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Today’s AI Hallucination

Today, AI effectiveness is only as good as the data standardization. By 2023, AI won’t need need data standardization to do a prefect job.

Today’s Menu

• My Weekly Editorial: Solve for the AI in Accounting & Finance: Quality, Speed and Cost

• ARK Investment 2023 Big Ideas

• Top 10 ChatGPT Tips to Write Perfect Prompts

• AI Accounting News

My Weekly Editorial: Solve for The AI in Accounting & Finance: Quality, Speed and Cost

Disclaimer: The views expressed in this article are my personal views. They do not express the views of my firm, my family or friends. In addition, these views represent my modest reflections at the current moment. I reserve the right to change or modify my views in the future.

Intro & Conclusion

At the end of the day, the ultimate purpose of AI in accounting and finance (and I can argue that this can apply to any other industries or profession), is to solve for three objectives: provide superior quality of work (1), at a much faster speed (2) and lower cost (3) than humans.

My AI Equation Thesis

I think we all can agree that Artificial Intelligence (AI) stands out as a powerful tool with the potential to revolutionize the industry. As accounting and financial professionals, it is crucial to understand how AI is working towards three primary objectives: delivering superior quality, faster execution, and cost-efficiency when compared to traditional accounting and finance methods.

1. Quality: Raising the Bar Beyond Human Capabilities

Quality is paramount in the world of accounting and finance, where precision and accuracy are non-negotiable. At my job, I’ve always told my team that “without quality, we have NOTHING!”. AI systems are designed to meticulously analyze vast datasets, uncover patterns, and generate insightful reports with unprecedented accuracy. By eliminating human errors and biases, AI ensures that financial statements, audits, analyses and compliance reports are more reliable than ever before.

One of the key advantages of AI in quality enhancement is its ability to process large volumes of data swiftly. It can spot discrepancies and anomalies that might go unnoticed by human accountants. Moreover, AI-driven predictive analytics can help identify potential financial risks and opportunities, providing invaluable insights for decision-makers.

Counterargument: Potential for Algorithmic Bias and Lack of Judgment

AI systems, despite their accuracy, can perpetuate bias present in historical data. They make decisions based on patterns learned from the past, which may include biases. Additionally, AI lacks the human judgment and context-awareness that accountants possess. In complex situations or unique cases, accountants can exercise discretion and professional judgment, which AI may struggle to replicate accurately.

2. Speed: Accelerating Task Execution

In the fast-paced world of finance, time is money. Traditional accounting processes can be time-consuming, often requiring hours of manual data entry, reconciliation, and analysis. AI, on the other hand, can complete these tasks in a fraction of the time, allowing organizations to make informed decisions more swiftly.

AI-powered automation streamlines routine accounting tasks such as invoice processing, transaction categorization, and reconciliations. This not only reduces the workload on accountants but also minimizes the risk of delays or oversights. Consequently, businesses can close their books faster, meet regulatory deadlines, and respond promptly to market fluctuations.

Counterargument: Overlooking Nuances and Risk of Oversimplification

The speed of AI in processing tasks may lead to oversimplification. AI systems often follow predefined algorithms, which might not account for nuanced situations or evolving regulations. Rushing through tasks to meet deadlines could result in crucial details being overlooked, potentially causing errors that require time-consuming corrections.

3. Cost Efficiency: Redefining Resource Allocation

Cost considerations are a constant concern in the accounting and finance industry. Hiring and retaining skilled accountants can be expensive, and manual processes can be resource-intensive. AI offers a cost-effective alternative, as it can perform many tasks at a lower operational cost.

By automating repetitive and time-consuming tasks, AI frees up human accountants to focus on more strategic activities, such as financial analysis, strategic planning, and client advisory services. This not only enhances the value accountants bring to their organizations but also allows firms to allocate resources more efficiently.

Moreover, AI can help reduce the likelihood of costly errors, which can have significant financial implications. By improving accuracy and reducing the risk of non-compliance, AI can save organizations from potential fines and legal repercussions.

Counterargument: Initial Implementation Costs and Job Displacement Concerns

While AI can be cost-effective in the long run, the initial implementation can be expensive. Integrating AI systems into existing infrastructure and training staff to use them effectively requires an upfront investment. Moreover, the fear of automation leading to job displacement among accountants is a valid concern. Organizations may need to balance cost savings with the potential social and ethical implications of reducing human roles in the industry.

Well, Let’s Have A Deeper Conclusion

In conclusion, Artificial Intelligence is making remarkable strides in the realm of accounting and finance, aligning its efforts with three key objectives: enhancing quality, accelerating task execution, and optimizing cost efficiency. By embracing AI as a tool to achieve these objectives, accountants can not only improve the quality of their work but also provide faster and more cost-effective services to their clients. It's not about replacing accountants; it's about empowering them to excel in their roles and meet the ever-increasing demands of the industry. Embracing AI is not just a choice; it's the path to a more efficient and effective future for the world of accounting and finance.

However, It's crucial for accountants and financial professionals to approach AI adoption thoughtfully, considering these counterarguments alongside the benefits. AI should be viewed as a complementary tool rather than a complete replacement, allowing accountants to leverage its strengths while still exercising their expertise, ethics, and judgment to provide the best possible service to clients and organizations. Striking the right balance between AI and human skills is the key to realizing the full potential of technology in accounting and finance.

ARK Investment AI Predictions

Last week, I came across ARK Investment big ideas for 2023. ARK is an investment management firm that manages several actively managed exchange-traded funds (ETFs) in new technologies. ARK predicts the following:

• Generative AI made waves this year, from DALL-E-2 to ChatGPT. These tools are improving the productivity of knowledge workers—~2x in the case of AI coding assistants.

• AI training cost declines continued at an annual rate of 70%, the cost to train a large language model to GPT-3 level performance collapsing from $4.6 million in 2020 to $450,000 in 2022. We expect cost declines to continue at a 70% rate through 2030.

• AI should increase the productivity of knowledge workers more than 4-fold by 2030. At 100% adoption, AI could increase global labor productivity ~$200 trillion, dwarfing the ~$32 trillion in total knowledge worker salaries.

For more details, click on ARK Big Ideas.

Top 10 ChatGPT Tips

The following are prompts to help you write perfect prompts:

1. Tone: Specify the desired tone (e.g. formal, casual, informative, persuasive).

2. Format: Define the format or structure (e.g. essay, bullet points, outline, dialogue).

3. Act as: Indicate a role or perspective to adopt (e.g. expert, critic, enthusiast).

4. Objective: State the goal or purpose of the response (e.g. inform, persuade, entertain).

5. Context: Provide background information, data, or context for accurate content generation.

6. Scope: Define the scope or range of the topic.

7. Keywords: List important keywords or phrases to be included.

8. Limitations: Specify constraints, such as word or character count.

9. Examples: Provide examples of desired style, structure, or content.

10. Deadline: Mention deadlines or time frames for time-sensitive responses.

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