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The technology M&A market is sending some unusually clear signals about where the industry is headed. In ATL277, Randy Johnston and Brian Tankersley examine a wave of acquisitions involving AI, semiconductors, data platforms, streaming, automation, and accounting technology—and what those deals may mean for accounting professionals. The discussion ranges from Lattice Semiconductor's acquisition of AMI and onsemi's proposed Synaptics deal to Salesforce's acquisition of Fin, Progress Software's Domo transaction, Bending Spoons' Airtable acquisition, Sage's purchase of Bangert, NVIDIA's proposed acquisition of Hugging Face, and SpaceX's acquisition of Cursor. Stripe's agreement to acquire OpenRouter gets particular attention because AI routing could become an important layer of tomorrow's technology stack.  20261002 Tech Mergers and Acqui… But the episode isn't really about dealmaking. It's about technology strategy and vendor risk. When a product your firm depends upon is acquired, its pricing, roadmap, integrations, support, privacy practices, or even its continued existence can change. Brian's advice: treat an acquisition as a trigger to revisit your contingency plan.  20261002 Tech Mergers and Acqui… Why This Episode Matters The common thread running through these deals is control of strategic technology layers. Stripe's OpenRouter agreement provides access to a gateway spanning 400+ AI models. Stripe Salesforce paid approximately $3.6 billion for Fin and completed the transaction September 10, the day before ATL277 was recorded. Salesforce Investor Relations NVIDIA announced its agreement to acquire Hugging Face for approximately $12.9 billion just eight days before the recording. NVIDIA Blog For accounting firms, that means vendor due diligence cannot stop when the software contract is signed. Ownership changes are technology-risk events. Highlights: Technology consolidation is accelerating. Randy argues that M&A activity can help identify longer-term technology trends.  20261002 Tech Mergers and Acqui…AI infrastructure is becoming strategic. Stripe's OpenRouter agreement highlights the growing importance of model routing and token economics. StripeAI agents are becoming acquisition targets. Salesforce agreed to pay approximately $3.6 billion for Fin, formerly Intercom. Salesforce Investor RelationsHardware and edge AI matter too. Lattice acquired AMI, while onsemi agreed to acquire Synaptics in a transaction valued at approximately $7 billion. Lattice SemiconductorData is part of the acquisition thesis. FOX's proposed $22 billion Roku acquisition combines content with a platform reaching more than 100 million streaming households and significant first-party data. SECAccounting-adjacent M&A continues. Sage acquired longtime partner Bangert, bringing its construction implementation expertise and AskRichard AI-enabled onboarding platform into Sage. SageThe real lesson is contingency planning. Brian recommends reassessing alternatives whenever a critical vendor or product is acquired. Accounting Technology Lab Episode ATL277Wiki Page:  https://wiki.cpate.ch/index.php/ATL277 Title: Technology Mergers and AcquisitionsPublication Date: October 2, 2026Recorded: September 11, 2026Hosts: Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMAPresented by: CPA Practice Advisor

In ATL276, Randy Johnston and Brian Tankersley sit down with Alexis Kingsbury, author of Accrual Intentions, to unpack what he learned from building a deliberately extreme experiment: an accountancy practice staffed by eleven AI agents with their own roles, personalities, and responsibilities. Kingsbury explains that the project began as part parody and part management-science experiment, but quickly became a practical test of delegation, workflow design, controls, and human judgment.The central lesson is not that AI is either brilliant or useless. It is that AI can perform impressively on difficult tasks and still make simple, checkable mistakes. Kingsbury argues that firms should separate probabilistic AI work from deterministic processes, document workflows, insert stage gates, and decide explicitly where human review belongs. He warns leaders not to confuse delegating the work with delegating the thinking.The discussion also covers token economics, local models, model portability, and the risk of locking organizational knowledge inside one AI vendor's project environment. Kingsbury recommends keeping core context, processes, and organizational knowledge in systems the firm controls, then connecting AI tools to that context. His closing advice: do not wait for perfect AI, and do not attempt a giant transformation. Pick a painful, valuable problem, solve it deeply, learn, and expand. Key Takeaways AI can be brilliant and stupid within the same workflow. Kingsbury describes Claude completing sophisticated work correctly and then altering an API-provided link enough to break it. Delegate execution carefully; do not accidentally delegate judgment. If AI takes over production, humans need to make the thinking, objectives, assumptions, and review gates more explicit.Deterministic controls matter. Where possible, use AI to create repeatable calculations, scripts, tests, templates, checklists, and processes.Review capacity has to scale with AI production capacity. Eleven virtual workers can generate an enormous volume of output, and that output still requires testing, prioritization, and accountable review.Your organizational knowledge should not belong to your AI vendor. Portability matters when prices, models, jurisdictions, or vendor strategies change.Token efficiency can become an economic issue quickly. AI consumption may require active optimization as usage scales.Waiting for “perfect AI” is not a strategy. Context, processes, guardrails, and review will remain necessary.Avoid the giant AI transformation project. Start with one sufficiently painful or valuable business problem, solve it well, and expand.Short Promotional Copy One-Sentence Promo What happens when you give eleven AI agents jobs, personalities, responsibilities—and enough autonomy to expose everything that can go brilliantly right and spectacularly wrong? Three-Sentence Promo Alexis Kingsbury built an accountancy practice staffed by eleven AI agents and turned the experiment into Accrual Intentions. In ATL276, he joins Randy Johnston and Brian Tankersley to discuss what the experiment revealed about AI errors, delegation, controls, token economics, organizational knowledge, and human judgment. The big lesson: AI can dramatically expand what a firm can do, but only if governance and review expand with it. Promotional Paragraph Your AI agent just completed the sophisticated analysis, updated the documentation, called the right tools—and then broke the link it was supposed to give you.That kind of contradiction is at the center of ATL276: The Secrets Agents Keep. Alexis Kingsbury joins Randy Johnston and Brian Tankersley to explain what he learned building the AI-staffed accounting experiment behind Accrual Intentions. The conversation moves beyond “AI good” versus “AI bad” and gets into the management problem: how do you provide context, separate thinking from doing, design deterministic controls, scale review, manage token costs, and keep your intellectual property portable instead of trapping it inside one AI provider? Timestamped Pull Quotes TimeSpeakerPull QuotePromotional Angle05:03 | Alexis Kingsbury | “It'll just be easier if I do it myself.” | AI vs. delegation12:40 | Alexis Kingsbury | “If you want a really good decision made, you don't want two people who think the same.” | Diversity of perspective26:08 | Alexis Kingsbury | “There's value, but also risk… maximize value and mitigate the risk.” | Governance34:28 | Alexis Kingsbury | “If you can get rid of the things that we don't enjoy… you get more time on the things that do add value.” | Human value38:33 | Alexis Kingsbury | “If you are delegating the doing, you have to pull out the thinking and do the thinking up front.” | Management47:03 | Alexis Kingsbury | “I've been able to improve token efficiency by 4,000x.” | AI economics50:48 | Alexis Kingsbury | “One other big mistake I would suggest people avoid is giving the keys away to big AI firms.” | Vendor lock-in53:15 | Alexis Kingsbury | “The technology is already good enough. It's just that you need all the guardrails and the context.” | Implementation53:15 | Alexis Kingsbury | “Pick something in your business that is either incredibly frustrating and painful… or is a current missed opportunity for value.” | Where to start Production note: Timestamps are based on the supplied transcript/SRT. Recheck them against the final edited episode before cutting promotional video. Best Short-Video Pulls The brilliant AI that breaks the easy thing — approximately 22:55–26:40Discussion of deterministic versus probabilistic work, culminating in Alexis's story about AI completing difficult work and then altering a valid link. Delegate the doing, not the thinking — approximately 38:30–45:00Alexis explains why removing the manual production step means leaders must intentionally preserve the thinking step. Tokens, local AI, and vendor economics — approximately 47:00–52:30Discussion of AI subsidies, token efficiency, local models, and changing provider economics. Don't give away the keys — approximately 50:45–53:10Governance discussion about keeping organizational context outside proprietary AI workspaces and making it accessible through tools such as MCP. How accounting firms should start — approximately 53:15–56:30Don't wait for perfect AI, don't start with an enterprise-wide transformation, and don't waste time on trivial experiments. Pick a valuable problem. Suggested Show Notes Why Alexis created an accountancy practice staffed by eleven AI agents.Why the experiment began as both parody and serious management research.Custom GPTs and the early evolution of the virtual accounting team.Giving agents different roles, personalities, backgrounds, and perspectives.Why multiple viewpoints can improve AI-assisted decision-making.Moving from Custom GPTs to Claude Code, Claude Cowork, Codex, and agentic workflows.Why LLMs sometimes excel at complicated work but fail at simple tasks.Probabilistic AI versus deterministic calculations and processes.Using AI to build conventional software, scripts, templates, and controls.Why “I checked i...

Episode Summary AI may feel like a flat monthly subscription today, but ATL275 argues that the economics are moving toward a metered, multi-model market. Randy Johnston and Brian Tankersley examine AI routers, token marketplaces, and agent orchestration—tools designed to let firms choose different models for different jobs rather than committing every task to one vendor. Brian explains why OpenRouter and LibreChat can make model choice resemble buying fuel: use the amount of compute you need in the engine best suited to the work. Randy connects that concept to a three-layer AI strategy spanning general productivity tools, AI embedded in accounting applications, and specialized agents. The hosts also discuss the difficulty of forecasting token budgets, the likelihood of more usage-based pricing, and a growing field of gateways including OpenRouter, Ramp Router, Factory Router, Portkey, LiteLLM, Cloudflare, Kong, AWS, Microsoft, and Google. For accounting firms, the practical issue is not merely cost. Model selection, privacy, compliance, governance, and vendor concentration all matter when agents handle sensitive workflows. The takeaway: expect AI procurement to look less like buying one software subscription and more like managing a portfolio of compute suppliers—optimizing each workload for capability, cost, risk, and control. Key Takeaways Every AI workload consumes compute. Whether the customer sees a monthly subscription or an API invoice, somebody is paying for the tokens behind the transaction.One model does not necessarily fit every workload. AI routers can give organizations access to different models without separately funding and administering every provider.Cost optimization will become part of AI governance. Firms may increasingly route simple work to inexpensive models and reserve expensive frontier models for jobs that justify the added capability.Per-seat pricing may not be the final economic model. As agents become more common, usage-based pricing could become increasingly important.Accounting firms need more than cheap tokens. Privacy, contractual protection, data handling, auditability, regulatory compliance, security, and vendor stability remain critical.AI gateways are becoming strategic infrastructure. OpenRouter, hyperscale cloud platforms, and newer routing competitors are competing to become the transaction layer between applications and AI models.“Bring your own tokens” may become commonplace. Software vendors can increasingly let customers supply their own API credentials and select the AI models used inside applications.Token measurement should eventually resemble cost accounting. Firms need to understand the cost of AI by workflow, agent, client, and business process—not merely the organization’s total monthly AI bill.

ATL274 — Alliances, AI, and Self-Funding! Oh My! Guest: Dan Pinkous, Founder & CEO, TrussHosts: Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMAPodcast: The Accounting Technology LabPublisher/Sponsor: CPA Practice AdvisorRelease Date: September 11, 2026Approximate Runtime: 28:26Primary Topics: Tax workflow, artificial intelligence, technology partnerships, client experience, advisory services, document management, practice management, startup funding, pricing 200-Word Episode Summary In ATL274, Randy Johnston and Brian Tankersley talk with Daniel Pinkous, founder and CEO of Truss, about a tax workflow platform built around three ideas: low-friction client experience, AI embedded throughout the workflow, and partnerships instead of trying to build every specialized capability internally. Pinkous explains that Truss began in late 2022 as an AI-native product, using large language models for document processing, client checklists, research, planning, and other tasks intended to move firms away from compliance tedium and toward advisory work. The conversation highlights Truss partnerships with Ping Assistant, Kintsugi, Filed, Byron, Magnetic, K1x, GruntWorx, CygnusAI, Bizora, and Karbon. Rather than replace every tax, practice-management, or document-management tool, Truss aims to connect the client-facing parts of intake, workpapers, preparation, and delivery while keeping the experience consistent. Pinkous also discusses adoption, saying Truss emphasizes web-based, zero-account client access and reports high client satisfaction. The episode closes with a different startup story: Truss says it is customer-funded, has taken no outside venture capital, operates profitably, and uses a simple firmwide pricing model with unlimited users, returns, e-signatures, and AI usage. For accounting firms, the question is not simply which tool wins, but how a connected ecosystem improves workflow, service, and control. Key Takeaways Partnerships can beat territorial product strategies. Pinkous argues that accounting technology vendors have historically been too territorial. Truss's strategy is to partner where another vendor has deeper expertise instead of attempting to recreate every specialty internally.AI is most useful when it disappears into the workflow. Truss was started in late 2022 and designed around AI from the beginning. Pinkous describes large language models working “under the hood” for document naming, page rotation, document processing, tax-year validation, checklists, research, planning, and other tasks.The goal isn't merely more compliance capacity. Pinkous sees automation first eliminating tedious compliance work and then creating room for higher-value advisory services.Tax workflow is an ecosystem problem. A tax engagement can involve intake, document collection, workpapers, preparation, signatures, payments, delivery, storage, and practice management. The more those pieces live in disconnected applications, the more time staff spend hunting for information instead of doing accounting work.There is a difference between “capital-W” and “small-w” workflow. Traditional practice-management systems such as Karbon or XCM manage the firm's broader internal workflow. Truss focuses heavily on the smaller client-facing workflows surrounding an engagement—requesting documents, exchanging information, preparing and delivering returns, collecting signatures, and keeping clients informed.Client adoption is an implementation metric, not a cosmetic metric. Pinkous argues that firms cannot redesign workflow around technology that only a fraction of their clients will use. Truss therefore emphasizes a low-friction, firm-branded experience with minimal login and account-creation barriers.Tax may be the entry point, but client experience crosses service lines. Pinkous says firms sometimes extend their use of Truss into audit and CAS because clients should not need an entirely different interaction model every time they work with another department.Document management remains an unresolved piece of the modern stack. The discussion touches on FileCabinet CS, SharePoint, Google Workspace, and other repositories. Pinkous describes Truss's own document-management capabilities while acknowledging that larger firms may still need more specialized systems and integrations.Capital structure affects product governance. Truss says it has been built without venture-capital financing. Pinkous argues that being customer-funded changes priorities because management is not simultaneously optimizing for an outside investor's required growth rate or next funding round.Pricing simplicity can reduce implementation friction. Pinkous describes firmwide pricing with unlimited users, returns, e-signatures, and AI usage rather than metering every transaction.Catchy Quotes and Video/Audio Locations TimeSpeakerPull QuotePromotional Angle03:55 | Dan Pinkous | “The first phase… save these firms from the tedium… liberate them from the compliance. Really, the second phase is now we can be free to do advisory.” | AI and advisory06:52 | Dan Pinkous | “The industry has been too territorial, and it's hurting accountants. We need to be working together. We need to be collaborating.” | Alliances07:05 | Dan Pinkous | “Ping is peanut butter and jelly with us.” | Partner ecosystem12:00 | Dan Pinkous | “Client says they uploaded something. Okay, where did they upload it? And I got to go search across four or five different systems.” | Workflow fragmentation21:01 | Dan Pinkous | “What if we start with the client experience, and we really nail that? And that's our primary north star for success.” | Client experience21:16 | Dan Pinkous | “I can't build a workflow around something where only 30% of my clients are using it… we need to push for 90% plus adoption.” | Technology adoption24:09 | Dan Pinkous | “We're really unique in that we're one of the only companies in the space that is built customer funded. We haven't taken any venture capital funding, any outside funding whatsoever.” | Self-funding24:41 | Dan Pinkous | “We get to serve just one master, and that's our customers.” | Best quote for graphics25:53 | Dan Pinkous | “Operating profitably is a much more stable future… long-term way to build.” | Vendor sustainability27:22 | Dan Pinkous | “One simple price for the entire firm, unlimited usage, unlimited e-signs, unlimited returns, unlimited users… unlimited AI usage… go crazy, have fun.”

ATL273 — Reinventing Your Practice with Advisory With Guest Nancy Sperry of Sage Episode: ATL273Release date: September 4, 2026Hosts: Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMAGuest: Nancy Sperry, Senior Vice President of U.S. Partner Sales, SageApproximate runtime: 33 minutesPrimary topic: Using trusted AI, agentic automation, and the Sage partner ecosystem to move accounting professionals from transaction processing toward higher-value advisory work.In ATL273, Randy Johnston and Brian Tankersley talk with Nancy Sperry, Senior Vice President of U.S. Partner Sales at Sage, about how AI can help accounting firms and finance professionals reinvent their practices around advisory services. Sperry argues that AI adoption in accounting depends on trust: systems must be explainable, auditable, secure, controllable, and subject to human approval. That “glass box” approach can reduce the time professionals spend validating transactions and manipulating data, freeing them to interpret results, advise clients, and look forward instead of backward. The discussion explores Sage Copilot, finance and close agents, partner-built agents, and a future agent marketplace where solutions created for one client may be reused across the Sage ecosystem. The hosts and Sperry also examine how AI could accelerate micro-vertical specialization in industries such as construction and nonprofit organizations, while integrations and Model Context Protocol connections may reduce dependence on traditional middleware and point solutions. The episode closes with Sage’s broader platform strategy, including Sage Intacct, Sage HCM, and acquired products, and with a clear message for firms: advisory growth will require both AI-enabled productivity and disciplined governance, security, accountability, and human oversight as firms redesign workflows and deepen trusted relationships with clients today. Key Takeaways Trust is the gating factor for accounting AI. Explainability, auditability, approval workflows, security, and accountability matter as much as model capability.Advisory becomes more practical when the mechanical work shrinks. Automation can move professionals away from manipulating data and toward interpreting what the numbers mean.Finance will not become autonomous overnight. Sperry notes that only a small portion of finance functions are autonomous today; confidence must be earned through reliable results and controls.Agents create a new partner opportunity. Sage partners may be able to build agents for specific client problems and then distribute reusable solutions through a broader marketplace.Industry specialization can get much deeper. AI and agent builders may allow firms to move beyond broad verticals such as construction into highly specialized micro-vertical workflows.MCP and cross-system agents can change the technology stack. Agents that work across systems such as CRM, payroll, and ERP could eliminate some traditional integration layers—but also introduce new security concerns.Advisory becomes forward-looking. The opportunity is to spend less time looking through the rearview mirror and more time helping clients see through the windshield.Human oversight remains essential. The accountant, CFO, or advisor remains responsible for consequential decisions even when AI performs more of the underlying work.Sage is broadening the platform around finance, HR, payroll, expenses, construction, forecasting, practice management, and other adjacent workflows.The strategic opportunity is bigger than efficiency. AI can change the relationship between the accounting professional and the client by making interpretation, specialization, and continuous advice economically feasible.Catchy Quotes and Video Locations Times are based on the supplied transcript and may shift slightly if the published video contains a different intro, edit, or advertising insert. 00:55 — Nancy Sperry: “AI is the most exciting and really going faster than either of those two kind of major changes.”04:34 — Nancy Sperry: “Anything that is explainable and that I can click through and see the result… gives a lot of confidence.”06:48 — Brian Tankersley: “When the math’s not mathing, it’s not good for anybody in accounting.”08:24 — Nancy Sperry: “I see it being a really big revolution in the relationship.”10:37 — Nancy Sperry: “Turn the headlights on and see into the future.”13:36 — Nancy Sperry: Partners can “solve real business problems that are really critically important to that client.”15:58 — Randy Johnston: Advisory is “looking out the windshield as opposed to looking in the rearview mirror.”20:44 — Nancy Sperry: “Partners are the intersection of that for us at Sage.”26:26 — Nancy Sperry: Sage’s “glass box approach” is designed to provide confidence, control, oversight, and accountability.31:39 — Nancy Sperry: AI creates an opportunity for partners “to just create amazing outcomes.”

In ATL272, “The Gathering Storm,” Randy Johnston and Brian Tankersley argue that AI is changing cybersecurity faster than many accounting firms are changing their defenses. The issue is not simply smarter phishing or more malware. AI can automate reconnaissance, vulnerability discovery, exploit development, credential testing, and lateral movement at machine speed, while open-weight models and falling token costs may make those capabilities cheaper and more widely available. That matters especially for CPA firms because they hold an unusually valuable combination of tax data, identity information, client credentials, banking access, payment authority, and long-retained documents.The hosts also point to a dangerous mismatch: attackers are getting faster while many firms still rely on home-grade routers, unsupported operating systems, aging hardware, and definition-based security tools. Human error remains a major weakness, when convincing phishing messages land during stressful periods.Their recommendation is practical: harden systems now, eliminate unsupported technology, rehearse incident response, shorten detection-to-containment time, test backup restores, inventory every AI tool and agent in the firm, map where client data goes, inspect audit trails, and maintain control of firm data. The takeaway is caution without panic: this is not “Terminator and Skynet,” but waiting for certainty is not a cybersecurity strategy.Pull Quotes TimeSpeakerQuote00:01:07 | Randy Johnston | “We want you to start being proactive now on protecting your businesses.”00:02:32 | Brian Tankersley | “I think that security is going through a similar transition right now.”00:04:47 | Randy Johnston | “The time to first attack after a vulnerability is exposed is well below an hour now.”00:07:02 | Brian Tankersley | “We have pretty much the dream identity theft set of data.”00:11:58 | Randy Johnston | “We are trying to have you think about how you stand up your defenses and how the attackers are trying to defeat your defenses or guardrails.”00:16:59 | Brian Tankersley | “You really need to step up your cybersecurity posture now, because we’re going into a very bad neighborhood with very scary things going on.”00:17:35 | Randy Johnston | “The attackers’ tools are actually dropping in cost very rapidly.”00:18:17 | Brian Tankersley | “When these things are out, they’re out, and there’s no real coming back.”00:20:17 | Brian Tankersley | “We have cheaper attacks, we have more targets. We have the machine speed shrinking the response time.”00:21:09 | Randy Johnston | “It’s not Terminator and Skynet at this point.”00:22:27 | Randy Johnston | “Get the fundamentals right, including testing the backups.”00:23:33 | Randy Johnston | “If you’re waiting for things to be certain, that ain’t going to happen.”00:25:12 | Randy Johnston | “Pollyanna Randy is suggesting that you may well have some really ugly conditions in front of you, and I’m trying to keep you out of the storm.”

Episode Summary: ATL271 - Why Your WISP Is Essential in 2026 Podcast Page/Subscription Links: https://podcast.cpate.chWiki Page: ATL271 - CPA Tech Wiki In ATL271, “Why Your WISP Is Essential in 2026,” Randy Johnston and Brian Tankersley explain why a written information security plan is no longer a compliance document that can sit on a shelf. Accounting firms hold concentrated stores of tax, financial, identity, and sometimes health information, making them attractive targets for phishing, credential theft, ransomware, fraudulent wire instructions, and AI-enhanced attacks. The hosts walk through the overlapping expectations of the IRS, FTC Safeguards Rule, and HIPAA, including written policies, multi-factor authentication, encryption, logging, incident response, training, governance, vendor oversight, and regular risk assessment. They emphasize that penalties can be severe, but the larger business risk may be client loss, reputational damage, litigation, and disruption during tax season. The episode also highlights practical governance: assign accountability, review the WISP regularly, connect security spending to risk, and report results to leadership. Randy and Brian close with five high-impact controls—MFA, full-disk encryption, tested backups, a written incident response plan, and vendor security questionnaires—plus a recurring calendar for log reviews, backup restores, phishing simulations, vulnerability scans, training, patching, and annual WISP updates. Their message: security is an operating discipline, not paperwork. For firms of every size, preparation now is cheaper than recovery. Key Takeaways A WISP should be an operating system for security—not shelfware. It needs ownership, periodic review, documented changes, and executive oversight.Accounting firms are unusually attractive targets because they aggregate tax, financial, identity, payroll, and other confidential information.Credential theft and phishing remain central risks, while AI is making fraudulent messages and attacks more convincing.Vendor management belongs inside the security program. Cloud applications, hosting companies, MSPs, AI services, and other third parties expand the firm's attack surface.Incident response must be planned before the incident. Firms should understand regulatory notification obligations, internal responsibilities, legal resources, and PR response.Security has a recurring calendar. Log reviews, backup restores, phishing tests, vulnerability scanning, access reviews, training, patching, and WISP updates need assigned frequencies and owners.Catchy Quotes Approx. TimeSpeakerQuote02:04 | Brian Tankersley | “The firms get hit because you and I are the Fort Knox of confidential data.”03:33 | Brian Tankersley | “The bad guys are getting better faster than the good guys are getting better.”07:40 | Brian Tankersley | “Anything that touches client data is a death sentence for a hard drive in my office.”12:10 | Brian Tankersley | “If you don't have an adequate WISP, you're in violation of the FTC safeguards rule.”18:20 | Randy Johnston | “You've got risk on any provider.”18:42 | Brian Tankersley | “As soon as you know something's happened, the clock is ticking.”23:11 | Brian Tankersley | “Multi-factor authentication, full disk encryption, tested backup strategies, written incident response plans, vendor security questionnaires.”24:55 | Randy Johnston | “Make sure that you've got your WISP … pulled out, dusted off, and updated for this year's regulations.” Note: Timestamps are approximate where the quote occurs inside a longer timestamped speaker segment in the transcript. Social Media Posts

ATL270: Hardware Hullabaloo - Episode Summary Hardware is once again a strategic business issue—not merely an IT purchasing decision. In ATL270, Randy Johnston and Brian Tankersley examine how cybersecurity concerns, new processor families, and extraordinary component-price increases are reshaping technology plans for accounting firms and home offices. They begin with aging consumer routers, warning that an inexpensive or unsupported gateway can become the weak link for business data, remote access, and connected devices. Network segmentation, managed security hardware, and renewed use of VPNs are presented as practical safeguards. The conversation then surveys emerging hardware from Intel, AMD, Apple, Google, NVIDIA, and major PC manufacturers, with special attention to neural processing units and locally executed AI workloads. Brian shares his early experience with a TCL NXTPAPER tablet, while both hosts caution buyers against underpowered back-to-school systems. The sharpest lesson comes from current upgrade economics: Brian reports that the same 64 GB memory kit he bought for about $210 was listed near $979, while Randy describes a previously $18,000 server configuration approaching $74,000. Their advice is deliberately pragmatic: extend maintenance where sensible, scrutinize cloud operating costs, match purchases to measurable productivity, and avoid spending premium dollars merely to own the newest hardware. In a volatile market, disciplined technology governance matters more than specifications alone.Key Takeaways- Treat home-office routers and remote-access hardware as part of the firm’s control environment.- Segment business, household, and connected-device traffic so one compromise does not expose every system.- Specify processors, memory, and storage around actual workloads—especially local AI—rather than marketing labels.- Evaluate upgrades using measurable productivity and risk reduction, not hardware envy.- When server replacement prices and lead times are extreme, compare extended maintenance, cloud economics, and deferral. Wiki: https://wiki.cpate.ch/index.php/ATL270 Creators & Guests Brian F. Tankersley - Host Randy Johnston - Host _________________________

ATL269 — Microsoft Agent 365 Program: Accounting Technology Lab Hosts: Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMA Approximate runtime: 31 minutesResource: 100 Free AI Prompts for Accounting - https://cpate.ch/100-prompts-atl Primary topic: Governed deployment, monitoring, security, and economics of enterprise AI agents 200-Word Episode Summary In ATL269, Randy Johnston and Brian Tankersley examine Microsoft Agent 365 as a control plane for deploying, monitoring, governing, and securing AI agents. They frame the shift as a move from per-seat software licensing toward an AI token economy, where tokens function like staff time, prompts replace checklists, and agents perform repeatable work at speed. Practical examples include invoice extraction, email drafting, financial-statement analysis, and budgeting—tasks that may cost pennies in model usage while still requiring review and judgment. The hosts argue that Agent 365 gives accounting firms an alternative to “Wild West” experimentation by extending Microsoft 365 security, auditability, and governance over agents. They discuss Copilot, Agent Builder, Copilot Studio, Microsoft Foundry, Azure AI, Power BI, Defender, Purview, and the E7 licensing bundle. Privacy, records retention, e-discovery, intellectual property, and workflow ownership receive attention because firms may expose sensitive client data or proprietary processes when using public AI platforms. Their practical recommendation is measured experimentation: convert checklists into prompts, move tasks into agents, retain humans in the loop, establish token budgets, and evaluate results firsthand. The message is urgent but cautious: firms need not operate at the bleeding edge, but they must start learning before competitors pull ahead. Key Takeaways ·        The economic unit of AI is shifting from a user license toward token consumption and task-level cost. ·        Tokens can be managed like staff time, prompts like procedures, and agents like digital staff assignments. ·        Agentic workflows depend on steps, loops, exception handling, context, permissions, and human review. ·        Agent 365’s differentiator is governance: visibility, monitoring, security, auditability, and centralized control. ·        Public AI tools create material concerns involving PII, PHI, client confidentiality, retention, e-discovery, and vendor training practices. ·        Proprietary workflows may be valuable intellectual property and should not be surrendered casually to a model provider. ·        Model selection should balance quality and cost with privacy, security, regulatory fit, and data ownership. ·        Accounting firms should begin with controlled experiments and measurable use cases rather than enterprise-wide autonomous deployment. ·        Human reviewers remain accountable for conclusions, professional judgment, client context, and exceptions. ·        Firms need AI governance policies, token budgets, approved-tool lists, monitoring, and documented escalation procedures. Catchy Quotes and Video Locations ·        01:48–01:50 — Brian Tankersley: “Yeah, so it’s an F-150 and not a G-Wagon.” ·        04:22–04:30 — Brian Tankersley: “This is like sending it to staff first, and the staff costs three cents.” ·        09:35–09:51 — Brian Tankersley: “I’m seeing tokens as staff time on the schedule… We used to have checklists, and now we have prompts.” ·        10:09–10:22 — Brian Tankersley: “They get work done so fast that the human is now the logjam in the process.” ·        15:32–15:48 — Randy Johnston: “Microsoft Agent 365 is the control plane for agents… Is it perfect yet? No. Is it pretty doggone good? Yes.” ·        17:25–17:41 — Brian Tankersley: “We have the grown-ups in charge now, and we’re going to systematize this in a way that we can regulate and do the right way.” ·        28:02–28:13 — Brian Tankersley: “Take your checklists and turn them into prompts, and take tasks that are on the schedule and push them into agents.” ·        29:31–29:43 — Brian Tankersley: “The train is leaving the station… If you don’t get started on this stuff, you’re going to be behind, and so it’s time to go.” ·        30:19–30:30 — Brian Tankersley: “It is critical that you get your hands dirty with some of these things, because it’s the only way that you will be able to evaluate whether something really works or not.”

ATL268 — Scaling New Heights 2026, Part Two is an episode of the Accounting Technology Lab podcast hosted by Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMA. In Part Two of their Scaling New Heights 2026 recap, Randy Johnston and Brian Tankersley examine what the conference revealed about artificial intelligence, accounting platforms and the profession’s readiness for change. They describe an unusually divided AI adoption curve: a relatively small group is experimenting aggressively with agents and advanced workflows, while many accounting professionals have done little or nothing with the technology. The hosts review keynote speakers, educational sessions and the conference’s AI-enabled general-ledger tour. Products discussed include Campfire, SoftLedger, Kick, Xero, Puzzle, Microsoft Dynamics 365 Business Central, Sage, Digits, Zoho and Acumatica. They also observe growing dissatisfaction with Intuit and uncertainty about replacements for QuickBooks Desktop. A central lesson is that firms should not select technology merely to reproduce today’s processes. Instead, they should define how services, pricing and workflows should operate three to five years from now and choose platforms that support that future. Johnston and Tankersley also warn that an overcrowded accounting-technology market will produce additional vendor failures and discontinued products. Firms therefore need careful due diligence, realistic implementation plans, data-export procedures and a viable Plan B—even when buying from established publishers._________________________________KEY THEMES AI adoption is highly uneven - Brian estimates that approximately 10% of conference participants were actively working with agents and advanced AI, another 10% had experimented with prompts, and a much larger group appeared to have done little with the technology. Randy compares the pattern to a K-shaped economy rather than a traditional bell-shaped adoption curve.Compliance still dominates - Despite years of discussion about client advisory services, many firms remain heavily dependent on compliance work. The transition to advisory, alternative pricing and technology-supported higher-value services continues more slowly than industry advocates expected.Accounting platforms are entering a transition period - The exhibit floor showed renewed competition among traditional accounting systems, AI-native ledgers and broader ERP platforms. Several offerings emphasized automated transaction coding, reconciliations, close management, reporting and real-time financial information.Firms must buy for their future operating model - A replacement platform should support the firm that management intends to operate in three to five years—not simply recreate existing workflows. Strategy concerning pricing, advisory services, staffing and automation should precede product selection.Every firm needs a technology exit plan - Vendor shutdowns, acquisitions and product discontinuations affect both startups and established publishers. Firms should understand data ownership, export formats, contractual terms, conversion options and the operational consequences of replacing a core application. Notable quotes 03:34 | Brian Tankersley | “The tool’s ready to be used… The challenge is pulling along those laggards that are out there.”04:41 | Randy Johnston | “You’ve got the really early adopters, and you’ve got the other people that aren’t moving—and there’s a big gap in the middle.”10:29 | Brian Tankersley | “It felt like there were a lot of people that were in the middle of a divorce with Intuit right now.”17:43 | Randy Johnston | “There’s too doggone many products trying to get to too small of a market.”20:58 | Brian Tankersley | “You need to have a Plan B in your workflow for what’s going to happen if your product is discontinued.”21:41 | Brian Tankersley | “Pick the tools that are going to enable not how you run the firm today, but how the firm’s going to run in three years—five years.”22:39 | Brian Tankersley | “We’re seeing an increasing rate of failures because they’re trying to buy products that solve the old workflow.” Episode information Episode: ATL268 — Scaling New Heights 2026, Part TwoPublication date: July 31, 2026Recorded: July 2, 2026Hosts: Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMAProgram: Accounting Technology LabPresented by: CPA Practice AdvisorApproximate runtime: 23 minutes, 35 secondsPrimary topics: Scaling New Heights 2026, artificial intelligence, AI-enabled general ledgers, technology adoption, advisory services, software selection, vendor risk and accounting-platform migration

ATL267 – AI Is the Ultimate Accounting Assistant, Part Two Guest: Sasha Orloff, Co-founder and CEO of PuzzleHosts: Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMAProgram: Accounting Technology Lab, presented by CPA Practice AdvisorEpisode length: Approximately 10 minutes Episode Summary In part two of the conversation with Puzzle co-founder and CEO Sasha Orloff, the Accounting Technology Lab examines how accounting professionals can begin adopting artificial intelligence without abandoning their existing knowledge, systems, or professional judgment.Orloff recommends starting with a difficult but low-risk problem rather than using AI only for trivial experiments. Accountants should remove client-identifying information, use personal or anonymized data, and practice explaining a task as clearly as they would to a highly capable new employee who lacks accounting experience. A prompt, in this context, becomes much like a detailed checklist: it defines the expected steps, safeguards, and outcome.The discussion also distinguishes helpful AI assistance from uncontrolled automation. Puzzle’s approach allows agents to prepare work while requiring human approval before anything is posted to the ledger. Randy Johnston emphasizes that the profession does not need technology that eliminates accountants; it needs technology that makes accountants more effective.Orloff argues that firms creating a safe culture of experimentation will improve productivity, profitability, and client service. Brian Tankersley closes with a challenge to accounting leaders: become sufficiently familiar with AI to evaluate solutions intelligently, guide employees, and lead clients through change. The central message is simple—AI adoption does not require reckless transformation, but it does require action. Key Episode Themes Begin with meaningful work. Testing AI on an authentic, complicated problem reveals more than asking it to perform a novelty task.Use low-risk information. Remove client names, confidential information, personally identifiable information, and other sensitive data before experimenting.Treat prompts as process documentation. AI performs better when instructions describe each step, decision, constraint, and expected output.Keep accountants in control. AI can draft transactions, reconciliations, analyses, and journal entries, but accountable professionals should review and approve the results.Create a culture of experimentation. Firm leaders should give employees permission and guardrails to explore AI safely.Leadership requires firsthand knowledge. Accountants do not have to adopt every AI product, but they need enough experience to distinguish practical capabilities from marketing claims.Suggested Episode Highlights Sasha Orloff explains why accountants should test AI on difficult, meaningful tasks.Detailed prompts function like checklists for accounting processes.Firms should experiment only with anonymized, nonconfidential information.Puzzle’s agents require approval before posting changes to the ledger.AI should enhance accountants rather than remove them from the process.Accountants retain responsibility for judgment, review, and accountability.Firm leaders must establish guardrails that make safe experimentation acceptable.Practical AI productivity in accounting is beginning to move beyond novelty.Professionals who learn now may gain improvements in margins, capacity, and service.Accounting leaders must develop enough firsthand knowledge to evaluate AI vendors critically. CPAFirmClientAccountingServicesCASMonthEndCloseProfessionalJudgmentResponsibleAIHumanInTheLoopDigitalTransformationPracticeManagementPromptEngineeringAccountingPodcastPuzzleProducts, Services, and Companies Mentioned Product, service, or companyContext in the episodeXFacebookLinkedInInstagramPuzzle | AI-native accounting platform and ledger discussed by Sasha Orloff; supports agent-assisted workflows with approval controls | @puzzlefin | No official account identified | Puzzle | No official account identifiedChatGPT | General-purpose AI assistant suggested for testing anonymized transactions and charts of accounts | @OpenAI | OpenAI | OpenAI | @openaiOpenAI | Developer and publisher of ChatGPT | @OpenAI | OpenAI | OpenAI | @openaiGemini | Google AI assistant suggested for controlled accounting experiments | @GoogleGemini | Google | Google | @googlegeminiGoogle | Developer and publisher of Gemini | @Google | Google | Google | @googleClaude | Anthropic AI assistant suggested for controlled accounting experiments | Anthropic | No official product-specific account identified | Anthropic | No official product-specific account identifiedAnthropic | Developer and publisher of Claude | @AnthropicAI | No official account identified | Anthropic | No official account identifiedX, formerly Twitter | Social platform referenced as a source of AI news and discussion | @X | Not applicable | X | @xCPA Practice Advisor | Presenter and sponsor of the Accounting Technology Lab | @CPAPracAdvisor | CPA Practice Advisor | CPA Practice Advisor | @cpapracticeadvisor Verification note: Social-media availability and account names can change. Puzzle’s website links directly to its LinkedIn and X accounts.

Title: ATL266 — AI Is the Ultimate Accounting AssistantWiki: ATL266 - CPA Tech Wiki Guest: Sasha Orloff, CEO of Puzzle Hosts: Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMA Publisher/Sponsor: CPA Practice Advisor AI Is the Ultimate Accounting Assistant—But the Accountant Is Still Accountable In ATL266, hosts Randy Johnston and Brian Tankersley speak with Sasha Orloff, CEO of Puzzle, about why artificial intelligence should be viewed as an accounting assistant rather than an autonomous replacement for accountants. Orloff argues that accounting is fundamentally an accountability profession: AI can prepare work, identify anomalies, execute firm-defined rules, and accelerate close processes, but a qualified human must review, approve, and remain responsible for the books. The conversation contrasts probabilistic generative AI with deterministic accounting workflows. Puzzle’s approach lets firms describe policies in natural language, confirm the system’s interpretation, and preserve those instructions as repeatable agents. Examples include automatically preparing depreciation for computer purchases and recognizing annual prepaid rent according to a fixed schedule. These agents preserve firm knowledge, create audit trails, and reduce repetitive clicking without silently changing records. The speakers also explore accuracy, trust, staffing shortages, and the limitations of legacy accounting platforms. Orloff says firms adopting governed automation can close faster, improve accuracy, scale without proportional hiring, and potentially give staff significant time back each month. The central message is optimistic but disciplined: firms that combine AI speed with human judgment, transparent controls, and explicit sign-off can deliver better client service, higher margins, and more rewarding accounting work. Key Themes ·       AI as an assistant and amplifier of professional judgment ·       Accountability, review, approval, and auditability ·       Deterministic agents versus probabilistic AI ·       Preserving firm procedures and client-specific knowledge ·       Faster monthly closes and improved consistency ·       Staffing leverage, higher margins, and better work-life balance ·       Gradual, opt-in adoption of AI-powered workflows Catchy Quotes and Video Locations 00:33 — Sasha Orloff: “AI is going to be one of the biggest booms for accounting, and accountants are going to make more money because of AI than ever before.” 06:49 — Sasha Orloff: “The difference is an AI is going to sound really confident when it guesses the wrong way.” 09:09 — Sasha Orloff: “Our customer is the accounting firm, and what does that mean? It means we defer to them as the experts.” 16:01 — Sasha Orloff: “An agent is a piece of software that executes a very specific task.” 21:31 — Sasha Orloff: “This can be designed…not to replace you, but to make you the best version.” 22:13 — Sasha Orloff: “You define your month close process as a set of agents…and just let it prepare and help you become your best version.” 24:14 — Sasha Orloff: “The accountant is the expert. You just need too many clicks to get that expertise implemented.” 30:41 — Sasha Orloff: “Could you imagine having a week of vacation every month and making the same amount of money?”

In this episode of the Accounting Technology Lab, Randy Johnston and Brian Tankersley discuss Scaling New Heights 2026 from Orlando and unpack why this year’s theme, "Strange New World," feels especially relevant for accountants. Randy shares observations from the conference floor, including strong attendance, a large exhibitor presence, sessions on AI, data cleanup, SOPs written with AI, and main stage presentations featuring technology, magic, and thought leadership. The conversation moves from conference recap to practical implications for the profession. Randy and Brian explore how AI is changing advisory services, why clean data remains essential, and why accountants need to understand the difference between deterministic accounting systems and probabilistic AI systems. They also discuss AI governance, privacy policies, EULAs, subprocessors, Microsoft’s compliance posture, and why professional standards require accountants to be more careful with client data than many other business functions. This episode is ideal for accounting professionals who want a grounded perspective on AI’s role in the profession, what was being discussed at one of the year’s major accounting technology conferences, and how firm leaders should think about education, governance, and responsible adoption. Show Notes: Scaling New Heights 2026 used the theme "Strange New World," reflecting the rapid and sometimes unsettling changes created by AI.Randy reported solid attendance of about 2,000 attendees and approximately 133 exhibitors.AI-powered general ledgers and AI-enabled accounting workflows were prominent conference topics.Clean data remains a prerequisite for useful AI output.Sessions emphasized practical AI use, including advisory services, growth strategies, and SOP development.Daniel Susskind’s main stage presentation explored work, professions, education, AI, and artificial general intelligence.Education and change management are becoming central to AI adoption in accounting firms.AI governance is becoming more important than a simple AI policy.Privacy policies, EULAs, subprocessors, and data use for model training require careful review.Microsoft’s compliance and governance approach was discussed as especially relevant for the accounting profession.Accountants must understand that traditional accounting systems are deterministic, while many AI systems are probabilistic.Brian used the vending machine vs. slot machine analogy to explain why AI outputs require review and professional judgment.Pull Quotes "There’s just a lot of things that are strange with AI." - Randy Johnston"You can’t make filet mignon out of hamburger." - Brian Tankersley"Education is the response to AI." - Randy Johnston, discussing themes from Daniel Susskind’s presentation"It is very ish." - Brian Tankersley, on the probabilistic nature of AI"We have to be grown-ups all the time." - Brian Tankersley, on professional obligations around private client data"Last year we said you always start with a policy, but now you’ve got to restrict things with governance." - Randy Johnston

Randy Johnston and Brian Tankersley record on-site in Orlando to debrief a packed week around AICPA ENGAGE 2026 and the annual Thought Leader/40 Under 40 mashup. They open with the Rise 2040 vision project, highlighting mega-trends like the profession’s “great identity shift,” AI as a strategic force multiplier, globalization, and the emerging “trust paradox” created by artificial intelligence. The hosts describe intense roundtable discussions among young tech-enabled CPAs and seasoned thought leaders on associations, evolving business models, and how state societies must reimagine member engagement in a digital, AI-driven world. The conversation then tackles AI and private equity—“AIPE”—and how late-career partners, unfunded buyouts, and underinvestment in technology are driving firms toward PE ownership and forced modernization. They explore return-to-office realities, cybersecurity and AI-powered threats, including federal actions around advanced AI models, and the profession’s persistent self-confidence gap with technology. Randy shares ENGAGE highlights, including his 40th year speaking, a standing-room-only Tech Update and AI prompting session, and a 200-vendor exhibit hall featuring every major publisher and cloud platform. They close with reflections on AI’s ubiquity at ENGAGE, main-stage guests like Ryan Reynolds, and why networking at these events still moves the profession forward.

In this episode of the Accounting Technology Lab, Randy Johnston and Brian Tankersley welcome Kashif Ali, founder of TaxGPT, for a discussion on why general-purpose AI tools such as ChatGPT, Claude, and Gemini are not sufficient for professional tax research and advisory work. Kashif shares his unconventional journey from journalism to software development and entrepreneurship, ultimately leading to the creation of TaxGPT after experiencing firsthand the difficulty of finding reliable tax information. The conversation explores the evolution of AI in tax research, beginning with source-cited answers and progressing toward autonomous agent-based workflows. Kashif explains how TaxGPT differs from consumer AI tools by focusing exclusively on tax and accounting use cases, implementing hallucination controls, maintaining vetted tax knowledge bases, and emphasizing security and professional trust. The discussion also covers agent orchestration, AI operating systems, workflow automation, and the future of accounting firms. Kashif argues that AI should eliminate repetitive compliance work while elevating the value of professional judgment. The panel examines the growing productivity gap between professionals who effectively leverage AI and those who do not. Looking ahead, Kashif predicts firms will increasingly deploy specialized AI agents, reduce reliance on outsourcing, shift toward advisory services, and potentially move away from billable hours toward outcome-based pricing. Key Quotes Quote #1 "The general purpose AI, OpenAI, Claude, and Gemini, those tools are created like social media. They want your attention. They want to keep you engaged. They are not made for accountants and tax work." Timestamp: Approximately 19:45 Quote #2 "Trust but verify." Timestamp: Approximately 06:45 Quote #3 "We're creating the super app for accounting, tax, and advisory firms." Timestamp: Approximately 12:20 Quote #4 "AI matches the capability of who is using it." Timestamp: Approximately 21:25 Quote #5 "The future of work is that all the manual and repetitive redundant work is gone." Timestamp: Approximately 25:55 Quote #6 "We don't want your attention. We want to help you get your work done effectively." Timestamp: Approximately 20:35 Quote #7 "A professional tool should be able to tell you when you're wrong." Timestamp: Approximately 20:15 (paraphrased) Episode Highlights Topics Covered Why general AI models struggle with tax researchHallucinations and trust in AI-generated answersTaxGPT's specialized tax knowledge architectureAgent orchestration and workflow automationAI governance and security considerationsModel Context Protocols (MCPs)AI operating systems for accounting firmsFuture of tax preparation and review workflowsOne-person million-dollar firmsOutcome-based pricing versus billable hoursMajor Takeaways General-purpose AI is optimized for engagement, not professional tax accuracy.Specialized tax AI requires curated knowledge, citations, and hallucination controls.Agent-based workflows are beginning to automate entire tax processes.Human judgment remains critical despite increasing automation.Firms that embrace AI are widening the productivity gap over competitors.AI will increasingly shift accountants from compliance toward advisory services.