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Enterprise AI · industry benchmarks

Seven situations where AI kickstarts company growth.

Support, sales, documents, data, reports, notes, onboarding - concrete situations where companies worldwide are already scaling with AI agents and assistants today. The same path is open to you, whatever your company's size.

01 · Customer support

Support is drowning in repeat tickets.

Every new customer means more emails, tickets, calls. Hiring people in step with growth is expensive and slow - and most questions are the same ones, over and over. An AI agent connected to your knowledge base resolves most routine questions itself, 24/7, and only hands people what genuinely needs judgment.

Klarna: 853 FTE saved, $60M/year
02 · Sales & leads

Sales reps have more leads than they can handle personally.

Either communication gets personalized by hand (and falls behind), or it goes out en masse with no effect. Both cost conversions. AI drafts a relevant, tailored message for every lead at scale - the rep just closes the last step.

JPMorgan: +20% gross sales in a targeted campaign
03 · Contracts & documents

Reviewing contracts and invoices eats time and causes errors.

Contract review, extracting data from invoices, finding a specific clause across thousands of documents - work nobody enjoys, where human error costs money. AI reads the document, understands the context and extracts exactly what you need, an order of magnitude faster than a human.

JPMorgan: 360,000 hrs/year saved, -80% error rate
04 · Data & decisions

You have demand data, but still decide by gut feeling.

The company has an ERP, a warehouse, order history - but planning is still done by a person with a spreadsheet. The result: either overstock or stockouts. A dedicated data platform connected to AI predicts demand and proposes decisions automatically, in real time.

General Mills: over $20M/year in supply chain savings
05 · Reports & presentations

Managers spend hours preparing materials instead of deciding.

Before you even get to the decision, the team spends a day compiling numbers into slides. AI assembles a report or presentation from data almost instantly - the human just handles the conclusion and the next step.

JPMorgan: presentation prep cut from hours to 30 seconds
06 · Notes & documentation

After every call or meeting, someone manually writes it up.

Classic tedious work - logging a CRM entry after a sales meeting, documentation after a client consultation. The employee knows what was said, but writing it up takes extra time and often slips or gets skipped. An AI agent records the call, summarizes it and files it straight into the CRM or system - no manual step.

Morgan Stanley: 98% voluntary adoption among advisors
07 · Onboarding & know-how

New hires ramp up slowly, know-how lives in a few veterans' heads.

Internal policies, procedures, product documentation exist, but are scattered across shared drives, wikis and people's heads. An internal AI assistant (RAG over your company knowledge base) answers employees instantly and accurately, with a source reference.

Industry data: -30 to -40% time spent searching for information

Figures come from publicly published case studies (Klarna, JPMorgan, General Mills, Morgan Stanley, UNIQA and others) - industry benchmarks, not our own engagements. They show the direction the market is moving; the absolute gain for a smaller company will differ, the principle won't. Real, anonymized references from our own work are on the References page.

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