AI automation and commercialisation assistance: use-case validation, prototype and MVP development, business workflow integration, evaluation and rollout planning.
What must be true for your pilot to become a viable product or operating capability? Use-case and commercial assumptions; Evaluation and human-review criteria; Pilot milestones and release readiness
A convincing AI demonstration does not establish a viable product or dependable business process. The next questions concern user value, data access, output quality, exception handling, cost and adoption. This engagement connects the use case with a staged delivery plan: test feasibility, build a focused prototype, evaluate it against representative tasks and determine what is needed for a pilot or commercial release. The approach can support an internal workflow or an AI-enabled product intended for customers.
You have an AI idea or proof of concept but need a practical route to an MVP. A team wants to automate document processing, knowledge retrieval or another repeatable workflow. A prototype works in a demo but lacks integrations, evaluation or operating controls. You need to assess user demand, delivery costs and commercial assumptions before a larger investment.
Define the user problem, baseline, success criteria and business assumptions. Compare AI with simpler automation and assess data availability, likely costs and adoption dependencies.
Select an approach and define a bounded prototype or MVP. Explore retrieval, document extraction or assisted workflows where appropriate, with human review and fallback paths.
Test representative tasks for quality, reliability, latency and cost. Review permissions, data handling and failure cases; connect the agreed solution to authorised business systems.
Plan a controlled pilot, feedback collection and monitoring. For customer-facing ideas, assess onboarding, pricing assumptions and delivery economics before agreeing the next release stage.
A use-case and feasibility assessment with a go/no-go recommendation. A prototype or MVP for the agreed stage and user journey. An evaluation report covering quality, limitations and operating cost assumptions. A pilot or commercial-release roadmap with ownership, controls and next milestones.
A description of the AI idea, intended users and target business outcome. Any existing prototype, process map or product requirements. Representative non-sensitive examples and a summary of data availability. Expected volumes, integrations, deployment constraints and budget parameters.
Submit a short enquiry about your organisation, intended outcome and timetable. Our team reviews the mandate. Responsible professionals, deliverables and fees are agreed before work begins.
Evaluate user value, solution quality and release readiness as you move towards commercial use.
Define the user, the current workflow and a measurable intended outcome. Compare AI with simpler automation before committing to a build. Potential engagement output: A bounded use case, success criteria and a feasibility recommendation.
Evaluate representative tasks, failure cases, latency and operating costs; make human review and fallback paths explicit. Potential engagement output: An evaluation report with limitations and cost assumptions.
Connect integrations, permissions, onboarding, monitoring and feedback to a pilot or commercial-release plan. Potential engagement output: A staged release roadmap with owners and the next decision points.
Test user value, build a bounded solution and evaluate the operating case before a wider launch.
Define the user problem, baseline and success criteria; assess data access, adoption assumptions and whether AI adds value over simpler automation. Potential engagement output: A feasibility assessment and go/no-go recommendation.
Prototype scoped document extraction, retrieval or assisted work, with integrations, permissions, human review and fallback paths designed into the journey. Potential engagement output: A bounded prototype or MVP for the agreed user task.
Test representative tasks and failure cases for quality, latency and operating cost; document limitations before deciding whether to expand the pilot. Potential engagement output: An evaluation report and transparent cost assumptions.
Connect onboarding, monitoring, feedback and pricing assumptions to a controlled pilot and the next commercial or internal release milestone. Potential engagement output: A release roadmap with owners, controls and decision gates.
A connected workspace for structured preparation, validation, review and batch filing workflows. Delivery capability demonstrated: Business-rule modelling, document controls and portal workflows.
Software connecting confirmation requests, responses, follow-up and reconciliation. Delivery capability demonstrated: External collaboration, response tracking and reconciliation design.
A workspace that brings tax notices, important dates and related actions into an organised review process. Delivery capability demonstrated: Operational monitoring, information organisation and review workflows.
A desktop signing tool that supports digital-signature workflows alongside portal filing. Delivery capability demonstrated: Desktop software and the connection between application and filing tasks.
AI-assisted document reading and guided form preparation, with explanations for professional review. Delivery capability demonstrated: Document extraction, assisted user journeys and human review of AI output.
Tenured Chartered Accountants & Advocates. 15 years in practice, with experience across manufacturing, services, banking, insurance and logistics.
Vidhi AI within the remittance workspace is an existing example of assisted document and form workflows. It connects document reading, suggested information and explanations with professional review. The wider WrapTax portfolio supplies the application context around that AI capability.
Document reading and extracted information connected to a defined preparation task.
Suggestions and explanations presented for a professional to assess before proceeding.
AI assistance placed inside an existing user journey, alongside records and review responsibilities.
Supply chains, capital investment & intercompany arrangements. India expansion and investment structures; Related-party supply and service arrangements; Finance workflows and document controls
Cross-border delivery, operating models & scalable processes. International contracts and payment flows; Group service models and transfer pricing; Workflow automation and AI use-case assessment
Transaction readiness, documentation & controlled operations. Transaction tax and diligence workstreams; Documented approval and reporting workflows; Technology integration with human review
Evidence, reporting & process governance. Tax exposure and transaction documentation; Reporting and reconciliation workflows; AI-assisted document handling with review controls
International operations, service flows & connected systems. Cross-border operating arrangements; Intercompany services and documentation; Operational data and workflow integration
% of 2026 survey respondents · separate questions. Improved own productivity: Share of respondents 80.0; Positive enterprise EBIT impact: Share of respondents 37.0. Separate self-reported measures from a survey of 1,719 participants in 97 nations. EBIT means earnings before interest and taxes.
An AI idea needs an economic case, evaluation criteria and integration into a real workflow. Which business measure would tell you that your AI pilot deserves to scale?
9 October 2026
Yes. Feasibility and use-case definition can be a standalone first stage, before a prototype or full product is commissioned.
A review can identify gaps in the user journey, evaluation, integrations, costs and controls, followed by an agreed MVP or pilot scope.
No. Discovery compares AI with rules, integrations and conventional automation. The proposed approach should fit the task, available data and acceptable level of risk.
McKinsey State of AI 2026 · Published 25 August 2026 · survey May–June 2026