Before we get into the AI side of things, I’d love to hear more about what you do. Understanding the business helps us figure out where AI will actually move the needle — and, just as importantly, where it won’t.

We want to understand your starting point. Are there tools people are using every day, tools that got abandoned after week one, or are you mostly starting fresh? If you’ve had false starts, that’s actually useful — it tells us what won’t stick in your culture. It would also help if you could share any existing AI policy, training materials, or internal guidance you’ve already put out.

We want to know whether we’re designing for people who’ll happily build a prompt library, or for people who need something that feels like the tools they already use. This shapes tool selection, training depth, and how we sequence rollout.

The most useful way to answer this is in specifics — a report that takes a week, an inbox nobody can keep up with, content production bottlenecking marketing, a sales team rebuilding the same deck every month. Specifics beat generalities here, and they tell us where to look first.

This might be customer support, report generation, content creation, sales outreach, internal knowledge search, document processing, onboarding, finance close — or something else entirely. We’ll pressure-test which of these are actually good AI candidates versus which need process fixes first.

Think CRMs (Salesforce, HubSpot), communication (Slack, Teams, email), document storage (Google Drive, SharePoint, Dropbox), finance (QuickBooks, Xero), or industry-specific platforms. We’re assessing integration complexity and data readiness here — and flagging early if anything will need IT or security involvement.

Especially relevant if you handle personal data, financial data, health data, or work in a regulated industry. A lot of clients ask us to draft or refresh their AI governance policy as part of the engagement — we can roll that into scope if useful. Also worth knowing: has anyone on the team raised concerns about employees using AI tools informally?

If AEO/GEO is on the table, we’ll want a sense of content volume, current SEO posture, and whether you’re already showing up in Google AI Overviews, Perplexity, ChatGPT Search, or similar. If not on the table, you can keep this brief — we’re mostly checking whether there’s documented knowledge we could draw on for internal AI tools.

This helps us scope format, cadence, and whether we’re building one-time enablement or a longer upskilling program. In our experience, change management matters more than the tools themselves — so we’d also want to know how your team typically adopts new tools and whether there’s an internal champion.

AI ROI can be fuzzy, so we like to name success early. Is it hours saved per week per team member, faster turnaround on a specific deliverable, reduced vendor spend, doubled content output, faster response times, fewer manual handoffs? Naming the metric upfront keeps the engagement honest — and gives us something concrete to report against.

Our engagements range from short rapid implementations to multi-month strategic programs. We’ll tailor phasing based on your timeline and where you want the first visible result — most clients appreciate having a concrete win landed in the first 30 days, even on longer programs.

We don’t work from fixed packages — pricing depends on scope, team size, and whether training or custom builds are involved.

The next step after today is usually a scoping conversation with recommendations and approach. If there are budget holders, operational leads, or IT/security folks who should weigh in before anything moves forward, I’d recommend pulling them in for that call.

I think I’ve covered everything I wanted to go through today — is there anything else we haven’t touched on that you had questions about, either about AI for your business or about what it’s like working with us?