Ajay Vashee’s Post

𝗛𝗼𝘄 𝗱𝗼 𝘆𝗼𝘂 𝗱𝗲𝘀𝗶𝗴𝗻 𝗮 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝗳𝗼𝗿 𝗮 𝗚𝗲𝗻𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝘄𝗶𝘁𝗵 𝗮𝗻 𝗲𝗻𝘁𝗶𝗿𝗲𝗹𝘆 𝗼𝗽𝗮𝗾𝘂𝗲 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗺𝗮𝗸𝗶𝗻𝗴 𝗽𝗿𝗼𝗰𝗲𝘀𝘀—𝗮 "𝗯𝗹𝗮𝗰𝗸-𝗯𝗼𝘅"? This is how you build confidence. ✅ We all dread the "black-box" of technology — mysterious operations accounting systems perform. With the advent of GenAI, this has become even more challenging! 🤔 Many suggest, "we'll have a human copilot," but this overlooks the complexities of GenAI. If you plan to double-check everything, why invest in GenAI tech? 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗚𝗲𝗻𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀 ➡️ GenAI applications are built with GenAI models (like OpenAI, Anthropic, etc.) wrapped inside purpose-built software. ➡️ Traditional software components: Much of the software remains traditionally programmed, so conventional application controls (e.g., SOC1, testing) still apply. ➡️ GenAI actions: These mimic human decision-making using data and training to provide the best answers to the problems presented. Just like with human actions, you can't (yet) peek inside their heads to understand their exact logic and process—the same is true for GenAI. 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗖𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝗰𝗲 𝗶𝗻 𝗚𝗲𝗻𝗔𝗜 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 So, how do you get comfortable with a technological process that operates like both a system and a human? 🤯 ➡️ Follow Normal System Implementation Controls Thorough user testing and documentation are still 100% applicable to GenAI. HOWEVER, you'll need robust procedures to identify when the technology or underlying GenAI models change, to determine if additional testing is needed. ➡️ Understand the GenAI Tech Thoroughly examine the tech you're implementing to understand what aspects are programmed vs. GenAI-driven. Unfortunately, this isn't always easy to parse out. ➡️ Define Reliance Levels and Risk Clearly define how you're relying on the system and the risk associated with this reliance (considering likelihood and impact). This sets the stage for the necessary level of diligence. ➡️ Develop Validation Controls Create specific validation checks (likely done by a human) that target ALL the GenAI actions you rely on. The best validation approach today is sample-based reperformance, which I strongly recommend until industry-accepted standards for GenAI reliance emerge. ➡️ Document and Resolve Thoroughly document your validation procedures (to support internal and external audits), including any errors/mistakes made by the GenAI. All errors/mistakes noted must be thoroughly vetted for impact and resolved to ensure we can rely on GenAI decisions. Following these steps will boost your confidence in using GenAI and help get your auditors onboard. How are you approaching controls around GenAI tools? Have you been able to get comfortable with the technology? Share your insights in the comments or DM me for assistance! 

💡Discover how machine learning is revolutionizing the accounting world! Did you know that ML algorithms can automate accounting processes like expense reports, risk assessment, and accounts payable? Get ahead with the online Master of Accountancy Professional Track program from Northern Kentucky University (NKU) and dive into the future of ML accounting. 💼Clients expect innovative services, and accountants are meeting those demands with AI technology. By automating tasks, improving functionality, and boosting productivity, machine learning is changing the game. Stay competitive in the accounting field with the power of AI and robotic process automation (RPA) to streamline processes and enhance accuracy. 🔍Explore the future landscape of reporting, auditing, and attestation with machine learning. Discover how technology such as speech and facial recognition can revolutionize risk assessment processes. Linking AI with business intelligence is reshaping how data is transformed into actionable insights, providing a deeper understanding of financial data. Join the wave of accounting professionals leveraging ML and AI technology with big data for enhanced business processes. 📚NKU’s Master of Accountancy Professional Track program offers courses in advanced auditing, forensic accounting, federal taxation, and more. Equip yourself with the knowledge to tackle the changing technological landscape in accounting, preparing you for a successful career in financial services. Start your journey with NKU today! https://lnkd.in/exA37-kg

The Future of Accounting according to ChatGPT-Part 1-Repost. The future of accounting is likely to be shaped by various technological advancements, evolving business models, and changes in the regulatory environment. While it's impossible to predict the future with certainty, here are some key trends and developments that are expected to shape the accounting profession in the coming years: 1. Automation and Artificial Intelligence (AI): Advances in automation and AI technologies will continue to transform accounting tasks, streamlining repetitive processes and reducing the time spent on manual tasks. This will allow accountants to focus more on value-added activities such as financial analysis, strategic planning, and consulting. 2. Data Analytics and Big Data: As businesses generate increasing amounts of data, accountants will need to leverage data analytics tools and techniques to extract valuable insights from this information. This will require accounting professionals to develop their data analysis skills and become proficient in using relevant software tools. 3. Cloud Computing: The widespread adoption of cloud-based accounting systems will continue to reshape the way accountants work. These systems offer increased accessibility, scalability, and efficiency, enabling accountants to collaborate more effectively with clients and colleagues. 4. Evolving Regulatory Environment: As regulatory requirements change and become more complex, accountants will need to stay informed about new laws and regulations that impact their clients and their practice. This will require continuous learning and adaptation to ensure compliance with the latest standards. Kindly stay tuned to part 2 of this article. Post credit: David Bergstein, CPA, CITP, CGMA Oyindamola Adeleye, ACA

AI is shaking up the accounting arena in ways we never imagined. Just stumbled upon an enlightening article that dives deep into the world of AI in accounting, and it’s a game-changer for professionals in the field. Here are some key takeaways that I found intriguing: - Not Just ChatGPT: While many think of AI accounting as merely the use of ChatGPT for daily tasks, the scope is much broader! We’re talking machine learning, computer vision, and even robotics making their way into day-to-day accounting functions. - Efficiency is Key: AI tools are significantly enhancing productivity and cost-efficiency for businesses. From automating invoice processing to anomaly detection in financial data, the practical applications of AI are profound. Figures show top firms are already leveraging AI and leading the charge toward a more automated future. - The Big Four Leading the Charge: Major CPA firms are at the forefront, utilizing AI for predictive analytics and client insights. This is not just about making things easier; it's about transforming how decisions are made and how businesses communicate with clients. - Job Growth, Not Loss: Interestingly, contrary to the fear that AI might take over jobs, it seems more likely to shift roles toward higher-level strategic thinking. Think less data entry and more decision-making. - Future-Proofing Your Skills: For anyone in accounting, embracing AI technology isn’t an option—it's a necessity. The future is about integrating advanced AI tools into existing workflows to enhance effectiveness. It seems we’re on the brink of a revolution in accounting, and the best part? The future is bright for those ready to adapt! Let's discuss: What are your thoughts on AI's impact on the accounting industry? Have you started integrating any AI tools into your practices? https://lnkd.in/eWqiytaJ

Impact of Technology on the Accounting Profession Technology has made an undeniable impact on the accounting industry. Before accountants had computers, they had to use calculators to manually reconcile financial documents against paper ledgers. Records were significantly less accurate than they are today, and calculation errors were difficult to catch. The advent of computer-based accounting technology dramatically changed the accounting industry. The most significant technological changes occurred after accounting software became widespread. How Has Software Changed the Accounting Profession? Of all the information technology advancements that have shaped the accounting industry, software has had the largest impact. In the latter half of the 20th century, technology companies developed innovative spreadsheet software for accountants to use on computers. Instead of using handwritten ledgers and calculators, accounting professionals could now automate equations in an electronic spreadsheet. Spreadsheet software allowed public accounting professions to spend less time on tedious tasks and focus more on finding solutions for high-level issues. Early spreadsheet software paved the way for more advanced technology, including automated accounts payable software and payroll and tax automation programs. Automated accounts payable software eliminated the need for manual data entry by pulling essential information from financial documents and entering that information into a database. Payroll and tax automation software streamlined human resource tasks by automatically calculating payments, applying tax rates, and storing employee tax information. Recent Changes in the Accounting Profession Over the past few years, accounting technology has advanced to adapt to changing needs in the workforce. Here are some of the major technological advancements that have impacted the accounting industry recently:     1.Artificial Intelligence & Robotic Process Automation: Artificial intelligence and robotic process automation (RPA) automate complex and repetitive tasks and processes with extreme accuracy, thereby reducing operating costs and increasing efficiency. These are some of the emerging technologies supporting the transitional role of today’s accountant into a more critical thinking role. The Association of Chartered Certified Accountants (ACCA) takes it a step further in their report, Explainable AI: Putting the user at the core, by stating that AI is most relevant for accountants and auditors when a user can explain its functionality. 2. Big Data & Natural Language Processing(NLP) A major way artificial intelligence is modernizing accounting is through its marriage with big data. Accounting firms have access to enormous amounts of unstructured data that would have previously been almost impossible to analyze. Through natural language processing (NLP), accountants can offer more accurate and valuable insights for better client outcomes. ....

Don't read this if you're selling or investing in AI. It won't help. Assuming biases have not completely distorted and/or exaggerated what's possible with AI (which they have), to summarize just because a theory, concept, model, or framework is possible or a seemingly good idea (from afar) doesn't mean it has any chance of being adopted into more than 0.001% of technology. Engineers who know a select few technologies well, they learned in the 90's or early 2000's, and refuse to progress and learn more shouldn't design the future of technology (or should they?). Technology has come a long way since then. These engineers are betting their knowledge will either come back into style, or that the type of codebases they build and maintain have high sunk costs making their knowledge fully required, and difficult to replace. Next consider the example of REA model "Resources, events, agents (REA) is a model of how an accounting system can be re-engineered for the computer age. REA was originally proposed in 1982 by William E. McCarthy as a generalized accounting model, and contained the concepts of resources, events and agents (McCarthy 1982)." This flexible model was novel at the time. It could be used to develop business software that both non-accounting, and accounting professionals could use. Don't forget "accounting is the language of business". It's extremely useful REA gives us a way features can be written for non-accountants and at the same time transactions end up on the journal, financial statements can be generated, and thus this design pattern can turn this same application into something useful for an accountant. In short, migrating all business and accounting system codebases to use the REA model lost steam quickly. Not a complete failure, it's used by a few well known products, and in education. It wasn't feasible to force different design patterns to mesh, so couldn't be integrated into existing projects and codebases, and likely wasn't even considered for others (even though it could have been considered and potentially used). REA is one of the millions of examples of how just because a good idea is developed it's rarely adopted. I predict once the hype burns out on AI there will many business backends that never incorporate AI. Business as usual will come back in and there will be dead end AI projects everywhere that will need to be dealt with. When there are so many applicants for every job it's easy to give people the wrong illusion of why they're not being hired. Leaders need vision. There is a heard mentality. Bias is common. Same politics is used in designing software as getting bills to pass. https://lnkd.in/gedYrPp8

How do we solve the conundrum behind automated accounting? In the epoch of the Digital Revolution, the quest for autonomous accounting and enriched fiscal transactions is paramount. It’s the key to the utopia of instantaneous financial reporting, a game-changer in our global economy. Data, the lifeblood of our cosmic commerce, is growing exponentially. To decrypt the past and foresee the future, we must infuse each transaction with a vast amoung of information. This enrichment allows us to scrutinize transactions from myriad perspectives - tax, financial, managerial, and even from the viewpoint of every possible customer. Currently, this enrichment is performed manually by our finance department or those procuring goods and services. This often leads to transaction aggregation, compromising the granularity of our data. But our AI require complete information on all transactions, a volume of data challenging for humans but a mere byte for AI. The conundrum then is: how do we optimize the enrichment of our transactional data? How do we add all the necessary parameters currently input by different entities? As we move towards great effeciancy and effectiveness, we build vast data models. But we always return to the principle that the unique key for all areas needs to be present in the financial transactions. In conclusion, to harness the power of AI in our financial transactions, we must automate the enrichment of transactional data. This involves understanding the purpose of each transaction, ensuring efficient data collection, and using advanced technology to manage the data required for comprehensive analysis. This is the interstellar challenge we face - help me unravel this cosmic conundrum

AI is exciting and is dominating the headlines. But, if you still have data processes that involve downloading data from one system, messing around with it in Excel, then uploading it into another system, you should be looking at automating that before anything else. And that goes for most accountants! There's a ton of proven, affordable solutions that can deliver immediate ROI. But for many in the office of finance, they seem technical and hard to understand — but with a few tips you can get started today. The business case for integration First, it's good to think about why we might want to do that. Since so many of us process data flows manually, it's easy to forget that it doesn't have to be that way — and that it comes with steep costs. Time is a huge one. Every accountant wants to be spending time on delivering value to the business; spreadsheet jockeying takes us away from that. Errors are another. Manual work always invites errors! And then we waste even more time double and triple checking. Manual processes also hold us back from timely reporting. How useful would the business find it if we could deliver numbers every day instead of every week or month, with no additional overhead? And don't underestimate the impact on morale. Will people want to work for us if we make them waste time on manual data work? Something to consider as we navigate the shortage of accounting talent. Exploring automation Getting automated doesn't have to be scary. First, take an inventory of what you need to integrate — and don't just consider the worst offenders. What are your systems — and are they on-premise, hosted or cloud? How often do you need the data to move? What time period should each process cover? Are there any data quality checks that need to happen (for missing fields, incorrect formats etc.)? Most importantly, what data needs to move where, and do we need to change it along the way? Investigate your options Then, there are three main options to explore. Many of your systems will probably have a set of built-in or "native" integrations with other tools that they are commonly used with. They're always worth checking out as they can be very convenient, being within a system you already use, and can often solve a problem for you very neatly — often at a very good price point. However, they only offer specific use cases; if you want something else, you may be out of luck. They also may not scale with volume — it's best to test with the vendor. Most importantly, they only solve a slice of the problem. You have a whole pile of applications that need to work together, and it's unlikely that built-in integrations exist for everything you need. Even if they do, the ease and cost benefits of this option start to go away when you have a lot of them! Reach out to me for more tips on how to integrate your manual bookkeeping and accounting processes using simple cloud based software at an affordable cost. Cheers!

The Future of Accounting according to ChatGPT-Part 1 The future of accounting is likely to be shaped by various technological advancements, evolving business models, and changes in the regulatory environment. While it's impossible to predict the future with certainty, here are some key trends and developments that are expected to shape the accounting profession in the coming years: 1. Automation and Artificial Intelligence (AI): Advances in automation and AI technologies will continue to transform accounting tasks, streamlining repetitive processes and reducing the time spent on manual tasks. This will allow accountants to focus more on value-added activities such as financial analysis, strategic planning, and consulting. 2. Data Analytics and Big Data: As businesses generate increasing amounts of data, accountants will need to leverage data analytics tools and techniques to extract valuable insights from this information. This will require accounting professionals to develop their data analysis skills and become proficient in using relevant software tools. 3. Cloud Computing: The widespread adoption of cloud-based accounting systems will continue to reshape the way accountants work. These systems offer increased accessibility, scalability, and efficiency, enabling accountants to collaborate more effectively with clients and colleagues. 4. Evolving Regulatory Environment: As regulatory requirements change and become more complex, accountants will need to stay informed about new laws and regulations that impact their clients and their practice. This will require continuous learning and adaptation to ensure compliance with the latest standards. Kindly stay tuned to part 2 of this article. Post credit: David Bergstein, CPA, CITP, CGMA What action point are you taking as an accountant to stay cutting edge based on the trends above?

Generative AI in Accounting: A Game Changer 🌟 I recently read Sam Boboev 's insightful post about the transformative impact of Generative AI on accounting, and I couldn't agree more with his points. As we witness this technological revolution, it's clear that AI is set to redefine how we approach various accounting functions. Here are some of my thoughts on this exciting development: 🔸 Data Collection and Ingestion Data collection has always been a painstaking process, involving manual data entry and reconciliation from diverse sources. With advancements in Open Banking and the introduction of LLMs, this process is becoming increasingly automated and efficient. AI copilots are now capable of extracting data from unstructured formats like contracts and invoices, streamlining data management and enhancing accuracy. 🔸 Research The research component of accounting is another area ripe for innovation. LLMs can navigate the complex web of tax codes, accounting standards, and regulatory filings with remarkable precision. This not only speeds up the research process but also ensures that accountants have access to the most accurate and up-to-date information, allowing for more informed decision-making. 🔸 Report Generation and Filing Generating and filing reports is an essential but often tedious task. LLMs can draft summaries, create audit-ready reports, and ensure documents adhere to specific styles, significantly reducing the time spent on these activities. This allows accountants to focus more on analysis and strategic planning. 🔸 Client Service and Advice Perhaps the most exciting potential of Generative AI lies in client service and advice. By providing regular financial analysis and optimization insights, AI can help convert transactional client interactions into ongoing engagements. This is particularly valuable for startups and SMBs that may lack sophisticated in-house finance functions. Fine-tuned, industry-specific models promise to elevate the quality and scalability of the advice accountants can offer. As these advancements continue to reshape our industry, the role of accountants is evolving into that of trusted advisors. With AI-powered tools like WebAccountPlus (Holding) AG, accountants are better equipped to offer strategic insights and proactive advice, driving value for clients in ways previously unimaginable. This evolution underscores the importance of embracing technology to stay ahead in the field. Generative AI is not just a tool; it's a catalyst for change, pushing the boundaries of what's possible in accounting. The future looks bright, and I'm excited to see how we, as professionals, can harness this technology to deliver even greater value to our clients. #Accounting #AI #GenerativeAI #FinanceInnovation #ClientService #DataManagement #Research #ReportGeneration #WebAccountPlus