Finance automation and value creation: A new nexus

Big Four accounting and consulting firm Deloitte’s Australian arm has come under public scrutiny after reports that it produced a document for the Australian government that was full of artificial intelligence-generated errors.

The incident involving one of the biggest names in the corporate finance world should serve as a wake-up call for anyone in the profession using AI tools without proper safeguards, experts say.

“This situation underscores a critical lesson for finance professionals: AI isn't a truth-teller; it’s a tool meant to provide answers that fit your questions,” Bryan Lapidus, FP&A Practice director for the Association for Financial Professionals, which provides training and credentials for people in the finance profession, said in an email.

Deloitte Australia’s report to the Australian Department of Employment and Workplace Relations was originally published on the department's website in July, according to an Associated Press article. A revised document was published earlier this month after revelations that the original version contained errors, including a fabricated quote from a federal court judgment and references to nonexistent academic research papers, AP reported.

Deloitte Australia agreed to partially refund the 440,000 Australian dollars ($290,000) paid by the Australian government for the document, which reviewed the information technology system used by the department to automate penalties in Australia’s welfare system.

“Deloitte conducted the independent assurance review and has confirmed some footnotes and references were incorrect,” a DEWR spokesperson said in an email, adding that “the substance” of the review has been retained. Deloitte has agreed to repay the final installment under its contract, the spokesperson said.

Deloitte Australia didn’t immediately respond to a request for comment.

Chris Rudge, a Sydney University researcher, has been credited with bringing the errors to light. He discovered that Deloitte’s report was “littered with citation errors,” prompting concern that it may have been generated by AI, according to an article published by the Australian Financial Review in August.

The event is a reminder for companies that AI is “smart but not infallible,” according to Nikki MacKenzie, an assistant professor in the Georgia Institute of Technology’s Scheller College of Business.

“We’re constantly hearing about how ‘intelligent’ AI has become, and that can lull people into trusting it too much,” she said in an email. “Whether consciously or not, we start to over-rely on it.”

AI tools such as generative AI chatbots can be susceptible to “hallucinations,” where they create outputs that are “nonsensical or altogether inaccurate,” according to an explainer published by ChatGPT creator OpenAI. Hallucinations can occur when an AI model is trained on a dataset comprising biased or unrepresentative data. AI tools can also be vulnerable to adversarial attack, where a bad actor manipulates output by subtly tweaking the input data, the article said.

Nearly six out of 10 employees admit to making mistakes in their work due to AI errors, according to a KPMG study released in April. In addition, about half use AI in the workplace without knowing whether it’s allowed and more than four in 10 are “knowingly using it improperly” at work, the study found.

The Deloitte event, while alarming, is unlikely to result in a pause in AI adoption, according to experts.

“I believe firms will see this as a normal cost of doing business,” MacKenzie said. “Just like how employees make mistakes, tools can too. The goal isn’t to avoid AI’s errors — it’s to make sure we’re smart enough to catch them as the ultimate decision-maker.” 

The Deloitte incident is just the latest high-profile example of the risks posed by AI as it gets rapidly deployed across industries.

In January, Apple suspended an AI feature designed to summarize news alerts after complaints that it generated false and inaccurate information. And in 2023, a New York federal judge sanctioned two lawyers who submitted a legal brief that included fictitious case citations generated by ChatGPT.

Jack Castonguay, an associate professor of accounting at Hofstra University, said Deloitte is the first major accounting firm he’s aware of that has produced a report with fictitious details generated by AI.

“It seems like it was only a matter of time,” he said in an email. “Candidly, I’m surprised it took this long for it to happen at one of the firms.”

The event underscores the need for organizations to build AI safeguards or internal controls to mitigate risks such as hallucinations, MacKenzie said.

“The responsibility still sits with the professional using it,” she said. “Accountants have to own the work, check the output, and apply their judgment rather than copy and paste whatever the system produces.”

As technologies like AI continue to evolve, business leaders need to make a series of increasingly complicated calculations to put their companies on the most effective digital transformation paths. That means the relationship between the finance and IT teams need to be closer than ever — and that the CFO and CIO need to be having discussions structured around strategy first, budget second, Rimini Street finance chief Michael Perica said.

In speaking with the CIO, “I don't want to hear [about] cost initially in the conversation,” Perica said in an interview together with Rimini Street CIO Joe Locandro. “If this is the best technology or path, irrespective of cost, we should be pursuing it.”

Putting value before cost

The need for a tighter relationship between finance and IT has come under a spotlight in recent years, as finance chiefs take on more tech-related responsibilities and as tools such as automation and AI become more deeply integrated into businesses’ everyday processes, CFO Dive has previously reported.

The two departments can be a “powerful combination,” Locandro said, because they can leverage both financial and technology discipline across the whole organization — as the finance and IT teams are “cross functional in a company, we see things enterprise wide,” he said.

Investing in the relationship with their IT counterpart is crucial for finance leaders today, especially for businesses to be able to meet their strategic goals, Perica said. Most of his conversations with Locandro focus on “corporate strategy and how we're going to deploy our IT resources and capabilities, not only internally, but externally, for the enterprise wide goals” of the business, Perica said.

Perica has served as CFO for the Las Vegas-based provider of ERP support solutions since October 2020, according to his LinkedIn profile. His previous roles include serving as vice president of finance, CFO energy systems global for EnerSys, and a five-year span at Alpha Technologies in various roles including a three-year stint as CFO.

Locandro, meanwhile, joined Rimini Street in February to lead the business’s global IT strategy and help drive “technology innovation initiatives in support of Rimini Street’s continued growth and client success,” according to a press release at the time. His experience includes a 25-year career in numerous CIO and IT roles, including serving as CIO for building materials provider Fletcher Building, a tenure as chief digital and business transformation officer for the Australian Energy Market Operator, and VP of business technology services for the Emirates group, according to his LinkedIn profile.

Before CIOs and CFOs can have a successful conversation about strategy, they need to find common ground. For both Perica and Locandro, it’s important that the CIO and CFO are peers inside of the executive leadership team, they said, and that each leader approaches the other with an eye toward value.

For instance, in working with IT leaders as a finance executive, a point of frustration for Perica is “is when they come to put in technology for technology’s sake,” he said. Rather, the focus should be on aligning “the technology and the deployment to business objectives,” he said.

On the IT side, meanwhile, “CFOs often treat IT as a cost, not as a potential advantage,” Locandro said. When CIOs report to CFOs, traditionally, IT is viewed as a cost center and not as a necessity for the running of the business or a value add, he said. However, “when you have a CIO and a CFO as peers on the executive committee, they look at things strategically, and they look at value creation, not cost minimization,” he said.

A birds-eye tech approach  

Technology budgets can be a key area where CIOs and CFOs differ: in a March survey by Big Four firm KPMG, almost one-third of finance chiefs said technology innovation spending is excessive, while just 16% of CIOs said the same, CFO Dive sister publication CIO Dive reported. Meanwhile, 12% of CFOs said tech budgets were “currently insufficient,” while one in three CIOs said the same.

One way to bridge that gap is by utilizing the natural birds-eye view both IT and finance have to look at technology implementations holistically. In conversations between Locandro and himself on the topic, the two discuss “how we're going to make IT investments enterprise wide, not just for my group, not just for any particular function within an organization,” Perica said. “And that's where I think it's…going to be a colossal miss if folks are not taking that view.”

When it comes to artificial intelligence initiatives, for example, “folks are going too fast and they're not taking an enterprise-wide look,” Perica said. Many companies have overshot their cost estimates on the technology, according to a recent study by Mavrik, an AI cost management solutions provider. The survey found 80% of enterprises missed AI infrastructure forecasts by over 25% while businesses also identified areas of “hidden costs,” such as data platforms and network access expenses.

The missed forecasts represent a familiar hiccup when it comes to technology implementations, Locandro said, where companies will jump on a technology hype cycle, “and they do a lot of proof of concepts, and then after doing a few they realize they have to put in governance,” Locandro said. “So often, governance is an afterthought versus a prerequisite.”

Without approaching such implementations with that eye toward governance, “you end up reworking it, and then you end up spending more money,” he said. “And then you go, ‘Well, if I had known this at the start, I would have probably sized it [differently] and put a different budget in place.’”

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Large companies with thousands of employees could lose seven figures every year to corporate cards with no restrictions or reimbursement-based workflows. That’s why modern finance teams are embracing modern cards that offer granular, dynamic controls.

Cards that let admins set spend rules based on category, vendor, amount, or date give business the power to automatically preempt out-of-policy transactions. This prevents time-consuming headaches for managers and finance admins later by reducing non-compliant spend.

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Employees dread expense reports. In legacy systems, it takes about 13 minutes to submit a single report, based on Ramp estimates.¹ At scale, that adds up to more than 14,000 hours and $500,000 per year in wasted time for a large company.

Modern tools flip the model entirely. Instead of making employees manually cobble together receipts and expense details, expenses largely submit themselves. These platforms automatically match transactions to preapproved funds, collect receipts via integrations and use AI to suggest accounting codes and memos.

Ramp can reduce expense submission time by 85%, saving up to $435,000 per year in employee wages, according to our new analysis.

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Not every transaction needs scrutiny from finance or department heads. In fact, forcing managers to sign off on every $30 charge is a recipe for delays and inefficiency.

Finance leaders are now implementing AI agents that can automatically review every expense and recommend whether to approve, reject, or review each transaction. These agents can even clear low-risk expenses so only a small percentage of transactions get escalated. This saves finance valuable time and translates to a much better experience for employees who make frequent purchases.

Even without agents, Ramp helped reduce expense processing time by over 90%, saving 2,400 workdays per year, our latest data shows.

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Legacy systems have few features in place to catch fraud, and the cost of this fraud only increases as the business scales. Businesses lose 5% of their annual revenue to fraud and the cost of losses is only increasing, according to an AFCE study.

But an intelligent system can instantly flag duplicate, blurry, AI-generated, or other atypical receipts. It can also pick up other unexpected activities such as an expense incurred over the weekend. These checks reduce risk by helping enterprises stay compliant and audit-ready without adding workload.

Enterprises using automated expense tools can reduce the cost of creating and processing reports by an estimated 90%, per our analysis.

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Accountants deploying generative artificial intelligence can upgrade the level of detail of financial reports by 12%, shift 8.5% of their time from routine, back-office processing to higher value tasks, and cut 7.5 days off the time needed to complete a monthly close, researchers said.

By using generative AI, accountants can devote more time toward analytical work, quality assurance and communicating with clients, researchers at the Massachusetts Institute of Technology Sloan School of Management and Stanford University Business School said in a study.

“On average, AI-using accountants support 55% more clients per week compared to non-users, enabling them to broaden their client service scope,” the researchers said. “These accountants also log more billable hours, indicating that AI helps convert previously non-productive time into client-facing work.”

Advancements in AI this decade have improved accounting efficiency and accuracy, with machine learning sharpening fraud detection, predictions of earnings, forecasts of market trends and risk management, according to research in recent years.

At the same time, many companies use robotic process automation to streamline workaday tasks such as data entry and reconciliation, reducing errors and upgrading efficiency.

Going beyond prior findings, the MIT/Stanford study “uniquely captures a complete perspective of how generative AI fundamentally transforms financial reporting and professional accounting practices,” researchers Jung Ho Choi and Chloe Xie said.

The researchers teamed up with a provider of AI software focused on accounting and analyzed hundreds of thousands of transactions from 79 small- and medium-sized companies.

Choi and Xie also surveyed 277 accountants, exploring how they adopted AI and viewed the benefits and hazards of the technology.

When used by accountants as a collaborative tool, AI especially complemented the professional judgment of the most seasoned accountants, Choi and Xie said.

“We find that more experienced accountants tend to leverage the AI system more strategically and reap larger performance gains from it,” the researchers said.

Veteran accountants are skilled in interpreting metrics from AI measuring the reliability of its recommendations and, when the scores are low, tend to intervene more frequently than their less experienced colleagues, the researchers said.

“Less experienced accountants may rely on the AI even when its confidence is low, or under-utilize the AI’s suggestions, resulting in smaller gains,” the researchers said.

“These dynamics suggest that AI augments, rather than replaces, human judgment,” they said, adding “the role of the accountant remains vital in supervising the AI, handling novel or complex cases.”

The industry view toward AI is not completely sunny. While most accountants acknowledge the value from AI in streamlining their work, 62% voice concern about potential errors and inaccuracy, the researchers said.

Overall, though, “generative AI can substantially augment accounting work without displacing the professionals who perform it,” Choi and Xie said. Accounting firms that adopt the technology can yield “remarkable improvements in productivity, task allocation and reporting quality.”

Corporate finance departments will look very different in three years, as technologies such as artificial intelligence agents transform how CFOs and their teams operate, Eric Glyman, CEO of tech startup Ramp, said in a recent blog post.

By 2028, many U.S. corporate finance teams will include a fleet of autonomous AI agents supervised by an “AI agent manager” and performing roles in a variety of areas ranging from procurement to expense management, Glyman predicted.

“This isn’t a story about replacing people,” he said in the blog post. “It’s about redeploying them — up the value chain, into the work only humans can do.”

New York-based Ramp offers an expense management software platform designed to help businesses optimize their spending and streamline finance operations.

Last week, the company announced that it raised $500 million at a $22.5 billion valuation in a Series E-2 funding round. This came on the heels of the startup launching its first AI agents.

“We have a fortress balance sheet and an accelerating core business,” Ramp CFO Will Petrie said in a press release on the funding round. “Both will allow us to play to win as AI reshapes the future of finance.”

Ramp has raised $1.9 billion in total equity financing and began generating cash flow earlier this year, according to the release. The software company announced on June 17 that it raised $200 million in a Series E funding round.

In his blog post, Glyman said the back-to-back funding rounds come “at a unique moment in finance” in which more and more CFOs are testing AI tools.

The rise of agentic AI in particular heralds a future just a few years from now in which finance software “thinks, acts, and improves by itself,” according to the post.

“Picture a fleet for different tasks,” Glyman wrote. “Expense agents clearing 99%+ of transactions without human touch. Treasury agents optimizing cash positioning. FP&A agents running real-time forecasts.”

As AI agents take on various roles in the finance function, junior analysts will become “agent coaches” and senior leaders will make a “smaller number of higher quality decisions,” he said.

On June 10, Ramp unveiled AI agents for controllers “to automatically enforce company expense policies, eliminate unauthorized spending, and prevent fraud.” The company said the agents are the first in a series that it is releasing this year.

The startup joins a rapidly growing list of enterprise software companies that are offering AI agents designed to perform workplace tasks with little human intervention.

Gartner predicts that 33% of enterprise software applications will include agentic AI by 2028, up from less than 1% in 2024, with at least 15% of day-to-day work decisions being made autonomously through the technology.

“Agents represent a paradigm shift in how AI systems interact with users and environments,” Gartner analysts said in a February report.

Among other recommendations, Gartner advised companies to gain experience with AI agents by starting with single agents before jumping to multiagent systems. The report also called on leaders to measure their investments and identify use cases that can result in outcomes such as increased productivity or improved decision making.

“Don’t invest in agentic AI simply because it is the latest innovation to be hyped,” the report said.

Microsoft’s finance department has incorporated various artificial intelligence agents into its toolkit as the team ramps up its years-long digital transformation push, an official said.

The agents add to a mix of AI-powered tools that are helping the team streamline a range of functions, including procurement, payment collections and financial forecasting, according to Cory Hrncirik, the company’s modern finance leader.

AI is “driving so much change at the company … saving us thousands upon thousands of hours” as well as millions of dollars, he said at a finance conference last week at the University of Southern California.

The arsenal of AI agents deployed by the finance team includes off-the-shelf Microsoft tools such as an analyst agent that can perform advanced data analysis, according to Hrncirik. The team is also using custom-built agents that it developed for specialized functions, including a tool designed to simplify the process of sourcing suppliers. 

The sourcing assistant is saving the company an estimated $10 million in costs per year, while also resulting in an estimated 15,000 hours in annual time savings, according to a PowerPoint slide shown during the presentation. 

Besides generating cost savings and productivity gains, AI initiatives have also helped to bend the finance team’s “headcount curve” over the past decade, Hrncirik said.

“Whereas we always had to rely on hiring a lot of people, armed with nothing other than Excel spreadsheets and a ... desire to power through broken systems and processes, we now have been able to really streamline a lot of the work that we do,” he said. “We’re seeing the opportunity to really empower every person that works in our finance division to achieve more.”

The event, sponsored by the University of Southern California and Financial Executives International, a professional organization for finance leaders, featured Hrncirik as a keynote speaker.

Hrncirik’s career at Microsoft spans a period of nearly 17 years. As part of his current role, which he assumed in 2018, he helps guide the digital transformation of the tech giant’s finance team in addition to sharing ideas with finance executives of other leading companies, according to his LinkedIn profile. His prior titles at the company have included senior business analyst manager and finance manager.

The finance team at Microsoft began its AI journey about a decade ago, long before OpenAI’s ChatGPT tool grabbed the world’s attention, according to Hrncirik.

“It started with traditional machine learning, primarily in the forecasting domain,” he said. The use cases quickly expanded to include areas such as audit reviews, he said. Eventually, the team also began using AI for purposes such as automating invoice payments, reconciliations and approvals of all kinds.

“We have learned a lot about AI and applying AI to finance over the past decade,” he said. “But we’ve seen more progress in the past couple of years than we’ve seen in a long time ... With the evolution of ChatGPT ... AI became common language ... and it’s at our fingertips. And that accessibility has opened up new ideas.”

The team’s AI push came after the groundwork was laid by CEO Satya Nadella and CFO Amy Hood, Hrncirik said.

After becoming CEO in 2014, Nadella sparked a cultural shift in the company when he pushed the overall organization to embrace a growth mindset, Hrncirik said.

“Amy and all of our finance leaders have leaned into that concept,” he said. “It’s really important, especially for risk averse finance and accounting professionals, who don’t always love change and don’t always love changing a system or process.”

He said the cultural shift was crucial in that it challenged people to ask themselves how they could “do things better, cheaper, faster, more efficiently.”

“There are some areas [where] you want to change things more methodically than others [to avoid running] afoul of any compliance or regulatory issues, of course,” he said. “But there are so many areas where we can move really, really fast.”

Artificial intelligence agents — tools designed to complete tasks with little or no human supervision — are dominating technology conversations, stealing at least some of the spotlight from generative AI chatbots like ChatGPT.

Software executives like Salesforce CEO Marc Benioff are lining up behind the technology, rolling out big plans for 2025 and beyond, as they imagine a future in which it’s trusted to perform a variety of key workplace tasks across industries.

Salesforce, for its part, is seeking to unleash one billion agents by the end of 2025, Benioff said in an announcement last fall.

While the technology is generating a lot of buzz, some analysts say it may be a while before companies can begin to realize its enormous potential.

Agentic AI offers new opportunities for business leaders but it also poses a host of potential challenges, including the risk of an agent leaking sensitive data or acting based on a “hallucination” or error, according to analysts. For now, at least, this could hinder adoption, particularly in sensitive parts of a business such as the finance department.

“I think the finance function is going to need to take some time to get comfortable with agentic AI,” Mark McDonald, a senior director analyst at Gartner, said in an interview, adding that rapid adoption among finance teams this year is unlikely.

Years, not months  

The consulting group Forrester in a report late last year stated that AI agents, despite being a top emerging technology for 2024, were effectively not ready for prime time, asserting that it would be another two years before they have “any chance of meeting inflated automation hopes.”

In addition, some may be underestimating the complexity of running projects that involve multiple agents working together, according to Assaf Melochna, co-founder of Aquant, an AI company based in New York City.

“There’s a difference between building something for an experiment versus an enterprise-grade system that needs to be bullet proof to avoid error,” he said.

Still, despite agentic AI’s immediate challenges, analysts say it might also be risky for business leaders to completely tune out the noise around the technology.

“With agentic AI, the question is not if, but when,” Deloitte said in a 2024 year-end AI report released this week. “Although the technology is still in its early stages, it is evolving rapidly and will likely become increasingly capable over the next few years.” 

Over the past year, organizations have improved their preparedness for generative AI more broadly when it comes to areas such as tech infrastructure and strategy but have made seemingly little progress on other critical fronts, including risk, governance and talent, the report said.

Chatbots versus agents

The tech industry’s agentic AI push comes amid growing disillusionment over generative AI in the business world as many C-suite leaders grapple with the reality of cost and return-on-investment challenges, analysts say.

For organizations struggling to see the benefits of generative AI, Cole Stryker, a writer who contributes to IBM blogs, writing in an October piece said he sees agents as potentially “the key to finding tangible business value.” 

“It remains to be seen whether the vast sums of money currently being poured into a handful of huge LLMs [large language models] will be recouped in real-world use cases, but agentic AI represents a promising framework that brings LLMs into the real world, pointing the way to a more AI-powered future,” Stryker argued.

Chatbots “can interact intuitively with humans, synthesize complex information, and generate content,” according to a November article published by Deloitte’s Center for Technology Media and Telecommunications. “But they lack the degree of agency and autonomy that agentic AI promises … AI agents don’t just interact. They more effectively reason and act on behalf of the user.”

Microsoft 365 Copilot, a ChatGPT-like tool, can serve as a personal assistant to business professionals by “jumpstarting” creative projects, but an AI agent can go even further, acting as “a virtual project manager” or tackling complex assignments like reconciling financial statements to close books, Susanna Ray, a features writer who produces online content for Microsoft, wrote in a November blog post.

“An agent takes the power of generative AI a step further, because instead of just assisting you, agents can work alongside you or even on your behalf,” she said. “Agents can do a range of things, from responding to questions to more complicated or multistep assignments.”

AI agents can choose a course of action, design a plan, gather relevant data, and employ multiple software tools to complete each step, according to an SAP explainer.

“By learning from evolving information, AI agents improve over time — analyzing feedback, self-correcting errors, and solving emerging problems,” according to the article. “Multiple AI agents can also work together, even coordinating with humans to achieve different tasks.”

SAP supports the policy that a “human should always be in the loop” when agentic AI is used, Walter Sun, global head of AI at SAP, told CFO Dive. He said SAP’s AI agents provide recommendations to users, who decide whether or not to take action. 

While agentic AI models are designed to make decisions and carry out complex sequences of actions, they are not foolproof and can still make mistakes, just as humans do, according to Mark Purdy, managing director of Purdy & Associates, an advisory and thought leadership firm.

“The agentic AI prize could be great, with the promise of greater productivity, innovation, and insights for the human workforce,” he wrote in a December article published by the Harvard Business Review. “But so, too, are the risks: the potential for bias, mistakes, and inappropriate use.”

Organizations were advised in Deloitte’s year-end AI report to prepare for agentic AI by developing a “strategic roadmap” and crafting risk mitigation plans, among other steps.

“[W]hile there are still many challenges to overcome — and technical complexities to sort out — now is the time to start preparing,” the report said.

AI’s ‘staying power’

More broadly, AI remains a top priority for C-suite leaders, despite some of the potential challenges and risks around adoption, KPMG found in a survey released this month.

The majority of corporate executives responding to the poll said they expect AI to “fundamentally” change the nature of their business within a year or two.

And nearly seven in 10 respondents said they plan to invest between $50 million to $250 million in generative AI over the next 12 months, up from 45% in first quarter 2024 poll results.

“The results show the staying power of the technology,” Todd Lohr, head of ecosystems at KPMG’s U.S. advisory division, said in an interview, adding that C-suite leaders have continued down the path of AI investment, by and large.

The coming year brings an opportunity to scale and advance AI capabilities across the enterprise, and a majority of organizations are looking to AI agents to help do so, KPMG said in a release announcing the study. Over half (51%) of organizations are exploring the use of AI agents and another 37% are piloting them, it found.  

But, once again, it will be up to businesses and their leaders to carefully weigh the risks and the benefits of various AI options.

CFOs and CIOs in particular are responsible for working together to ensure the company is aligned with the right projects, Melochna said.

“On the one hand, you have this pressure to invest to avoid falling behind competitors,” he said. “On the other hand, you need to be cautious to ensure you’re investing in the right thing.”

Leading U.S. enterprise software providers including Microsoft and SAP have kicked off a fresh wave of artificial intelligence-driven innovation in recent months, rolling out a flurry of new “AI agents” designed to perform tasks in corporate finance and other business functions.  

The industry’s recent moves come as many C-suite leaders face growing pressure to make the type of AI investments that can deliver optimal value for their organization after experiments in the last two years, according to analysts. It also comes, they say, as some of the initial hype around generative AI — spurred in large part by the introduction of ChatGPT in November 2022 — has begun to fade. 

“There was this phase where people were enamored” with the technology, Mark McDonald, a senior director analyst at Gartner, said in an interview. “They kind of took that first step into the water to try it out and got varying levels of results, most of them kind of ho-hum.”

McDonald said he has been talking lately with clients who are “done with the experimenting and imagining what we can do phase” of AI adoption. “It’s now about turning these AI ambitions into concrete plans,” he said.

The year ahead brings an opportunity to scale and advance AI capabilities across the enterprise, and a majority of organizations are looking to AI agents — tools that can work independently to perform tasks and adapt in real time — to help do so, KPMG said in a Jan. 9 release announcing survey findings. 

Over half (51%) of organizations are exploring the use of AI agents and another 37% are piloting them, according to the research.

Agentic AI technology is poised to revolutionize industries, handling complex tasks with human-like decision-making, but it also poses risks such as hallucinations, where a tool asserts errors as if they were true, according to Shomit Ghose, a Silicon Valley venture capitalist and lecturer at the University of California, Berkeley.

Mitigating risks from agentic AI will require transparent design, strong safety measures and governance to maximize benefits while minimizing harm, Ghose said in an article published last month by the UC Berkeley’s Sutardja Center for Entrepreneurship and Technology. 

“Ultimately, perhaps no agentic AI will be fully autonomous — humans may always need to be involved... especially when material actions are required,” he added.

The following is a list of some of the biggest players in the tech world that are developing or offering AI agents to streamline finance and other business functions:

SAP

During its annual TechEd conference in October, SAP announced the launch of new innovations, including AI agents, to complement its generative AI copilot known as “Joule.”

The rollout included agents designed to “streamline key financial processes by automating bill payments, invoice processing, and ledger updates while quickly addressing inconsistencies or errors,” according to a press release.

“We’ll certainly have many, many more [AI rollouts] in the next year,” Walter Sun, global head of AI at SAP, said in an interview.

As part of its approach to AI risk mitigation, the company supports the policy that a “human should always be in the loop,” according to Sun. “Joule and SAP AI agents provide recommendations to the user, which the user then verifies and decides how to act on,” he said.

The company said it was not ready to disclose whether the agents have been fully rolled out to the public or how pricing is being handled. “We’ll be announcing news at our Business Unleashed event on Feb. 13, which will provide more detail on these," a spokesperson said.

ServiceNow

ServiceNow announced in September that it was planning to integrate agentic AI into its platform with the potential for “massive scale across use cases.”

Since the announcement, the company has delivered its first two agentic AI use cases, one for customer service management and another for IT service management.

The software provider is now focused on scaling AI agents to more use cases across functions, including finance, procurement and human resources, Kirsten Loegering, ServiceNow’s vice president of product management, finance and supply chain workflows, said in an email.

A host of potential finance-related agentic AI use cases are being evaluated for the coming year, according to Loegering. This includes tools for assessing potential risks such as market volatility, credit defaults, or fraud as well as automating the entire process of invoice management.

On pricing, Loegering said: “We are announcing updates to the pricing and packaging for our AI Agents very soon, but early customers have been metered through our Assists — the consumption piece of our GenAI SKUs. The final model will scale with the number of AI Agent interactions.” 

As part of its approach to AI risk mitigation, the company supports the principle that users should always be in control. “ServiceNow AI Agents evolve from the more familiar prompt-based activity to deep contextual comprehension, keeping people in the loop for oversight and governance,” Loegering said.

Oracle

During its annual CloudWorld conference in September, Oracle announced that it was releasing more than 50 role-based AI agents within its Fusion Cloud applications suite. The agents are designed to help “achieve new levels of productivity across finance, supply chain, HR, sales, marketing, and service,” according to a press release.

Among other tools, the company rolled out a “ledger agent designed to help organizations monitor and analyze account balances, exceptions, and anomalies as well as detect if revenue for a specific line-of-business is off forecast before the quarter end. It also announced an “advanced prediction agent” capable of delivering revenue forecasts by leveraging internal and external data factors.

Many of the agents announced in September are already available to customers, including use cases in customer experience, supply chain, and HR, Hari Sankar, group vice president of product management at Oracle, said in an email, adding that finance use cases in Oracle Cloud ERP and Oracle Cloud EPM are being rolled out this year.

“In 2025 we are laser-focused on broadening and deepening the capabilities of the agents throughout the Oracle Fusion Applications Suite, as well as introducing new agents to help finance leaders enhance processes such as account reconciliation and supplier payments,” Sankar said.

He said Oracle AI agents “work within Oracle Fusion Applications and use retrieval-augmented generation (RAG) to help reduce hallucinations and deliver more accurate responses and stronger performing solutions.”

Workday

During its annual Workday Rising conference in September, Workday announced the release of new AI agents as part of a broader “Illuminate” framework aimed at transforming corporate finance and HR functions.

The effort is intended to “assist and augment humans, not to replace them,” Workday CEO Carl Eschenbach said during a keynote speech for the conference, which was held in Las Vegas, Nevada.

The AI agents that were unveiled “are the first of many to come from Workday as the company seeks to radically simplify business processes for end users and elevate humans at work,” according to a release at the time.

The rollout included a recruiter agent designed to automate tasks such as creating job descriptions, sourcing candidates, and scheduling interviews; an expenses agent capable of matching receipts with credit card transactions and creating the expense line automatically; and a “succession agent” aimed at helping managers identify and develop future leaders within their organizations.

The release said the recruiter agent was being made immediately available in the company’s HiredScore platform and “will become even more integrated with Workday in spring 2025.” The expenses and succession agents are expected to become available in early 2025.

Andy Kershaw, group general manager for the office of the CFO at Workday, told CFO Dive the company currently doesn’t charge customers an additional cost for its AI features, unless “we fully transform a business process.”

“That’s where there is likely going to be an additional cost,” Kershaw said in an email.

The company supports “responsible development of AI technologies” and regulation as part of its risk mitigation approach, he said.

Microsoft

In late October, Microsoft announced that it was introducing 10 new autonomous agents, including two designed for finance professionals, in its Microsoft Dynamics 365 enterprise resource planning platform.

A new account reconciliation agent for Microsoft Dynamics 365 Finance automates “the matching and clearing of transactions between subledgers and the general ledger, helping them speed up the financial close process,” according to a blog post penned by Bryan Goode, corporate vice president at Microsoft. The company also introduced a new financial reconciliation agent designed to help teams prepare and cleanse data sets.

The software giant said it was not ready to disclose whether the agents have been fully rolled out to the public or how pricing is being handled. “We look forward to sharing more details as these agents reach public preview in the coming weeks,” Georg Glantschnig, Microsoft vice president of Dynamics 365 AI ERP, said in an email.

Salesforce

Salesforce in September unveiled “Agentforce,” a suite of AI agents designed to handle tasks in service, sales, marketing and commerce, with the goal of “driving unprecedented efficiency and customer satisfaction,” according to a press release at the time.

“Our vision is bold: to empower one billion agents with Agentforce by the end of 2025,” Salesforce CEO Marc Benioff said in the release. “This is what AI is meant to be.”

Agentforce sits across all Salesforce products and applications, so the rollout potentially impacts various teams in an organization, including finance, sales and marketing, the company said in an emailed statement.

“In finance, for example, a custom-built banking agent can handle customer service inquiries quickly and automate complex tasks like facilitating transaction disputes,” the statement said. “The agent can pull up recent transactions from an account, work with a customer to spot unauthorized charges, reach out to merchants about disputed charges, and even issue the customer a provisional credit — all before a human agent needs to step in.”