AI in Finance and Accounting: A Strategic Roadmap

Finance and accounting (F&A) are critical to the operational efficiency and strategic decision-making of any business. The advent of artificial intelligence (AI) presents a transformative opportunity for these functions. This article analyzes manual, analytical, and strategic activities within these functions and determines the most optimal AI adoption roadmap.

1. Nature of Activities in F&A Functions

The following table estimates the volume of manual, analytical, and strategic activities in these functions as high, medium, or low:

FunctionsManualAnalyticalStrategic
Procure to PayHighMediumLow
Order to CashHighMediumMedium
Expense ManagementHighMediumLow
Tax and ComplianceMediumHighHigh
TreasuryMediumHighHigh
Financial Planning & AnalysisLowHighHigh
Mergers & AcquisitionsLowHighHigh

The next-generation AI technologies are mature and can be applied well in Finance and Accounting with a significant financial impact. We recommend prioritizing the Procure-to-Pay, Order-to-Cash, and Expense Management functions for AI adoption.

2. The AI Revolution Opens a Path to New Automation

AI techniques for interpreting unstructured data have advanced significantly in recent years. These techniques now permit what was previously considered human-level intelligence tasks.

Transformer-based frameworks allow for unstructured content understanding, language generation as well as predictive tasks. Large Language Models (LLMs) accelerate the ability of AI systems in language understanding, information retrieval, summarization, text generation, and conversational AI. Data-driven econometrics models for forecasting and trend analysis enable numeric and financial data analysis.

In finance automation, this is how these AI techniques can radically transform each of these tasks:

The structured and orderly nature of finance processes, underpinned by a robust ERP knowledge base, provides a solid foundation to leverage sophisticated machine learning and AI methodologies. Now is an opportune moment to invest in the adoption of AI-native strategies for a substantial positive business impact.

3. The AI Applications in Finance & Accounting

3.1 Procure to Pay 

The P2P function involves numerous repetitive and manual activities where AI can significantly increase efficiency and reduce errors.

AI CapabilitiesReadiness
Uses machine learning and LLMs to achieve straight-through processing for 80% of invoices. This includes automated invoice extraction, understanding, validation, matching, GL coding, and postingShort-term
Uses forecasting systems to automate accrualsShort-term
Uses predictive and prescriptive models for optimal vendor payment timingsShort-term
Uses advanced ML techniques to detect fraudulent and duplicate invoicesShort-term
Uses classification techniques to classify expenses for capitalizationShort-term
Uses AI models and tax dictionaries to verify the sales and other types of applicable taxesShort-term
Builds company and F&A-specific conversational AI models to provide chatGPT-like analyticsMedium-term
Optimizes vendor selection using predictive analyticsMedium-term
3.2 Order to Cash

The O2C function is also highly manual and prone to AI automation.

AI CapabilitiesReadiness
Uses machine learning and text processing techniques to extract and validate purchase order information from customers’ PO documents and contracts and auto-uploads information into the ERP system, resulting in 95% plus automationShort-term
Uses advanced AI techniques to generate customer invoices based on purchase orders, customer master, inventory, and shipment information to generate 100% First Time Right (FTR) invoice.Short-term
Uses recommender systems to create a daily/weekly priority list of customers for collections.Short-term
Uses dynamic models to enhance customer credit scoringShort-term
Uses advanced data science techniques for cash management including discovery of discrepancies, over and under-paymentsShort-term
Uses generative AI to automatically communicate with customers on invoices and payments, including follow-upsShort-term
Uses generative AI for conversational analytics on O2C dataMedium-term
3.3 Expense Management

Employee expense management continues to be tedious for employees and the finance teams. This process can make use of AI to achieve a very high degree of automation.

AI CapabilitiesReadiness
Uses image and text processing techniques to automatically extract information from receipts and bills, and validate and auto-create expense reports for employees.Short-term
Uses machine learning techniques to verify expense reports against policies and proofs.Short-term
Uses advanced ML techniques to detect fraudulent and duplicate expenses.Short-term
Uses classification techniques to identify the correct GL code for each expenseShort-term
Uses generative AI to communicate and answer employee queriesMedium-term
3.4 Tax and Compliance

AI has a high potential to optimize and streamline the tax and compliance function.

AI CapabilitiesReadiness
Automates collection and validation of data required to file tax returns, ensuring higher accuracy and reduced human effortMedium-term
Applies the correct withholding rates based on payer and recipient jurisdiction, reducing errorsMedium-term
Helps organize documentation related to taxation for audit purposesLong-term
Tracks applicable sales and use taxes across jurisdictions, ensuring accurate application to transactionsLong-term
Uses generative AI to map financial statements to the latest reporting standards. Facilitates SOX complianceLong-term
3.5 Treasury 

AI can provide substantial value by automating routine activities and improving decision-making in treasury management. 

AI CapabilitiesReadiness
Machine learning models analyze historical cash flow patterns to predict future cash needs.Medium- term
Monitors cash balances across accounts and recommends the most efficient pooling techniques.Medium- term
Compares fee structures across banks, helping to negotiate better terms.Long-term
It uses advanced predictive models to assess market risks and helps optimize long-term portfolio allocation. It also recommends low-risk, high-return, short-term investment opportunities.Long-term
Predicts currency fluctuations to help develop effective hedging strategies. Identifies forex arbitrage opportunities.Long-term
Builds models to identify market and operational risks using various internal and external debts.Long-term
3.6 Financial Planning & Analysis

FP&A involves many analytical and strategic activities. AI can help improve decision-making for these activities. 

Automates the data extraction from structured and unstructured sources like documents and ERPsLong-term
Analyzes the historical data to build predictive budgets and rolling forecastsLong-term
Simulates scenarios and recommends outcomesLong-term
Helps in variance analysis between planned and actual budgetsLong-term
Analyzes capital allocations and predicts ROI using historical dataLong-term
Predicts future cashflows based on historical trendsLong-term
3.7 Mergers and Acquisitions

AI can play a significant role in M&A, improving efficiency and strategic decision-making.

AI CapabilitiesReadiness
Analyzes financial reports and news articles to assess potential targets.Long-term
Builds sophisticated financial models using machine learning to provide a more accurate valuation of the target companies.Long-term
Analyzes contracts and other financial statements for risks and liabilities.Long-term
Identifies and predicts potential risks.Long-term
Provides data-backed insights into potential negotiation points.Long-term

4. Financial Impact of AI on Finance & Accounting

Now that we have analyzed the specific AI-based automation of the above finance functions, we can estimate the financial impact it can create. 

5. AI Adoption Roadmap in Finance & Accounting

Having evaluated the financial impact on all F&A functions, we can recommend the AI adoption roadmap.

6. Conclusion

The next-generation AI technologies are mature and can be applied well in Finance and Accounting with a significant financial impact. We recommend prioritizing the Procure-to-Pay, Order-to-Cash, and Expense Management functions for AI adoption.

Evolution of P2P Process

Find out interesting insights with Anthony Dias, VP Finance Delcath

Moderated by Emily ,Digital Transformation Consultant at Hyperbots

Don’t want to watch a video? Read the interview transcript below.

Emily: All right. Hi everyone. This is Emily, and I am a digital transformation consultant at Hyperbots. For today’s discussion on the evolution of the Procure-to-Pay process, I’m very glad to have Tony on the call with me. Anthony is the VP of Finance at Delcath. Anthony, would you mind telling us a little more about yourself before we get started?

Anthony Dias: Sure. I’ve over 30 years of experience. I started my career in public accounting many years ago and then moved into the private sector. I’ve worked in small to medium-sized companies, most of my career in companies that are probably in the startup phase that needed more experience to kick into the next level through public stages or acquisition phases of the company or growth phases. I’ve had an opportunity to work for a very large organization that got sold for five billion dollars as well. So, I have a good understanding of good processes, good business practices in both small and medium-sized companies. The industries I’ve been in are mostly manufacturing, high-tech manufacturing, and for the last 10 or so years, the bio-pharma space where we have manufactured both devices and drugs. Most of my experience has been at the senior level of finance, both as CFO and VP of Finance, in both public and private companies, including private equity and VC-backed companies. So that’s a high-level background.

Emily: That’s amazing and really glad to have you here on this forum today. Along with the many organizations that you have worked in, you have also been associated with all the processes of finances as well. Would you like to share what kind of Procure-to-Pay initiatives you’ve been a part of in the various organizations?

Anthony Dias: Yeah, I would say when I first started, the Procure-to-Pay part of the organizations I’ve worked at was really manual. As I mentioned, most of the companies I worked with were startups looking for the next phase. As a startup, your biggest priority is making sure you’re paying your vendors and employees. But as you grow, you need to look at other facets of growth, and bringing on additional accounts payable folks may not be the most ideal use of your resources and cash. So, looking at systems and more efficient processes around procure-to-pay becomes crucial for supporting the growth of the business. This includes having proper controls in place and better processes from the purchasing side, ensuring proper approvals, processing invoices, paying the right vendors, and controlling payments.

Emily: Got it. Tony, for the sake of the audience, would you like to break up the overall Procure-to-Pay process into sub-processes?

Anthony Dias: Yeah, I would say the front end of the process is primarily the procurement process, where you may have a requisition process for purchasing a service or product. This involves ensuring the person is authorized and getting the best price by putting a bid out, working with legitimate vendors, and having the proper approval to spend the money. Then there’s the purchasing process, where a purchasing department might vet the vendor, negotiate the best price, and handle contracts. Once the decision is made, they issue a purchase order committing the organization to the purchase. The next phase is in the finance realm, ensuring receipt of goods or services, verifying the pricing and quantities, and making timely payments based on contractual terms.

Emily: And how do you see the evolution of these processes over the last decade or so?

Anthony Dias: There’s been a lot of evolution in the last 10 years. My career started 30 years ago, and for the first 20 years, a lot of it was very manual. In small finance groups, the focus was on paying vendors and employees. As companies grow, they tend to invest in other areas like sales and marketing, often overlooking the accounts payable and Procure-to-Pay processes. The accounts payable group grows but without additional resources, leading to inefficiencies. OCR technology has been helpful, where invoices are scanned and processed electronically, reducing errors and lost mail. Electronic invoicing and payments through ACHs or wire transfers have also become common, making the process more efficient and reducing the risk of errors and delays.

Emily: So, apart from OCR or digital adoption, what other tools and technologies are used in different aspects of the Procure-to-Pay process?

Anthony Dias: In the requisition process, technologies have been adopted by larger ERP systems, making everything more electronic and web-based, which is crucial as businesses become more global and remote. Mid-sized and smaller ERP systems might not invest as much in these areas. Technologies include electronic requisitions, purchase orders, and vendor price comparisons. In the accounts payable process, the adoption of electronic payments, capturing invoices through OCR, and other technologies have minimized manual errors and improved efficiency.

Emily: After the adoption of such tools and technologies, are there still challenges that exist on the procurement side?

Anthony Dias: The biggest challenge is time. Getting a requisition approved by a manager who gets many emails can be slow. The purchasing department also needs time to find the best price. For someone needing a product or service quickly, this process can be frustrating. Speeding up approvals and negotiations can help. There’s also the issue of adherence to processes and the perception that controls and procedures slow things down. Improving the speed and efficiency of these processes is crucial.

Emily: Why do you see many organizations still having significant elements of purchases without a rigorous PO-driven process?

Anthony Dias: It often comes down to the hesitation of non-finance folks to follow the process, preferring the ease of direct purchases as they do in their personal lives. The mindset in organizations is still not there for some. They might feel that going through the approval process is unnecessary when they can quickly purchase items online. But organizational purchases need to comply with standard practices, regulations, and ensure consistency. The process also ensures the company is not at risk and is getting the best terms.

Emily: Apart from the timing, what other challenges have you seen in the procurement process in general?

Anthony Dias: The three-way match process matching purchase orders, receiving goods, and invoices can be time-consuming. Discrepancies in quantities, prices, or quality of goods received versus what was ordered can cause delays and require back-and-forth communication with vendors. Resolving these issues takes time and can affect payment timeliness, leading to potential leverage issues with vendors.

Emily: What are the best practices in streamlining the procurement process to have better financial control?

Anthony Dias: Best practices include a robust requisition process with manager approvals aligned with budgets, a purchasing group vetting vendors and ensuring the best prices, timely receipt and verification of goods, and accurate and timely payment of invoices. Good communication between procurement and finance is crucial, ensuring everyone is aligned on budgets and vendor payments.

Emily: What kind of collaboration would you suggest between the finance and procurement teams to achieve the company’s common business objectives?

Anthony Dias: Procurement and finance should have a strong partnership. Purchasing should understand budgets and approval limits, consult finance when needed, and ensure proper vendor documentation flows to the accounts payable team. Collaboration in budgeting and forecasting is also important, ensuring purchases align with the company’s financial plans.

Emily: Can you share the inefficiencies that still exist in the procurement process despite best-in-class ERP implementations?

Anthony Dias: Some inefficiencies still exist due to resistance to change, manual data entry, and writing checks. People are often slow to adopt new technologies due to risk aversion and a lack of understanding of how these technologies can minimize risk and improve efficiency. Educating staff on new technologies, demonstrating their benefits, and investing in these areas can help address these inefficiencies.

Emily: Apart from the mindset, what else do you think is needed to improve these processes?

Anthony Dias: Investing in these areas is crucial. As companies grow, they need to re-evaluate and invest in their accounts payable and procurement processes to avoid inefficiencies and risks. Continuous education and training for staff on new technologies and best practices, attending conferences, webinars, and networking with other professionals in the field can also help improve these processes and keep them up-to-date with industry standards.

Emily: One last question: what do you think could be done to address these inefficiencies better?

Anthony Dias: Education is key. Accounts payable clerks, CFOs, and controllers need to stay informed about new technologies and industry best practices. Networking with peers, attending conferences and webinars, and bringing in experienced people can help. Investing in technology and processes will help organizations grow efficiently and keep employees motivated and engaged by reducing manual work and improving job satisfaction.

Evolution of P2P Process Part 2

Find out interesting insights with Anthony Dias, VP Finance Delcatch

Moderated by Emily Digital Transformation Consultant at Hyperbots

Don’t want to watch a video? Read the interview transcript below.

Emily: All right, welcome back Tony to this segment. Thank you so much for walking us through the Procure2Pay overview and the challenges involved. In this segment, we’ll be talking about the future roadmap of the Procure2Pay process, some examples, and the advantages of AI in the Procure2Pay space. Before we get into the questions, would you mind introducing yourself and telling us a bit more about you?

Anthony Dias: Yes, sure. I’m Anthony Dias. I’m Vice President and CFO for a biotech company in the Boston area. I’ve been a senior finance person in both public and private companies, ranging from smaller organizations to mid-sized ones, and I’ve had the opportunity to work for a large organization that sold for over five and a half billion dollars. Most of the industries I’ve been involved in are the medical space and manufacturing.

Emily: Got it. Thank you so much for that introduction, Tony. In the last segment, you mentioned that embedding AI in different tasks in the Procure2Pay processes could remove some inefficiencies. Could you highlight some examples of this?

Anthony Dias: Yes. Using AI could speed up the matching process, especially the three-way match process in AP. AI can read invoices faster and more accurately than a human AP clerk. It can process invoices quickly, matching the receipt, purchase order, pricing, quantities, and unit price. This process, which can be time-consuming and manual for AP personnel, can be handled swiftly by AI. AI can help identify mismatches quickly, allowing AP personnel to focus on resolving errors rather than processing entire invoices.

Emily: Correct. So apart from reducing redundant tasks, you also touched on how the roles of procurement or accounts officers would evolve with AI adoption. Could you elaborate on that?

Anthony Dias: Yes, it empowers finance teams by eliminating repetitive, clerical work. AP clerks, who usually handle a high volume of invoices, often find their tasks monotonous and unengaging. With AI handling the manual processes, clerks can shift to more analytical roles, examining data trends, looking for savings opportunities, and optimizing payment schedules. Similarly, AI can assist in purchasing by finding the best prices and making procurement decisions more efficient.

Emily: Correct. Can you delve deeper into the learnings and unlearnings necessary to fully leverage AI in Procure2Pay?

Anthony Dias: There’s often hesitation about integrating AI into AP processes due to concerns about security and risk. However, with strong security programs, segregation of duties, and robust controls, AI can significantly lighten the workload. AI can handle heavy lifting, such as checking for duplicate invoices and pricing errors, while humans can focus on approval processes. Learning to trust and adapt to AI’s capabilities while ensuring security measures are in place is key.

Emily: Got it. So, what are the risks you see in adopting AI in Procure2Pay?

Anthony Dias: People risk is significant. AP cler

ks might fear job loss or significant changes to their roles due to AI. This can be mitigated by involving them early in the AI adoption process, providing proper training, and explaining how AI will help them perform better and focus on more analytical tasks rather than clerical ones. Ensuring they feel part of the change and understanding AI’s benefits can ease the transition.

Emily: Got it. And any specific recommendations for the order of tasks for AI adoption in the Procure2Pay space?

Anthony Dias: Start with tasks that offer immediate efficiency gains and minimal risk, such as invoice processing using OCR technology and automating manual data entry. Gradually incorporate more complex AI functions, like payment term optimization and vendor management. Ensuring a phased approach allows for better adjustment and minimizes disruptions.

Emily: Understood. What would be your advice on building versus buying AI and automation solutions?

Anthony Dias: It depends on the company’s resources and focus. Major companies like Oracle, SAP, and NetSuite are developing AI solutions, but their primary focus isn’t AP or purchasing. Smaller companies might offer more specialized and adaptable AI solutions. The decision to build or buy should consider the specific needs of the organization, risk tolerance, and the capability to integrate these solutions with existing ERP systems.

Emily: What AI solutions do you see emerging in the Procure2Pay space currently?

Anthony Dias: AI can optimize cash flows by analyzing payment terms, cash availability, and ensuring timely payments. It can perform trend analysis, identify opportunities for savings, and suggest payment schedules. AI can handle tasks like coding invoices, matching them with purchase orders, and managing vendor relationships more efficiently. These capabilities allow finance teams to focus on strategic decision-making rather than routine tasks.

Emily: Great. So, what adoption rate do you foresee for AI-led Procure2Pay solutions over the next couple of years?

Anthony Dias: Adoption will increase as more companies realize the efficiency and cost savings AI offers. Manual tasks like data entry will become obsolete, replaced by OCR and AI-driven automation. Purchasing processes will become more streamlined, with AI quickly analyzing quotes and selecting the best vendors. Overall, AI will transform Procure2Pay processes, reducing the need for manual intervention and allowing finance teams to focus on strategic tasks.

Emily: Got it. Thank you so much, Tony, for sharing your insights on the evolution of Procure2Pay, the current landscape, challenges, future roadmap, and the infusion of AI. It was great having you here.

Anthony Dias: Thank you.

Best Practices for Optimizing Purchase Requisitions, Invoices, and Payment Approvals

Creating a comprehensive and efficient purchase requisition, invoice, and payment approval process is crucial for organizations to maintain operational efficiency and financial control. Given the diversity in practices across companies, it’s beneficial to consolidate best practices that can serve as a guideline for establishing or refining these processes. This blog aims to outline these best practices, incorporating examples and illustrations to provide clear insights.

Understanding approval authority matrices

An approval authority matrix is a framework used by organizations to define who can approve expenditures and at what thresholds. The complexity of these matrices can vary based on the organization’s size, structure, and operational needs. Here are some foundational best practices:

1. Layered approval levels based on purchase value

A common practice is to implement multiple levels of approval based on the value of the purchase. For example, purchases under $1,000 might only require approval from a direct manager, while those exceeding $10,000 require additional sign-off from a department head or even the CFO. This tiered approach ensures that higher-value transactions receive more scrutiny.

PURCHASE VALUEPURCHASE VALUEAPPROVAL LEVEL 2APPROVAL LEVEL 3
Up to $1,000Direct ManagerN/AN/A
$1,001 – $5,000Direct ManagerDepartment HeadN/A
$5,001 – $10,000Direct ManagerDepartment HeadCFO
Over $10,000Department HeadCFOCFO

2. Department and expense type consideration

Some organizations adjust approval levels based on the department making the purchase or the type of expense. For instance, IT hardware purchases might follow a different approval path than marketing expenses due to the specialized knowledge required to evaluate such expenses.

DEPARTMENTEXPENSE TYPEPURCHASE VALUEAPPROVAL LEVEL 1APPROVAL LEVEL 2
ITHardwareAnyIT ManagerCFO
MarketingAdvertisingUp to $10,000Marketing ManagerCFO
OperationsSuppliesUp to $5,000Operations ManagerDepartment Head

3. Vendor purchase aggregation

Tracking gross purchases from the same vendor across multiple requests helps in negotiating better terms and identifying opportunities for bulk discounts. This also ensures better internal financial control. This approach requires a more sophisticated tracking system but can lead to significant cost savings.

VENDOR PURCHASE TOTAL ACROSS MULTIPLE PURCHASESAPPROVAL REQUIREMENT
Up to $5,000Direct Manager
$5,001 – $20,000Department Head
Over $20,000CFO

This can be additional authority metrics in addition to 1 or 2 outlined as above.

4. PO-based vs. Non-PO-based invoices

The process for approving invoices can differ for purchase order (PO) based and non-PO-based transactions. PO-based approvals typically follow a more streamlined process since the purchase has already been pre-approved at the requisition stage. Non-PO transactions may require additional verification steps to ensure they are legitimate and necessary.

INVOICE TYPEPURCHASE VALUEAPPROVAL LEVEL 1APPROVAL LEVEL 2APPROVAL LEVEL 3
PO-BasedAnyPre-approved*N/AN/A
Non-PO-BasedUp to $1,000Direct ManagerN/AN/A
Non-PO-Based$1,001 – $5,000Direct ManagerDepartment HeadN/A
Non-PO-Based$5,001 – $10,000Direct ManagerDepartment HeadCFO
Non-PO-Based>= $10,000Not permittedNot permittedNot permitted

* PO-Based invoices are considered pre-approved at the requisition stage but may require final verification through system based matching logic..

5. Unified vs. Separate invoice and payment approvals

While a few companies combine invoice approval and payment authorization into a single step, most others separate these processes to add a layer of control. Separating these steps can help in identifying discrepancies before payments are made.

For example for company A the invoice approval could be as per the following table:

INVOICE TYPEPURCHASE VALUEAPPROVAL LEVEL 1APPROVAL LEVEL 2APPROVAL LEVEL 3
PO-BasedAnyPre-approved*N/AN/A
Non-PO-BasedUp to $1,000Direct ManagerN/AN/A
Non-PO-Based$1,001 – $5,000Direct ManagerDepartment HeadN/A
Non-PO-Based$5,001 – $10,000Direct ManagerDepartment HeadCFO
Non-PO-Based>= $10,000Not permittedNot permittedNot permitted

And for the same company the payment approval would be as follows:

PURCHASE VALUEAPPROVAL LEVEL 1APPROVAL LEVEL 2APPROVAL LEVEL 3
Up to $1,000Direct ManagerDepartment HeadFinance Controller
$1,001 – 5,000Department HeadFinance ControllerN/A
$5,001 – 10,000Department HeadFinance ControllerCFO
>=$10,001Department HeadCFOCEO

6. Hierarchical vs. decoupled approval structures

Organizations must decide whether the approval hierarchy should mirror the organizational structure or if it should be decoupled to allow for more flexible and efficient processing. Decoupling can be advantageous in organizations where cross-departmental purchases are common.

APPROVAL STRUCTUREPURCHASE VALUEAPPROVAL ROLE 1APPROVAL ROLE 2
HierarchicalUp to $5,000Direct ManagerDepartment Head
HierarchicalOver $5,000Department HeadCFO
DecoupledUp to $5,000Project ManagerFinance Controller
DecoupledOver $5,000Procurement SpecialistCFO

Critical success factors for approval authority matrices

Implementing the best authority metrics does not automatically make a company’s approval process optimal and efficient. The following factors play a critical role in that. 

Conclusion

To conclude, with the right mix of policy, process, and technology, organizations can ensure that their procure-to-pay approval cycles are both efficient and effective, paving the way for fiscal responsibility and long-term success.

How AI Connects and Elevates P2P Business Processes

Artificial Intelligence (AI) is rapidly transforming the landscape of business operations offering innovative solutions to enhance decision-making and optimize performance. The Procure-to-Pay (P2P) process, encompassing a wide range of tasks from purchase requisition to payments, stands as a prime candidate for such AI-driven transformation. By acting as a unifying glue, AI can not only tie the loose ends within the P2P process but also elevate its maturity to the next level. This blog explores how AI can revolutionize the P2P process, with detailed examples illustrating its potential impact.

AI Integration in procure-to-pay processes

The integration of AI into P2P processes can significantly enhance efficiency, reduce errors, and facilitate strategic decision-making. Below are key areas where AI can make a substantial difference:

1. Automating routine tasks

Purchase Requisition & PO Approvals: AI can automate the generation and approval of purchase requisitions and purchase orders (POs) by analyzing historical data and learning approval workflows. For instance, AI systems can automatically generate purchase requisitions for inventory replenishment by predicting stock levels and processing PO approvals based on predefined criteria. AI can also convert contract documents into purchase orders.

Invoice Processing: AI-powered text processing can automate the extraction of invoice data, reducing manual data entry errors. Further, AI algorithms can match invoices with POs and Goods Received Notes (GRN), ensuring accuracy in payments.

2. Enhancing vendor management

Vendor Contracts: AI can manage and analyze vendor contracts by extracting key terms and conditions, monitoring compliance, and identifying renegotiation opportunities based on performance analytics and market trends.

Vendor Selection: By analyzing historical performance data, market trends, and risk factors, AI models can assist in selecting the most suitable vendors for procurement needs.

3. Optimizing inventory management

AI can predict optimal stock levels by analyzing trends, seasonal variations, and sales forecasts. This helps in maintaining the right balance between overstocking and stockouts, ensuring smooth operations.

4. Streamlining compliance and tax verification

Sales Tax Verification: AI systems can automatically verify the accuracy of sales tax calculations on invoices, ensuring compliance with tax regulations.

Regulatory Compliance: AI can monitor compliance with industry regulations and corporate policies by analyzing transaction data and flagging potential issues.

5. Financial process enhancement

GL Posting and Month-end Activities: AI can automate General Ledger (GL) postings and facilitate month-end activities such as accruals, by analyzing and categorizing financial transactions accurately.

Payment Decisions: AI algorithms can optimize payment timings and methods by analyzing cash flow forecasts, vendor payment terms, and discount opportunities. This not only ensures timely payments but also maximizes cost savings through early payment discounts.

Conclusion

AI’s potential to transform the P2P process is immense, offering opportunities to automate routine tasks, enhance decision-making, and improve efficiency across the board. By acting as a unifying force, AI can address the challenges posed by disparate systems and applications, bringing coherence and efficiency to the P2P process. As technology evolves, the role of AI in P2P processes is set to become even more pivotal, marking a new era of procurement and financial management.

The AI Advantage in Finance Function: Beyond Traditional Automation

The shift from traditional workflow automation to AI-enhanced processes in finance represents a leap toward more intelligent, adaptive, and strategic financial management. AI’s ability to learn and improve over time, predict future trends, and provide deep insights into financial data offers CFOs powerful tools to drive efficiency, compliance, and strategic decision-making. While traditional automation streamlines tasks based on rules and workflow, AI introduces a level of sophistication and analytical depth that transforms finance functions into proactive, strategic pillars of the organization.

The table below highlights the evolution from traditional automation, to AI-led automation.

FINANCE FUNCTIONTRADITIONAL WORKFLOW AUTOMATIONAI-LED AUTOMATION
Procure to Pay (P2P)Automates workflow, payment processing, and basic vendor management tasks based on predefined rules. Each invoice needs to be reviewed by a human.Uses machine learning to improve invoice processing accuracy over time, predicts optimal payment timings for cash flow management, and detects fraudulent invoices through pattern analysis. Enables straight-through processing for 80% of invoices.
Order to Cash (O2C)Focuses on automating order entry, credit checks based on static criteria, and straightforward dunning processes for overdue accounts.Enhances credit scoring with dynamic models, automates personalized dunning campaigns using customer data to improve collections, and predicts future payment behaviors for credit risk management.
Financial Planning & Analysis (FP&A)Streamlines data aggregation for budgeting and forecasting, relying on historical data and linear projections.Utilizes predictive analytics for forward-looking insights, identifies trends and anomalies, and simulates various business conditions for strategic planning, offering adaptable FP&A.
Expense ManagementSimplifies expense report submission and approval processes, enforcing policy compliance through rule-based checks. Each expense needs to be reviewed by a human.Employs NLP and machine learning for detailed expense report audits, identifies policy violations and fraudulent patterns, and personalizes reporting guidance to reduce errors. Enables straight-through processing for 80% of expenses, and receipts.
TreasuryAutomates cash management and forecasting based on historical cash flow patterns and executes predefined investment strategies.Leverages advanced analytics for accurate cash flow forecasting, recommends investment strategies by analyzing market trends and the company’s financial health, and adapts to real-time market conditions.
Mergers & Acquisitions (M&A)Supports data room management and basic due diligence automation, relying on manual analysis for valuation and integration planning.Automates in-depth financial, operational, and market data analysis to uncover insights, predicts integration success, identifies synergies and red flags, and optimizes deal structuring based on strategic objectives.
Tax and ComplianceFacilitates tax calculation, filing, and basic compliance monitoring through rule-based systems.Automates complex tax planning strategies, monitors compliance with changing regulations using predictive analytics, identifies potential compliance risks, and adapts to new tax laws and regulations for tax filing and reporting

This detailed look at AI’s impact across various finance processes underscores the need for CFOs to embrace AI technologies, not just for the operational efficiencies they bring but for their potential to fundamentally redefine how finance supports and drives business strategy.