Kevin demonstrates ways you can adopt AI in the next 100 days Summary 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 cover Claude 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 both AI 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 meeting Adopt 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 them AI'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 invoices AI 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 truth Faster 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 build AI 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 auditable Using 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 document, choosing diagrams, and making it consumable remains a human task Virtual Board / AI AvatarsA GrowCFO partner CFO used AI avatars of their board members to anticipate board reactions to finance reports before presentingKevin tested a "virtual advisory board" in AI, including public figures like Michael Heppell, and received useful diverse perspectivesThe deeper goal: frame board materials to open up discussion rather than trigger defensive reactions KAIOS — Kevin's AI Operating System (Personal Project)Started from a ChatGPT conversation: "What if everything you've been taught about time management is a lie?" — leading to the insight that most productivity systems just create more tasks rather than freedomEvolved into KAIOS (Kevin's AI Operating System): a Dropbox-based knowledge structure containing Kevin's values, StrengthsFinder profile, career history, stories, and frameworks — accessible by any AI model via instructions stored within the structureA book outline, introduction, and chapter frameworks have been drafted with ChatGPT's help; the project paused in favour of building KAIOS first so the book has genuine personal stories and IP embeddedGraham suggested this could be Kevin's biggest career opportunity — analogous to how MeclabsAI has built a multi-million pound business around systematised marketing knowledgeKevin noted he prefers positioning himself as an expert using AI in finance rather than as an AI expert per se, given how fast the field moves Career Reflection & Future DirectionBoth hosts reflected on the retirement vs. continued work question; Kevin expressed enthusiasm for staying engaged with AI developments and not wanting to reach the point where technology no longer makes senseKevin acknowledged competitors in the AI-for-finance space (e.g., Nicholas Boucher's AI Finance Club) but sees his differentiation in applying deep finance and personal IP rather than competing directlyGrowCFO Show is approaching episode The Next 100 Days Podcast Co-HostsGraham ArrowsmithGraham founded Finely Fettled in 2014 to provide data from The UK High Net Worth Database to marketers targeting affluent and high-net-worth customers. He's the founder of MicroYES, a Partner for MeclabsAI, creating lead generation AI Agents & Workflows and introducing the MeclabsAI Platform. Graham is an inCruises Independent Partner, and is building up interest from people around the world in the World's Largest Travel Membership - inCruises. You can sign up and access 21,000+ cruises, hotels and tours by clicking HERE Kevin ApplebyKevin specialises in finance transformation and implementing business change. He's the COO of GrowCFO, which provides both community and CPD-accredited training designed to grow the next generation of finance leaders. You can find Kevin on LinkedIn and at kevinappleby.com