The biggest AI workflows, ripe for agent-ification in each department, that we've seen at Varick: 1. Finance a. Manage AP exceptions: most AP teams are managing 600-800 exceptions a month where invoices don't match POs or receipts and require manual resolution b. Automate your month end close: background execution of bank recs, accruals, intercompany, etc. can get your close cycle from 18-22 days to 7-9 days c. Cash application and collections: automate matching remittance advice to open invoices and getting customers to pay on time 2. Sales Ops a. Manage CRM data and rep admin: we see sales reps spend 38% of their time updating Salesforce b. Deal desk approvals: we see deals take 23 days to get discounts, pricing, etc. approved c. Prepare for forecast calls: ensure all the right data is available for each deal to prepare for Monday forecast calls (call notes, stage changes, next steps, etc.) 3. HR a. Manage payroll changes: compare your ATS, HRIS, and payroll systems before payroll to make sure all new hires, raises, terminations, etc. are accurate. Most payroll corrections are due to issues before the payroll run. b. Handle employee inquiries: we've seen up to 80% of inquiries for PTO, benefits, policy questions, etc. can be handled without human intervention c. Onboarding: manage the process from offer acceptance to day 1, including background checks, equipment, account provisioning, I-9, etc. 4. Legal a. Redline contracts: reduce turnaround time from 5+ days to same day for first pass redlines on NDAs, MSAs, vendor contracts, etc. based on your contract playbook b. Contract intake: manage the intake process for contracts, including determining the requestor, type of contract, contract template, contract lawyer, etc. c. Track contract obligations: extract contract renewal dates, notice periods, auto-renewal provisions, etc. from signed contracts 5. Operations a. Disruption management: move from a week-long process to manage shipment delays, supplier issues, etc. to a few hours b. Order management exceptions: many orders have exceptions that require manual management, whether it's a customer on credit hold, bad ship address, lack of inventory, etc. 6. Procurement a. Supplier onboarding: reduce the time it takes to onboard new suppliers from 26 days to 4 by automating collection of W-9s, banking info, insurance, sanctions, etc. b. 3-way match: compare invoices to POs and receiving documents to identify instances of duplicate invoices, invoices over PO price, etc. 7. IT a. Joiners, movers, and leavers: ensure employees have all the right access on day 1, instead of day 4, and remove access the day they leave b. Ticket routing: we see 1 in 3 IT tickets are routed to the wrong team and require rerouting 8. Marketing a. Speed to lead: enrich, score, and route inbound demo requests to the right sales rep in under 5 minutes b. Media reconciliation: reconcile media invoices to insertion orders and media actually run to identify the 8-12% of media spend that is lost 9. Customer Operations a. Route escalations to the right team the first time, instead of having them bounce back and forth between support and engineering multiple times b. Create case summaries to ensure your engineering team doesn't send cases back for additional details All of these can be run in the background using your existing systems (NetSuite, Salesforce, SAP, ServiceNow, Dynamics, etc.) and exceptions can be routed to your people. If you can solve these for your clients, you'll make them very happy. But in order to succeed across the entire company, you have to go about this systematically. Read more on how to go about it below:

Top 25 questions the world's largest C-Suite executives ask us re: AI transformation in the enterprise: 1. Are AI transformation firms more like McKinsey or Palantir? 2. We launched Copilot for everyone to use, but why hasn't it changed anyone's week? 3. We've done training, custom GPTs, enablement. What's next? 4. Where do we even start with AI? 5. How do we choose the first workflow to AI-enable? 6. Should AI be owned by IT or the business? 7. Do we really have to train all 10,000 people in the company? 8. How do we enable everyone to build agents, without ending up with agent sprawl? 9. Why are our token costs increasing? 10. How do we know if using AI is really cheaper than just hiring another person? 11. Which steps should remain human? 12. How do we communicate AI won't replace our team's jobs? (Will it?) 13. Will we own the agents you build for us? 14. What does maintenance look like in 6 months? 15. Will our data leave our environment? 16. What models should we be using? What do we do when they're deprecated? 17. Can we run these agents inside our ERP, or will people have to use a new tool? 18. Do we need to clean up our data first? 19. How long until we start seeing ROI? 20. When you talk about ROI, do you mean headcount? 21. How do we keep growing our business without increasing headcount? 22. Why did our last pilot project die in POC purgatory? 23. Our process documentation doesn't match what our team actually does – how do you know what to automate? 24. How do we keep up with how quickly AI is changing? 25. If AGI becomes a reality tomorrow, where should we point it? We solve these every day at Varick. Work with us below: