FDE Collaboration

Prototyping, Conversational UX & Walking Skeletons

Testing, UAT, Evaluations & AI Safety

Change, Trust, Training & Adoption

Go-Live, Observability, AgentOps & Production Support

Value Realization, Governance & Continuous Improvement

The analyst & consultant toolkit, one real engagement.

You don't watch videos. You run engagements.

Digital Edify Agentic CRM — the continuous project

AI Opportunity & Autonomy Canvas

To-Be Human–AI Workflow & evaluation set

Your implementation engagement in a controlled project environment.

Taught by engineers who shipped agentic AI to production.

What employers say about Digital Edify grads.

An Agent‑Ready credential, not a participation trophy.

Roles this program prepares you for.

Your first BA offer isn't a lottery ticket. It's a built process.

A portfolio, not a graveyard.

Rewrite, don't proofread.

Where most opportunities actually live.

Hundreds of BA careers launched — here are eight.

Come chat with us — over coffee, or over Zoom.

Questions we actually get — answered honestly.

One million AI‑native professionals by 2027.Let's put you in that number.

Get Skilled

One million AI‑native professionals by 2027.
Let's put you in that number.