INSIGHTS
AI in business, in practice.
Concrete guides for leadership and teams: where to start, what to hand over to AI, how to stay in control. No figure without a source.
REFERENCE GUIDES
METHOD · 5 articles
Method and steering.
- AI without a technical team: what your company can already doMany companies have no data scientists or developers available for AI. That is no obstacle to getting started, as long as you separate what your business teams can do alone from what needs support.
- Deploying AI in your company: a four-step methodYour teams already use AI, each in their own way. Deploying AI in your company means turning that into team use, connected to your tools and governed by clear rules.
- Connecting AI to your ERP and CRM: connectors, APIs, MCPWithout a connection to your software, AI works blind and your teams copy and paste. There are three ways to connect it to the ERP and CRM: connectors, APIs and MCP. The choice is made with the IT department, one use case at a time.
- First AI use case: where to start, depending on your industryYour first AI use case sets the tone for everything else. Chosen well, it shows your teams what AI is good for; chosen badly, it joins the list of tests that went nowhere.
- Measuring the ROI of AI in your company: the methodThe ROI of AI isn’t found in a market study; it is measured in your own company. The method comes down to three elements: a baseline, verified gains and full costs.
FUNCTIONS · 16 articles
By function.
- AI in customer service: responses prepared, advisors in controlAI doesn’t replace your advisors: it prepares their work. It sorts requests, finds the customer’s file and drafts a response that the advisor reviews, corrects and sends.
- AI voice agents and phone reception: use cases and rulesAn AI voice agent answers the phone in natural language, captures the request and routes the caller. Well framed, it organizes reception without making it impersonal; poorly framed, it exasperates your customers.
- AI and CRM: an up-to-date sales pipeline without manual data entryA CRM is only useful if it is up to date, and it rarely is, because data entry costs salespeople time. AI can capture information where it originates and propose the update: the salesperson approves in one step.
- AI and project management: tracking, risks and reporting prepared for youA project manager spends a good share of their time collecting information and putting it back into shape. AI can handle that consolidation and flag drift; the project manager stays in control.
- AI in the supply chain: inventory, purchasing and suppliersPlanners and buyers spend much of their time gathering scattered information before they can decide. AI does this collecting and matching; they keep the decision.
- AI and cash management: forecasts, collections and customer remindersForecasting flows, identifying what has been paid, chasing what has not: cash management involves a lot of reading and matching. AI prepares this work; the finance department keeps the decisions and the payments.
- AI in accounting: reconciliations, payment reminders, closingIn accounting, AI is useful for the repetitive tasks that come before a decision: matching, checking, following up, preparing. The accountant keeps approval of every entry and every message sent.
- AI, invoicing and contracts: what AI checks before you doQuotes, invoices and contracts pass through many hands and few systematic checks. AI can review each document against your rules and flag discrepancies: a person makes the call.
- AI and business email: sort, prepare, follow upOverloaded shared inboxes, slow replies, forgotten follow-ups: email still takes up a large share of many teams’ time. AI can sort and prepare; a person reviews and sends.
- Document management and AI: find, check, classifyContracts, procedures, meeting notes, invoices: the information exists, but it is scattered across servers, inboxes and business tools. AI helps find it, classify it and check it, always citing its source.
- AI and B2B marketing: content, social media, editorial guidelinesAI writes fast, but generic content does not serve a B2B brand. What makes the difference: your teams’ expertise as raw material, written editorial guidelines, and a review before every publication.
- Customer onboarding and AI: complete files, faster startBetween signature and the first service delivered, a lot of time goes into missing documents, re-keying and back-and-forth. AI can prepare this work; your teams keep the sign-off on every file.
- AI for B2B sales prospecting: what works, what to avoidIn B2B prospecting, AI is useful for preparation: knowing the account, writing a relevant first message, keeping the CRM up to date. It becomes counterproductive when it is used to send more messages without reviewing them.
- Reporting and AI: dashboards that explain themselvesDashboards show what changed, rarely why. AI can write the commentary, answer questions in plain language and flag variances, provided every number comes from your tools.
- AI meeting minutes: decisions and action items that get followed upA useful meeting is judged by what happens afterward. AI can prepare the minutes, file the action items in your tools and remind everyone what was decided, provided you set a few rules.
- Competitive intelligence with AI: sources, summaries, alertsInformation about your competitors is public and plentiful; the time to read it is far scarcer. AI collects, sorts and summarizes; your teams analyze and decide what matters.
INDUSTRIES · 6 articles
By industry.
- AI in construction: tenders, job sites and documentsTender documents, technical proposals, site meeting minutes, subcontractor paperwork: a construction company runs on written documents. AI prepares this work; project managers and site managers decide.
- AI and e-commerce: catalog, customer service and visibility in AI answersAn online store lives on three things: an accurate catalog, responsive customer service, and customers who find it. AI helps with all three, provided a team reviews what is published and sent.
- AI for accounting firms: practical use cases, task by taskCollecting documents, reviewing entries, closing the books, answering clients: AI can prepare much of an accounting firm’s written work. Judgment, sign-off and advice stay with the accountant.
- AI in real estate: developers, property managers, investment companiesReal estate runs on documents: leases, deeds, plans, specifications, minutes, requests from tenants and buyers. That is where AI proves useful first, provided your teams keep the decision.
- AI for notaries and law firms: use cases and professional secrecyLegal professionals work on documents, under professional secrecy. AI can lighten research, document analysis and first drafts, provided the data stays within a controlled environment and the professional signs.
- AI for condominium managers and property management firmsOwner requests, general meetings, insurance claims, building works: condominium management runs on written documents, and time is short. AI sorts, finds and prepares; the property manager reviews and decides.
COMPLIANCE · 1 article
Rules and compliance.
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