#543 - Kevin Appleby - Adopt AI in The Next 100 Days

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#543 - Kevin Appleby - Adopt AI in The Next 100 Days

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Kevin demonstrates ways you can adopt AI in the next 100 daysSummary of the PodcastOverviewEpisode 2 of a mini-series within The Next 100 Days Podcast where Kevin Appleby and Graham Arrowsmith discuss how AI is influencing their workPre-recording conversation touched on football transfers (Nick Pope, James Trafford) before the formal recording beganKevin identified four or five distinct areas of AI usage he wanted to coverClaude as a Personal AI Assistant (Pre-Call Preparation)Kevin's primary personal AI tool is Claude Cowork, which he connects to email, Notion, HubSpot, calendar, Dropbox, and Google DriveUse case: 10 minutes before a client call, ask Claude to summarise all recent interactions across those sources — it surfaces outstanding promises, discussion topics, and what to raiseClaude can also draft emails into Gmail drafts (not sent), giving a ~90% ready version the user can refineGraham noted concern about integrating a Synology server; Kevin noted most personal data lives in Dropbox or Google Drive and Claude can connect to bothAI Agents Running AutomaticallyKevin runs two scheduled agents without manual triggeringAgent 1 (daily): Scans calendar 30 days out and checks whether each diary entry has a corresponding task in Notion; creates missing tasks automatically, including a Notion page for notesAgent 2 (weekly): Scans upcoming 30 days for GrowCFO Show or Next 100 Days podcast recordings, researches the guest online, and appends notes (bio, website links, suggested questions) to the relevant Notion taskKevin deliberately ignores AI-suggested questions to preserve natural curiosity in conversation, but acknowledges suggested questions are useful for solo-host formatsThe same agent concept applies to client/partner meetings: an agent could automatically pull last interaction notes before any key meetingAdopt AI in Finance Operations (GrowCFO Context)GrowCFO's current quarterly theme is Intelligent Finance Operations — covering the end-to-end finance cycle from purchase orders to final accountsThree-way matching: AI can match purchase orders, goods receipt notes, and invoices automatically; if all match, the invoice is paid without human interventionFraud detection: AI spots anomalies far more effectively than manual reviewReporting: AI can generate board reports and dashboards from accounting systems; demonstrated in a GrowCFO webinar with tech partner Round Treasury using ClaudeKey value: AI removes grunt work so finance professionals can focus on what the numbers mean, not just crunching themAI's Impact on Finance JobsSignificant job displacement expected in transactional/lower-level finance roles; less so for senior finance business partners whose work is relationship-basedChallenge: AI often saves portions of multiple people's jobs rather than eliminating whole roles, making headcount reduction difficult — a pattern observed in shared services projects long before AISupply of finance professionals is falling, particularly FP&A specialists in the US; AI may initially ease recruitment pressure rather than cut headcountMost finance teams are still at the "chatting with ChatGPT" stage, not yet using agentic or Cowork-style toolsA live example of a fully agentic debt-chasing system: an AI agent that checks the debtors ledger, identifies overdue accounts, calls customers, and holds an intelligent conversation about outstanding invoicesAI Connectivity LimitationsClaude's current integration with Xero is poor — only capable of producing basic debtor reports rather than actionable overdue listsCopilot and Gemini do not support Dropbox connectivity, limiting their use in Kevin's personal setupHallucination risk is reduced when AI operates within a well-defined, high-quality data "cocoon" — the importance of a single source of truthFaster Close and Rolling Forecasts"Faster close" — producing monthly accounts quickly rather than 10–15 days after month-end — has been a finance aspiration for 20+ years and AI now makes it achievableRolling forecasts with multiple scenarios (e.g., 0%, 25%, 50% tariff scenarios) can be modelled and run instantly by AI rather than taking weeks to buildAI Governance in FinanceSegregation of duties must be replicated in AI workflows: different agents or human approvers for setting up suppliers, authorising accounts, and making paymentsA single "super AI agent" handling everything end-to-end is not yet appropriate or auditableUsing AI for Research & White PapersKevin used ChatGPT Deep Research to read ~30 published documents from major consultancies (PwC, Deloitte, EY, Accenture, BCG, Forrester, etc.) on AI in finance ops in 15–20 minutes — work that previously would have taken two graduate trainees a fortnightHe gave both ChatGPT and Claude the same prompt and found ChatGPT produced a better overall result, though Claude surfaced some content ChatGPT missed; he combined bothAI is excellent at generating and researching text but structuring the final ...

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