AI Coaching · AI Prototypes · Automations · Product Consulting

AI for Your Business — Whatever Function You Run

AI is not one thing. What it means for a finance director is completely different from what it means for a marketing lead or an HR manager. The tools overlap, but the workflows, the data, and the decisions are yours.

Find your function: Finance · Accounting · Marketing · Sales · eCommerce · HR and Operations · Product

Read what AI can actually do there. If it resonates, the next step is an AI Discovery Session — 45 minutes focused on your business, ending with a written assessment of where AI fits and what to do next.

Together, let’s take an honest look at where AI fits.

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AI for Finance Teams

Finance teams sit on some of the most valuable data in any organization, and most of it is underused. Reports get built manually every month. Anomalies get caught late, or not at all. Explanations get written from scratch, reviewed, rewritten, and still end up inconsistent. The tools that were supposed to help — spreadsheets, ERP systems, reporting platforms — do their jobs, but they do not think. They do not flag what matters or surface what is buried.

AI changes that relationship with your data. Not by replacing the systems you already use — your ERP, your financial reporting platform, your business intelligence tools — but by sitting on top of them and making them more useful. An AI-powered dashboard can pull from your existing data sources and surface the numbers that actually need your attention, in plain language, before you have to go looking for them. An automation can monitor a workbook for anomalies and notify the right people with a structured prompt for a response, rather than waiting for a monthly meeting to surface the issue.

If your team is spending meaningful time on work that AI could handle — pulling numbers, formatting reports, chasing explanations, building the same table for the fourth time this quarter — that is where we start.

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AI for Accounting and Reporting

Accounting teams deal with a particular kind of repetition — the same data, the same formats, the same deadlines, every period. Month-end close. Reconciliations. Variance reports. Audit documentation. Each one follows a process that is well understood but time-consuming, and the margin for error is high because the stakes are high.

AI does not replace the judgment that accounting requires. What it does is handle the parts of the work that do not require judgment — the pulling, the formatting, the organizing, the first pass — so that the people on your team can focus on the parts that actually need their expertise.

Connected to your accounting platform — whether your team runs on QuickBooks, SAP, or another ERP — an AI automation can pull data, format it consistently, flag variances that exceed a threshold, and produce a structured summary ready for review. What used to take several hours of manual work becomes a starting point your team reviews and signs off on, rather than builds from scratch. The same applies to payroll reconciliation and expense management: rather than chasing receipts, cross-referencing reports, and assembling everything manually, an AI-powered workflow handles the routine steps and surfaces the exceptions that actually need a human decision.

This kind of work is where I start with most accounting and finance teams — not with a grand transformation, but with one specific process that is taking too long and producing inconsistent results. Fix that one thing well, and the next one becomes obvious.

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AI for Marketing Teams

Marketing teams are often the first to experiment with AI and the first to get frustrated with it. The tools are everywhere, the outputs are inconsistent, and the results rarely match the brand voice you have spent years building. Using AI well in marketing is not about prompting a tool and hoping for the best. It is about building a system — one that knows your voice, your audience, and your standards — and then running it with discipline.

There is real work AI can do here. Content generation is the obvious one: blog posts, social copy, email sequences, ad variations, product descriptions. Claude and ChatGPT are capable tools for this once you build the right prompts and context around your brand. But the more valuable applications are the ones that scale your thinking rather than replace it. AI can take a single well-written piece of content and adapt it across formats, channels, and audience segments. It can generate first drafts of video scripts that your team refines, rather than starting from a blank page every time — and tools like HeyGen can take those scripts to production-ready AI video without a camera or a crew. Midjourney and Runway handle image concepts and video briefs. ElevenLabs turns a voiceover script into production-ready audio in minutes. The whole content production cycle moves faster when the tools are connected and the workflow is designed for your team.

AI also connects to the systems marketing teams already live in. Your CMS, your email platform, your CRM — AI can work alongside all of them, helping you move faster without rebuilding your stack. An automation that pulls CRM data and personalizes an email sequence is not a future capability. It is something we can build now.

The question is not whether AI belongs in your marketing workflow. It does. The question is where to start so the output is actually usable and on brand — and that is what an AI Discovery Session is for.

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AI for Sales Teams

Sales teams lose time to work that is not selling. Research before a call. Follow-up emails after it. CRM updates that never quite get done. Proposals assembled from scratch for every prospect. Competitive briefs that are out of date before they get read. Every hour spent on that work is an hour not spent in a conversation with a potential customer.

AI does not close deals. But it can give your team more time to do the work that does. Pre-call research synthesized from public information, your CRM data, and your own notes — ready before the call, not assembled during it. Follow-up emails drafted from call notes, in your voice, ready to review and send. CRM fields updated from a conversation summary rather than manually entered after the fact. Proposals generated from a structured brief, with the sections your team customizes rather than writes from scratch every time.

Your CRM is the natural home for most of this. Whether your team runs on Salesforce, HubSpot, or something else, AI can work alongside it — not replace it. The goal is to make the system your team is supposed to use actually easier to use, so it gets used.

There is also the top of the funnel. AI can help sales teams generate and qualify outbound leads, personalize outreach at scale, and identify patterns in which prospects convert and which do not. These are not hypothetical capabilities. They are things we can build and test with your data, in your environment, starting with an AI Discovery Session.

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AI for eCommerce Teams

eCommerce moves fast, and the teams running it are usually stretched. Merchandising, promotions, customer communications, inventory decisions, product copy, returns — the list of things that need attention on any given day is long, and most of it is manual. AI does not fix everything at once, but it can meaningfully reduce the manual load in the places where it compounds most.

Product content is one of the clearest wins. Writing accurate, consistent, on-brand product descriptions at scale is tedious work. AI can generate first drafts from structured product data — dimensions, materials, category, intended use — and your team focuses on review and refinement rather than writing from scratch. The same applies to metadata, SEO titles, and category copy that most eCommerce teams know they should improve but never have time to touch.

Product visuals are another area where AI is changing the economics. Generating product images, creating background variations, and producing short product videos used to require a full photo shoot for every SKU. AI can now generate and edit product imagery at a fraction of that cost and time — useful for new product launches, seasonal refreshes, and A/B testing visual treatments without reshooting.

Customer communication is another. AI can handle the first layer of support — order status, return policy, product questions — consistently and at scale, with escalation to a human when it matters. Connected to your eCommerce platform and your CRM, an automation like this runs without adding headcount.

I have spent years working on eCommerce products and customer experience at companies like Macy’s and Adobe. I understand how the data flows, how the customer journey works, and where the friction actually lives — not in theory, but from building and optimizing these systems directly. That is the perspective I bring when we sit down and figure out where AI fits in your operation.

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AI for HR and Operations

HR teams handle an enormous volume of communication, documentation, and process — much of which is repeated across every hire, every onboarding, every review cycle, every policy update. The people on these teams went into HR because they care about people and culture, not because they enjoy reformatting the same offer letter for the fourteenth time this month.

AI can take the repetitive, document-heavy work off the table. Job descriptions drafted from a role brief. Offer letters generated from structured inputs. Onboarding checklists personalized to role, department, and location. Policy documents updated consistently across the organization. Connected to your HRIS or your document management system, these are not complicated automations — they are straightforward applications of AI to work that HR teams do every day.

There is also the internal communication layer. AI can help HR teams communicate more consistently across a distributed workforce — drafting internal announcements, summarizing policy changes in plain language, translating documents for multilingual teams. The voice stays yours. The drafting time drops significantly.

Operations teams face a similar dynamic. Processes that are well defined but manually executed — intake forms, approval workflows, status reporting, vendor communications — are exactly the kind of work AI handles well. The goal is not to automate everything. It is to identify the specific workflows where the manual effort is highest and the process is clear enough for AI to handle reliably. That is what we figure out together.

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AI for Product Teams

Product teams are already using AI — but most are using it the way everyone else is: individually, inconsistently, and without a shared approach. One person uses it for user story drafts. Another uses it to summarize research. A third uses it to write test cases. None of them are using the same tools, the same prompts, or the same standards. The result is that AI speeds up individual work but does not change how the team operates.

The bigger opportunity is at the team level. AI can be built into how your team discovers, decides, and delivers — not as a collection of individual tools, but as a shared capability. Synthesizing user research into patterns. Generating and pressure-testing product requirements. Drafting PRDs, epics, and stories from a brief. Automating the documentation that always falls behind. Running structured retrospectives. None of this requires replacing your existing tools — your project management platform, your design tools, your analytics stack — it requires connecting AI to the work your team is already doing.

There is also the product itself. If your team is building a digital product and considering where AI belongs inside it — as a feature, as a workflow, as a layer on top of your existing data — that is a different conversation, and one I have been having with product leaders for years. I have built AI-powered features into consumer products, advised on AI integration strategy, and shipped AI-native apps from the ground up. I bring all of that into the room when we talk about your product.

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Every team on this page has something in common: more work than time, and processes that were designed before AI existed.

I sit with you, listen to how your team actually works, and together we figure out where AI fits. No hype. No overwhelm. Just a clear, honest look at what is worth doing and where to start.

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