Tag: CPA Firms

  • What the best CPA firms do differently with technology

    What the best CPA firms have in common when it comes to technology

    The accounting profession is in the middle of a significant technology shift. AI tools are being evaluated, adopted, and in some cases quietly shelved. Some firms are navigating this well. Others are spending money and getting nowhere.

    The difference is not the tools they chose. It is how they approached the decision.

    After spending time with CPA practices across the country, a clear pattern emerges among the firms getting this right. Six things they have in common. None of them are about which software they picked.

    Software does not fix a broken process

    This is the one that costs firms the most money and produces the least return. A practice with a broken process buys new software hoping the tool solves the underlying problem. It does not. What the firm ends up with is a broken process running on newer infrastructure. Sometimes faster. Still broken.

    The best firms audit their process before they select a tool. They ask hard questions: where does work get stuck? Where does information go missing? Where does the most qualified person in the room spend time on work that does not require their judgment? The answers to those questions determine what technology they actually need. The tool comes last, not first.

    This discipline is less common than it should be. Vendors do not encourage it. Software demos are compelling. The pressure to look like a modern firm is real. The firms that resist that pressure and do the diagnostic work first are the ones that end up with technology that actually performs. The firms that skip it end up frustrated and wondering why a product that looked so good in the demo is underdelivering six months into an implementation.

    Identify the problem clearly before you buy anything. This sounds obvious. The number of firms that skip this step suggests otherwise.

    They stopped waiting for the perfect moment

    There is a version of due diligence that turns into permanent delay. The firms stuck in that loop are not being careful. They are paying the cost of inaction and calling it prudence.

    The best firms made a decision and moved. Not recklessly. They did the work. They evaluated options. And then they committed. They understood that waiting for certainty in a market moving this fast is itself a choice, and not a safe one.

    The accounting firms that adopted cloud-based practice management tools a decade ago did not do so because the technology was perfect at the time. They moved because the direction was clear and the cost of waiting was already showing up in their operations. The same logic applies today. The direction is clear. AI-native solutions are not a future consideration. They are a current reality that a growing number of practices are already building their operations around.

    The window to move with intention, rather than scramble to catch up, is still open. It will not be open indefinitely.

    They treat technology as a judgment amplifier, not a productivity shortcut

    This is the distinction that separates the firms building something durable from the ones chasing a faster version of what they already had.

    The productivity framing goes like this: if this tool saves each accountant two hours a week, multiply that across the team and the year, and the ROI is defensible. That math is real. But it is the wrong question.

    The judgment framing goes like this: what work is currently consuming the time and attention of the most qualified people in this practice, and does any of that work actually require their judgment? If the answer is no, the goal is not to make that work faster. The goal is to remove it entirely, so those people can spend their time on work that only they can do.

    Firms operating from the judgment framing end up in a fundamentally different position. Their senior people are focused on advisory work, on client relationships, on decisions that require experience and expertise. The return on that shift is not measured in hours saved. It is measured in client outcomes, retention, and the kind of professional reputation that does not require a marketing budget to sustain.

    This is the problem Auciera was built to solve. Not faster accounting. Better accounting, by putting the right work in front of the right people.

    They are deliberate about what senior people should and should not be doing

    This follows directly from the point above, but it deserves to be named separately because it requires a management decision, not just a technology purchase.

    Most firms have never had an explicit conversation about role definition in the context of their processes. Senior accountants end up doing work that does not match their seniority because the process demands it of them, not because anyone decided this was the right use of their time. The most qualified person in the room spends Tuesday afternoon chasing a missing document because nobody redesigned the process to prevent it.

    The firms getting this right made it a deliberate call. They looked at where their senior people were actually spending their time, identified which of that work required professional judgment, and structured their process to protect those hours. Technology supported that decision. It did not make it.

    That sequence matters. Leadership decides what the practice should look like. Technology gets deployed in service of that decision.

    They take change management seriously

    Technology adoption fails more often because of people than because of software. The best firms know this going in. They plan accordingly.

    Change management in most practices is an afterthought. The software is selected, the implementation is scheduled, and then someone sends an email to the team. That is not a change management plan. That is an announcement.

    The firms doing this well communicate the why before the what. Staff understand the problem the technology is solving. They understand how their day-to-day work is going to change and why that change is in their interest. They have a forum to raise concerns before go-live, not after. And the change is led by someone with the actual authority to make decisions, not delegated down to whoever had the most availability.

    This takes more time upfront. It consistently saves significantly more time on the back end. Adoption rates are higher, resistance is lower, and the technology gets used as intended rather than worked around by people who were never brought along on the decision.

    They build time for learning into the practice

    The last thing the best firms share is the simplest and the most consistently neglected. They protect time for their people to learn.

    Not a training budget that nobody touches. Not a standing suggestion that staff explore new tools when they find a gap in their schedule. A specific, recurring, protected block of time for education, exploration, and professional development in the context of technology.

    The accounting profession is changing fast enough that the skills and tools relevant today are not identical to what they will be in three years. The firms building learning into their operating model are accumulating institutional knowledge that their competitors are not. That compounds. A team that has been given the protected space to understand new tools, test approaches, and share what they learn is considerably better positioned than one expected to absorb change in the margins of a full workload.

    It is also, for what it is worth, one of the clearest signals a firm can send to its staff that it is investing in them. In a profession where experienced accountants have no shortage of options, that signal matters more than most managing partners acknowledge.

    The firms getting technology right are not the ones with the largest budgets or the most tools. They are the ones that approached the whole thing with discipline: understanding the process before buying the software, committing before certainty arrived, and thinking about technology as something that amplifies the judgment of their best people rather than a substitute for the hard decisions underneath.

    Those six things are not complicated. They are also not common. The practices that get all six right will be in a significantly stronger position three years from now than the ones still waiting for the right moment to start.

    Explore more perspectives on accounting practice, technology adoption, and AI on the Auciera Insights page.

    About the Author

    Auciera's Head of Growth - Patrick Parato

    Patrick Parato is the Head of Growth at Auciera, an AI-native accounting platform built to bring clarity, accuracy, and trust to financial operations. He holds a degree in Computer Science and has spent his career working at the intersection of technology, data, and business systems.

    At Auciera, Patrick helps shape product strategy, platform positioning, and market education, with a particular focus on AI-native system design, financial transparency, and scalable growth. He regularly writes about the role of AI in accounting, the importance of trust in financial systems, and how modern technology can support better decision-making without sacrificing control or accountability.

    With a strong technical background and deep experience in go-to-market strategy, Patrick focuses on how modern software architecture, automation, and AI can be applied responsibly in real-world business environments. His work centers on translating complex technical concepts into practical solutions that business owners and accounting professionals can actually rely on.

  • Why CPA Firms Need More Than AI Tools Like ChatGPT

    Why CPA Firms Need More Than AI Tools Like ChatGPT

    Why CPA Firms Need a Smarter Approach to AI Than ChatGPT or Claude

    General-purpose AI tools are everywhere in accounting firms right now. Here is why that should concern firm leadership.

    Written by Patrick Parato

    Accountants working together using AI chat windows hoping to solve accounting problems.

    Walk through any CPA firm today and you will find the same thing; a senior accountant using an AI chat window to draft a client memo. A junior staff member pasting a financial summary into an AI chat window to pull out key numbers faster. A partner using an AI tool to research a technical issue that would have taken an hour to dig through manually.

    Nobody flagged it as a problem. The outputs look reasonable. The time savings are real. The firm believes it is embracing AI.

    But here is what is actually happening: the firm has adopted a collection of tools with no strategy, no governance, and no accountability. Most partners have no idea the level of risk they are accepting

    There is an important distinction that is getting lost in the rush to use AI: the difference between an AI tool and an AI solution. Understanding that difference is not academic. For a CPA firm, it is a professional obligation.

    The Ad Hoc AI Reality in CPA Firms

    The use of general purpose AI tools in professional services is not a future trend. It is already happening, and it is happening faster than most firm leaders would like to admit.

    Staff are not waiting for an AI policy to show up. They are finding tools that make their work easier and using them. That is not a criticism. It is human nature. When a tool saves you an hour on a task that used to take three, you will keep using it.

    The problem is not the individual. The problem is what happens at the firm level when dozens of people are making dozens of individual decisions about which AI tools to use, what client data was entered into them; and how much to trust the outputs. There is no consistency. There is no oversight. There is no record of any of it.

    This is the ad hoc AI reality that most CPA firms are living in right now. Not a deliberate AI strategy. A collection of individual workarounds that nobody approved and nobody is managing.

    For a profession built on precision, documentation, and accountability, this should make every partner uncomfortable.

    The Risks Firms Are Not Taking Seriously Enough

    Informal AI use is not just an efficiency question. It is a risk question. The risks are specific enough that every CPA firm leader should be paying attention.

    When a staff member pastes client financial data into an AI chat window, that data leaves the firm. General purpose AI tools are not built for the confidentiality requirements of a professional accounting practice. Most free and standard tier versions of these tools use input data to improve their models. Even where opt-outs exist, most users do not know they exist, let alone use them.

    For a CPA firm handling sensitive financial information on behalf of clients, that is not a grey area. It is a liability.

    General purpose AI tools are impressive. They are also wrong in ways that are not always obvious. A confidently written memo with a subtle factual error. A financial summary that missed a nuance in the underlying data. An analysis that looks authoritative but was never verified.

    The problem is not that AI makes mistakes. Every tool can make mistakes. The problem is that informal AI use has no formal review structure built around it. If there is no checkpoint or if there is no second set of eyes, then the output goes straight from the tool to the client.

    This is the risk that should concern CPA firm leaders most. In a profession where documentation is not optional, general purpose AI tools leave no audit trail. There is no record of what was prompted, what was generated, or who reviewed it.

    Beyond the individual transaction, the absence of governance means every staff member is making their own decisions about which tools to use, how to use them, and how much documentation to capture. Two accountants at the same firm handling similar client work may be applying completely different standards without anyone knowing. That inconsistency is invisible until something goes wrong. At that point it is very visible.

    The Difference Between an AI Tool and an AI Solution

    This is the distinction that matters most and gets discussed least.

    ChatGPT and Claude are large language models. They are general purpose tools built to handle an enormous range of tasks across an enormous range of industries. That breadth is their strength. It is also their limitation for professional accounting work.

    A general purpose AI tool does what you tell it to do. It has no understanding of your firm, your clients, your workflows, or your professional obligations. It does not know the difference between a reconciliation that is complete and one that needs a second look. It cannot flag an anomaly in a client’s books because it has no context for what normal looks like. It generates outputs based on what you prompt it with, and it stops there.

    A purpose-built AI accounting solution is built differently from the ground up. It is designed around accounting workflows, not around general language tasks. It understands the structure of financial data. It flags exceptions. It validates outputs against expected patterns. It maintains a complete record of every action taken, every output generated, and every human decision made along the way.

    The difference is not cosmetic. It is architectural.

    Think of it this way. A general purpose AI tool is like hiring a brilliant generalist who has read everything but has never worked in accounting. Impressive in conversation. Unreliable when the details matter and the stakes are high.

    A purpose-built AI accounting solution is built by people who understand accounting deeply, designed for the specific workflows CPA firms run every day, and governed in a way that meets the professional standards the profession demands.

    At Auciera, this distinction is the foundation of everything we build. Our platform is designed specifically for accounting workflows, with governance, audit trails, and human oversight built in from day one. Not added later. Built in.

    What Good AI Adoption Looks Like in a CPA Firm

    Getting AI right in a CPA firm is not about moving the fastest. It is about moving deliberately.

    The firms that will look back on this period with confidence are not the ones that banned AI tools entirely, nor the ones that let informal adoption run unchecked. They are the ones that made intentional decisions about where AI fits, how it is governed, and what standards it is held to.

    Here is what that looks like in practice.

    Start with an honest assessment of what is already happening in your firm. Before you build a policy or evaluate a solution, find out what tools your staff are already using and how. You may be surprised. In most firms the informal AI adoption is further along than most realize, or willing to admit.

    Establish clear guidelines about what data can and cannot be used with general purpose AI tools. Client financial data, confidential communications, and sensitive business information should never be going into an ungoverned tool. That is a policy decision that costs nothing to make and protects the firm immediately.

    Evaluate AI solutions the same way you evaluate any professional tool: not just on what it can do, but on how it is governed. What is the audit trail? Who is accountable for the outputs? How does it handle client data? How does it integrate with your existing workflows? These are not technical questions. They are professional ones.

    Recognize that AI adoption is not a one-time decision. It is an ongoing practice. The firms that build governance frameworks now will find it significantly easier to scale AI responsibly as the technology continues to evolve. The firms that skip that step will be rebuilding from scratch later, under more pressure and with more to unwind.

    The Firms That Lead This Will Not Be Going Back

    AI is not a phase CPA firms are passing through. It is the new operating environment.

    General purpose tools like ChatGPT and Claude have a place. They are powerful, accessible, and genuinely useful for a wide range of tasks. But useful is not the same as appropriate. And for a profession where documentation, accountability, and client confidentiality are not optional, the difference between a tool and a solution is not a minor technical distinction. It is a professional one.

    The Auciera solution is designed specifically for accounting workflows, with governance, audit trails, and human oversight built in from day one. It also gives practitioners AI accounting guidance in plain language, when they need it.

    The firms that get this right will not just avoid the risks outlined in this article. They will build something more valuable: an AI practice that is consistent, defensible, and scalable. One that clients can trust, regulators can review, and staff can rely on.

    That is not a complicated goal. But it requires making a deliberate choice rather than letting informal adoption make it for you.

    The firms that make that choice now will not be going back.

    This article reflects the perspective of the Auciera team based on ongoing conversations with CPA firms and accounting professionals.

    About the Author

    Auciera's Head of Growth - Patrick Parato

    Patrick Parato is the Head of Growth at Auciera, an AI-native accounting platform built to bring clarity, accuracy, and trust to financial operations. He holds a degree in Computer Science and has spent his career working at the intersection of technology, data, and business systems.

    At Auciera, Patrick helps shape product strategy, platform positioning, and market education, with a particular focus on AI-native system design, financial transparency, and scalable growth. He regularly writes about the role of AI in accounting, the importance of trust in financial systems, and how modern technology can support better decision-making without sacrificing control or accountability.

    With a strong technical background and deep experience in go-to-market strategy, Patrick focuses on how modern software architecture, automation, and AI can be applied responsibly in real-world business environments. His work centers on translating complex technical concepts into practical solutions that business owners and accounting professionals can actually rely on.

  • How AI Is Changing Accounting Work

    AI Is Rewriting the Rules of Accounting. Here Is What Firms and Professionals Need to Know.

    AI is compressing entry-level work, disrupting the apprenticeship model, and raising the stakes for firms that move too slowly.

    Written by Andrew Ross

    Artificial intelligence is often discussed in extremes: either as a breakthrough productivity tool or as a direct threat to employment. In practice, the more useful view is that both dynamics are unfolding at once. AI can improve output, shorten cycle times, and reduce the cost of routine knowledge work. At the same time, it is forcing organizations to rethink roles, workflows, controls, training, and leadership expectations.

    That matters for the accounting profession because accounting work sits close to information, analysis, documentation, compliance, and judgment; precisely the kinds of activities AI is beginning to compress. The central issue is not whether AI will eliminate the profession. It will not. The issue is that AI is changing how work is performed, which skills are developed first, and how firms will train the next generation of professionals.

    AI as a Force Multiplier: What It Means for Accounting Firms

    The economic case for AI is substantial. Generative AI is expected to create meaningful productivity gains across a wide range of business functions, particularly in knowledge-intensive work. That matters in accounting because much of the profession depends on reviewing information, preparing first drafts, summarizing issues, documenting conclusions, and moving work through structured processes.

    But AI does not replace whole professions all at once. Jobs are made up of tasks, and AI tends to affect tasks first. It can accelerate drafting, summarizing, reconciling, researching, reviewing, and preparing a first-pass analysis. As those activities are compressed, the human role moves upward;  toward interpretation, judgment, client communication, exception handling, and accountability.

    That is why AI should first be understood as a force multiplier, not simply a headcount story. In the short term, it raises the output of individuals and teams. Over time, however, those same productivity gains can reshape staffing models, skill requirements, promotion paths, and the number of people needed to perform certain categories of work.

    In a CPA firm, that shift is already becoming visible. Entry-level professionals are likely to spend less time manually assembling first drafts and more time using firm-approved AI tools to generate an initial work product, then validating outputs, investigating exceptions, documenting the basis for conclusions, and translating the results into clear recommendations for manager review and client delivery.

    The same pattern is emerging in audit. AI can assist with documentation review, draft communications, data comparison, and first-pass research under human oversight. Yet the core professional expectation remains unchanged: the engagement team is still responsible for the quality of the work, the adequacy of the evidence, and the exercise of professional judgment. AI may accelerate the process, but it does not relieve the professional of responsibility.

    This distinction is critical. Across accounting and audit guidance, the message is consistent: AI can augment the work, but it cannot replace professional skepticism, oversight, or accountability for the final result.

    The Workforce Is Already Changing. Accounting Is Not Immune.

    The labour-market implications of AI are becoming easier to see. Technological change is expected to create new categories of work while compressing or displacing others. That sounds manageable in the aggregate, but transitions are rarely smooth. Job creation and job displacement do not happen in the same places, at the same speed, or for the same people.

    The pressure is likely to be felt earliest in routine, document-heavy, and process-oriented work, especially where AI can produce a competent first draft or first pass. Entry-level roles are particularly exposed because they often include the kinds of tasks AI can automate quickly: gathering information, summarizing documents, preparing routine communications, coordinating basic workflows, and providing standard analytical support.

    For accounting firms, that matters because many of these activities have historically served as the training ground for junior professionals. Early-career employees did not simply produce work; they learned through repetition. They prepared the first draft, assembled the binder, reconciled accounts, researched issues, built schedules, and documented routine findings. That work was not glamorous, but it helped develop discipline, pattern recognition, technical fluency, and judgment.

    Consider a junior auditor assigned to a year-end engagement. In the past, that employee might have spent much of the engagement vouching transactions, preparing working papers, and documenting routine procedures. In an AI-enabled workflow, those responsibilities are likely to shift toward reviewing AI-generated outputs, investigating exceptions, validating evidence, and documenting issues that require an audit manager’s attention.

    That change is important because it alters not only productivity, but the apprenticeship model itself. If AI performs more of the foundational work that once trained junior staff, firms will need new ways to develop judgment in early-career professionals through post-secondary education, structured in-firm training, closer supervision, and more deliberate review models. Otherwise, firms may gain short-term efficiency while weakening their long-term talent pipeline.

    The Cost of Standing Still

    The most important risk may not be outright job loss, but declining relevance. As AI becomes more embedded in professional work, the divide may widen between organizations that redesign work intentionally and those that continue to rely on older workflows. The same is true at the individual level.

    Companies that move too slowly may preserve familiar processes for a time, but they also risk higher costs, slower response times, and weaker client experience than more adaptive competitors. Professionals face a parallel challenge. Those who treat AI as optional may remain employable, but they may find themselves working with less leverage, narrower responsibilities, and fewer advancement opportunities than peers who learn how to use AI effectively inside a controlled professional environment.

    That said, adaptation should not be confused with uncritical acceptance. AI literacy is not merely the ability to prompt a model. It includes the ability to test outputs, identify hallucinations, protect confidential data, understand process risk, and recognize when human judgment must override a machine-generated suggestion. In professional settings, particularly those involving audit, tax, reporting, compliance, or financial decision-making; responsible adoption matters as much as rapid adoption.

    The future advantage will not belong to the professionals who use AI most casually. It will belong to those who can use it productively without outsourcing judgment.

    The Firms That Win Will Redesign, Not Just Automate

    The long-term winners in this transition are unlikely to be the individuals or firms that simply automate the greatest number of tasks. The more important opportunity lies in redesigning workflows intelligently.

    For accounting firms, that means using AI to remove low-value friction while reinvesting human time into higher-value work: stronger analysis, better client advice, faster decisions, improved controls, and more timely escalation of risk. It also means building organizations that can scale AI responsibly rather than treating each use case as an isolated experiment.

    In practice, that could include AI-assisted preparation of tax return drafts with mandatory human review, AI-supported audit documentation with clear escalation thresholds, and exception-based review models that teach junior staff how to challenge outputs rather than simply produce them. Used properly, AI can reduce repetitive effort. Used poorly, it can create false confidence, weaken documentation standards, and erode professional learning.

    For firm leaders, the agenda is clear: move beyond pilots, establish governance, redesign workflows, train people, and rethink how capability is built at the entry level. For managers, the priority is to create review structures that preserve quality while helping staff develop judgment. For early-career professionals, the challenge is to become AI-literate without losing the technical discipline, skepticism, and communication skills that define strong accountants.

    Judgment Is Still the Advantage

    AI will not make accounting expertise irrelevant. It will change how that expertise is expressed.

    In the years ahead, the professionals who advance will be those who can combine technical credibility with adaptability, critical thinking, communication, and the discipline to use AI without surrendering judgment. The firms that succeed will not be those that automate most aggressively, but those that redesign work in a way that improves productivity without weakening quality, training, or accountability.

    The workplace is not simply adding another tool. It is moving toward a new operating rhythm.

    This Editorial Opinion reflects the perspective of the Auciera team based on ongoing conversations with accounting professionals and regulators.

    Author

    Andrew Ross, CPA, CMA

    Andrew A. Ross, CPA, CMA

    Andrew Ross, CPA, CMA, is the Co-Founder and CEO of Auciera, an AI-native accounting platform built for accounting professionals and businesses that demand clarity, control, and confidence in their financial operations. Andrew brings over 25 years of accounting, tax, and financial management experience across public practice, consulting, and academia. He spent nearly a decade at two of the world’s leading professional services firms, serving as Senior Manager of Tax at EY and Performance Management Consultant at PwC, where he advised organizations on tax performance and enterprise financial decision-making. He has also held senior roles at Longview Solutions and MicroStrategy, giving him a deep understanding of how technology intersects with financial operations at scale. Since 2018, Andrew has served as a Professor of Accounting and Tax at Humber College, where he continues to shape the next generation of accounting professionals. His academic work reflects the same principle driving Auciera: that rigorous professional judgment and governance are non-negotiable, regardless of what tools are doing the work.

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