Industry
Manufacturing
Future-Ready Manufacturing: Partnering in your journey to a sustainable manufacturing enterprise
Highlights
- Now it is time for finance leaders in manufacturing to harness Gen AI, moving from reactive decisions to predictive insights and transform the financial landscape.
- Gen AI will pull the finance and accounting from “reactive actions” to “predictive insights” leading to confident decision-making.
- Predictive cashflow, working capital management, and dynamic period-end closing checklist will revolutionize the CFO functions.
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Finance & Accounting Transformation
The ‘Gen AI Express’ is hurtling past. Now is the time to get on board.
Open Gen AI platforms are already helping users create original content with ease. Programmers are writing codes with it, students are taking cues to do their assignments, and even legal professionals are now using Gen AI to draft documents and conduct research. Now it is time for finance leaders in manufacturing to harness Gen AI, moving from reactive decisions to predictive insights and transform the financial landscape.
AI and Generative AI
While AI and generative AI are built on similar technology, Gen AI stands out by creating new content, not just processing existing data.
While traditional AI has largely focused on outcome-based decision-making, Generative AI represents a shift, designed to create new data, rather than just analyze existing datasets or make predictions (Zewe, 2023). For some time now, AI has supported financial decision-making powering processes like –MRP, financial planning based on historical trends, and risk assessment by actuaries evaluating loan repayment potential. On the other hand, Gen AI is currently being used to create content, images, videos, sounds, and even conversational chatbots that mimic human interaction.
AI has already transformed Finance and Accounting to some extent, but Gen AI has not yet made a significant mark in this area across most industry verticals. The Gen AI transformation wave is rising, and those who miss it now risk falling behind, stuck in a long and costly game of catch-up.
Gen AI Use Cases - F&A
Finance and Accounting is an ‘after the fact’ function and reactive in nature; Gen AI is about to turn this around and transform Finance and Accounting into a predictive and a generative function.
CFOs and finance leads will be able to generate the financial statements and KPIs for future periods with unparalleled accuracy and confidence. This will help them strategize effectively and adjust their approach. Once the historical financial statements, calculations, and details about other financial parameters are fed as context to the LLM, the Gen AI engine will be able to generate data for the future periods. Explainable AI (XAI) will show the assumptions and calculations used that can be adjusted in subsequent prompts to finetune the output. These adjustments will serve as context and baselines for predictions and forecasts.
Some of the key potential use cases are:
- Predictive cashflow: Ability to accurately predict cash balance in future gives the business an opportunity to efficiently manage and potentially reduce the interest expense, a significant overhead in manufacturing industry. This enables the CFOs/financial heads to strategize effectively and make informed decisions (like - discounting their receivables or prepaying their bills or deferring their capital expenditure). Gen AI engines will generate realistic cashflow statements for future periods based on the historical context (past receivables and payables trends and other parameters – structured data) and the effects and impacts of relevant financial, political, and economic information (unstructured data).
- Working capital management (WCM) dashboard: “Working capital improvement opportunities will remain at the top of CFOs list in 2023 and beyond” (The Hackett Group, 2023), more so in an investment-heavy manufacturing company. Monitoring and controlling the Cash Conversion Cycle (CCC) impacted by Days Sales Outstanding (DSO), Days Inventory Outstanding (DIO), and Days Payables Outstanding (DPO) is a challenging task. A Gen AI created predictive WCM dashboard will enable the CFOs/finance leads monitor and manage their working capital in real time. The context and continuous feedback, together with real-time political and economic factors will make this dashboard realistic and effective, unlike the traditional static reports-based output.
- Dynamic period closing checklist: Period-end closing is one of the most import tasks in accounting and often a nightmare for finance leads and their teams. It involves closing different modules, reconciling multiple accounts, executing several repetitive steps, and following up with relevant teams, with the deadline approaching fast all this while. A Gen AI based dynamic period closing checklist will eliminate chaos and backlog impacting day-to-day business that can lead to a ripple effect in the manufacturing process. It will create a list of relevant incomplete tasks during a certain closing cycle and automatically address routine and repetitive tasks and timely suggest steps and activities for human approval/intervention.
Potential Benefits
Takeover of Finance and Accounting functions and tasks by Gen AI will accrue several benefits to the CFOs/Finance Leads.
- Accuracy/Realistic: The data controls and inbuilt automated checks and balances will ensure data accuracy and help instill trust in the minds of CFOs and finance leads for their own data. Additionally, Explainable AI (XAI) will provide the behind-the-scenes calculations and assumptions further strengthening the confidence on data. Generation of forecasts based on the market conditions and economic outlook will provide a more realistic outlook.
- No more human errors: Human errors in accounting will be a thing of past after automation. For example: errors that humans do while posting a vendor invoice will no longer happen when the AI agent will read the invoice and post the invoice. This will reduce correction effort and duplication of work and save precious resources.
- Repetitive work is minimized: AI agents will take over repetitive and routine tasks from the finance team. For Example: account reconciliations, journal entry postings, invoice postings, etc.
- Efficiency: Time taken by a human to post a vendor invoice is way higher than the time taken by an AI Agent to post the same vendor invoice without “human-errors”. “AI enables organizations to deliver highly personalized customer experiences, at scale, while driving higher levels of productivity and efficiency” (Perez, 2023). Increased efficiency in the Finance and Accounting functions will lead to faster reporting, quicker decision-making, and more lead-time to respond to the outcomes.
- Cost reduction: Authentic data, accurate information, minimum errors, reduced routine work, and increased efficiency - they all result in reduced costs by way of eliminating duplication of work, eliminating communication back and forth to authenticate the information, reduced effort, and faster results.
Challenges/Limitations
Although not significant, the great advantages of Gen AI in Finance and Accounting come with a few challenges.
These challenges can be addressed with minimal effort, paving the way for a smoother transformation to the Gen AI based F&A. Some of these challenges are as follows.
- Data privacy and security: Finance and accounting data is confidential data. As such, strictest precautions must be taken while handing this data through Gen AI and exposing it to the LLMs.
- Bias: Bias in the data model and the training sets can lead to faulty decisions and inaccurate results. This can put the credibility of the Gen AI solutions on the line. For accurate predictions and forecasts, removing bias from the model is imperative.
- Basis of results: At times, the Gen AI models appear to be a “black box,” in the sense that establishing/identifying the basis behind a certain output or result becomes extremely difficult. This poses a huge challenge while convincing the users about the authenticity and accuracy of the results. However, with Explainable AI (XAI), there is an opportunity to win customer confidence.
- Efficiency means staff cutting: Unfortunately, some people relate increased efficiency and automation to reduction in the team size. On the contrary, this shift is an opportunity to invest, train, and get future ready, rather than simply letting the teams go.
- Ethical use: Considering the capabilities of Gen AI, the ethical use of this technology is the biggest challenge facing us. Proper regulations are required for its use to ensure that this technology is used for the betterment of the people and not otherwise.
Future Outlook
Gen AI is a reality, our future, and is set to bring in significant transformation in the field of Finance and Accounting.
It will revolutionize the way we look at the finance functions and the way the finance functions are handled today. The Gen AI benefits to the CFOs and the finance leads will be phenomenal and outweigh the challenges. More and more ERP products are now offering AI agents embedded in their products. SAP has introduced Joule and Joule Studio for Gen AI Agents in HR, AP, and other finance functions. Oracle is also promoting their pre-built AI agents and AI Agent Studio for creating custom agents. Similarly, ServiceNow has also launched their AI platform.
