Industry
Industrial and consumer goods manufacturers: quality, maintenance, engineering knowledge, procurement and after sales service.
13 organizations in 9 countries run these use cases in public. 73% of those 15 deployments disclose a measurable outcome.
An assistant for procurement and vendor management that reads supplier contracts and proposals, extracts the key terms, flags deviations from the organization's standard positions, drafts requests for proposal and evaluation matrices, and prepares negotiation positions, with a procurement or legal owner approving every conclusion.
Machine learning and conversational analytics, offered by some banks inside their cash management platforms, that categorise a company's cash flows, forecast positions across accounts and currencies, and answer treasurers' questions in plain language, so the treasury team decides on funding and idle balances with better information and less spreadsheet work.
A generative AI assistant for the people who run and repair machines in plants, workshops and service centres: it answers fault and procedure questions from equipment manuals, fault reports, shift logs and live machine data, in the technician's language, with links to the sources, so faults are diagnosed faster and expert knowledge is not lost when experienced staff retire.
AI that takes documents in any format, such as scanned forms, PDFs, photos, emails and handwritten notes, splits and classifies them, extracts the required fields with a confidence score, validates them against business rules and source systems, and sends only the uncertain cases to a person before the data enters the downstream process.
AI that reads remittance advices in many formats, matches incoming customer payments to open receivable invoices, proposes deduction and short pay reason codes from prior resolutions, and routes only the genuine exceptions to a cash application analyst, so the accounts receivable sub ledger clears itself for the clean majority of payments.
Generative AI that helps learning and development teams turn source material such as procedures, product documentation and policies into training: course outlines, lesson text, quizzes, narration, avatar videos and translations, which instructional designers and subject matter experts review before publishing.
AI that reads every piece of free text customer feedback, such as survey verbatims, NPS comments, reviews, social posts, chat and call transcripts, and turns it into themes, sentiment, drivers and suggested actions that a named owner can act on, so the organization hears all of its customers instead of a sample.
An internal platform that uses AI to infer employees' skills and interests and recommend short term projects, open roles, mentors and learning to them, while showing managers which employees fit an opportunity, so that work is staffed from inside before hiring or contracting externally.
AI that translates and adapts an organization's commercial content, such as campaigns, emails, product pages, help content and websites, for each market and language, using the brand's glossary, style guide and past approved translations, and routes the output to human linguists and local marketers for review in proportion to how visible and risky the content is.
Machine learning that learns the normal behaviour of industrial and energy equipment from sensor and process data, flags early signs of degradation weeks or months before a failure, and turns them into prioritised maintenance work, so plants and utilities plan repairs instead of reacting to breakdowns.
AI that inspects every unit on a production line, from camera images, sound or machine process data, to find defects, missing parts and wrong variants in real time, and routes the few anomalies it flags to a quality inspector instead of relying on manual sampling at the end of the line.
AI that turns what a customer sends, such as a product list, a drawing, a roof photo or a request for quotation, into a draft quote: it reads the input, matches items to the catalog, calculates quantities and applies the organization's price rules, and hands the draft to a seller or estimator who checks and sends it.
AI for sales teams that analyses sales calls and meetings against the team's own sales method to coach sellers and their managers, and writes the call summary, next steps and opportunity updates into the CRM for the seller to confirm. Its purpose is winning deals and building selling skill, not the regulated advice record or general meeting notes.
AI that reads purchase orders, invoices, card transactions and contracts and assigns each line of spend to a category in the organization's taxonomy, and to the right supplier, so that procurement can see what is bought, from whom and where to consolidate or negotiate.
A governed register of every AI system and model an organization builds, buys or uses, with its owner, purpose, data, risk tier and approval status, kept current by AI that discovers unregistered use, reads the documentation and assembles the evidence a board, auditor or supervisor asks for.
Free PDF playbook
15 use cases with deployments, value, playbooks and governance, in one document for your team.
Computed from the 15 public deployments behind these use cases at manufacturing organizations. Numbers update with every checked record.
Bosch Digital, Carlsberg Group, DeAcero, Georgia-Pacific, Keurig Dr Pepper, Mattel, Pegatron, Prysmian, Pupuk Indonesia, Sandvik Coromant, Schneider Electric, Textron Aviation, Unilever.
43 public deployments at 39 organizations outside manufacturing run these use cases too. They are not counted in the numbers above; each use case page shows them.
