Digital transformation, one smart step at a time

Salesforce is expecting “Agentforce,” a new high-priority artificial intelligence product, to supply a “modest contribution” to the enterprise software company’s revenue this year, departing CFO Amy Weaver said Wednesday.

The new product is still in the early phase of getting adopted among customers, Weaver said during her final earnings call as the software provider’s finance chief.

“We expect the momentum to build throughout the year, driving a more meaningful contribution in fiscal '27,” she said.

The news comes as Salesforce and other major tech companies continue to spend heavily on AI amid growing questions about the strength of its return-on-investment potential.

On Wednesday, Salesforce posted weaker-than-expected total revenues of $10 billion for its fiscal 2025 fourth quarter ending Jan. 31, up 8% over the year-earlier period.

For its full-year fiscal 2026, the company reported projected revenues of $40.5 billion to $40.9 billion, up 7% to 8% compared with the prior year, a forecast that fell short of analysts’ expectations.

Salesforce’s stock fell about 4% on Thursday, closing at $295 per share.

In September, the company’s venture capital division, Salesforce Ventures, announced a new $500 million AI fund, marking a total commitment of $1 billion in the space over a period of 18 months. 

That announcement came just days after Salesforce unveiled Agentforce, a suite of AI “agents” designed to perform workplace tasks. At the time, CEO Marc Benioff said the company was seeking to deploy one billion agents by the end of 2025.

Since October, the company has closed more than 5,000 Agentforce deals, including 3,000 that are now paid, according to its latest earnings report.

“Our investments in this space have been deliberate and focused, and we are now starting to yield strong returns,” Weaver told investors Wednesday.

Morningstar analysts said in a Thursday client’s note that Agentforce “represents a good long-term opportunity to transition from a mostly human agent labor force to a mostly virtual agent pool over time.”

“While profitability remains a source of strength, we see a path for continued margin expansion even as the firm invests in artificial intelligence innovation,” they said.

Today’s financial leaders are still confronting economic pressures, weighing inflation, labor challenges and other headwinds against their long-term business plans. Despite these pressures, however, many CFOs are optimistic they will be able to boost their profit margins this year — with many looking to investments in emerging technologies like AI to do so, a recent study by spend management software provider Coupa Software found.   

Investing in new technologies or incremental software improvements is a “fundamental way” businesses can improve their internal processes — helping to boost the efficiency of their employees in ways that sustainably increase profit margins, Coupa CFO Michael Agresta said. By investing in new technologies to automate certain areas like sales or accounting activities, businesses can meet the key balance they need to between growth and profitability.

“You can't just say, ‘hey, run faster,’ and they run faster,” Agresta said in an interview of how to boost efficiency among employees. “You have to actually change things for them.”

Winning the efficiency game

An increasing focus on profitability represents a perspective shift especially for the technology industry, which has pivoted away from the “growth at all costs” model that was so popular over the past decade or so. Part of the reason for that shift lies in pricing pressures — with interest rates higher than two years ago, money is no longer free, Agresta said.

However, profitable growth is also generally, “the right way to scale a business over time,” he said. As businesses grow, they “eventually, once they get to a certain scale, should be at profitable growth,” he said.

Agresta took the top financial seat for the Foster City, California-based spend management software provider in November, according to a company announcement. His previous roles include serving as CFO for e-learning company Pluralsight and software provider Skupos, as well as a three-year span at Eventbrite in roles such as director of sales operations and strategic finance manager, sales FP&A, according to his LinkedIn profile.

Many finance chiefs today are eying technology as a way to help them meet their profitability targets, with 58% of finance leaders pointing to “strategic investments” in technology as a significant way to bolster their margins this year, the global study by Coupa found. That comes as 74% of U.S. leaders said they believed they would see their margins expand, according to the study shared with CFO Dive.

Investing in the right technology, in the right place, can be a strong way for business leaders to meet their profitability goals. While reducing costs is also a critical element, simply chopping expenses is “not a very sustainable way to get more and more profit over time,” Agresta said. Rather, leaders need to be able to build a “healthy, growing business,” he said — which requires investment, rather than just paring down costs.

That’s critical because to grow top line faster than expenses, companies “need to make every single person more efficient every single year,” he said. “Otherwise, every dollar out of the top line, I have to add an equivalent amount of expense, and I'm not going to become more profitable.”

The software provider is looking to automation to improve some its own internal processes, Agresta said. The company aims redo some of its systems in order to streamline those processes, he said.

Risk versus reward in the AI age

Bringing automation or other technologies to improve team efficiency is not a new strategy for businesses.  

“I think everyone's always looking to improve processes and take the lowest value work that someone's doing, automate it and move them to the highest value, because that constantly drives efficiency, and software generally just has done that over time,” Agresta said.

However, in an age where more and more business is being conducted in the digital realm — and as technology rapidly evolves — it’s important for leaders to thoughtfully consider where and which technologies they are implementing.

Without a technology team or guidelines, many businesses end up with redundant systems or “shelfware” that simply adds to their costs, without providing that much-needed lift in productivity, Agresta said.

One of the problems with software “is that once you put it in, it's really hard to take out,” he said, noting retention rates for software are typically high, “so you have to be pretty careful on what you let come in.”

It’s important for leaders to bring that same attitude to emerging technologies like AI; while the technology offers considerable promise, it’s still in its early days, with businesses lacking the data on its long-term impact or return on investment. Those are critical considerations for leaders as they balance AI’s risk versus reward, Agresta said.

“In areas where you have to be very accurate every single time, you probably [need to] take a more conservative approach on the amount of AI you're going to use there until it's very proven in areas where it isn't as big of a risk,” he said.

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Generative artificial intelligence may fail to spark expected big gains in productivity, prompting setbacks in the share prices of companies that have invested heavily in the emerging technology, Federal Reserve Vice Chair Michael Barr warned Tuesday.

“It is possible that the expected value creation from GenAI was overhyped, anticipating transformative breakthroughs rather than incremental productivity gains,” Barr said in a speech. “This could trigger market corrections for the firms that have heavily invested in this technology if reality doesn’t measure up to expectations.”

Generative AI will likely bring “widespread productivity gains” and evolve along one of two pathways, Barr said. Adoption may incrementally augment what humans do today, or it may spur “transformational change where we extend human capabilities with far-reaching consequences.”

Nearly eight out of 10 CFOs (77%) plan to boost spending on generative AI and other technologies this year even in the face of persistent economic and geopolitical disruptions, Gartner found in a survey.

Roughly half of those finance leaders (47%) will increase technology budgets by at least 10%, while 30% plan to expand spending between 4% and 9%, Gartner said.

“The continued focus on technology aligns with developments in traditional and generative AI, which promise to drive new offerings, enhance decision-making and boost productivity,” Randeep Rathindran, research vice president with Gartner’s finance practice, said in a statement.

In finance, generative AI may prove to be a two-edged sword, Barr said, increasing “both the vulnerabilities and sources of resilience that already exist in the system.

“Attractive trades become more crowded, but risk managers gain new insights,” he said. “Malicious actors gain new tools, but cyber defenders become better armed.”

CFOs and other actors involved in both the private and public sectors need to stay ahead of the technology’s potential hazards, he said in a speech to the Council on Foreign Relations in New York.

“So long as financial regulators, enterprise risk managers and others charged with managing downside risks prioritize efforts to keep pace with the evolving financial ecosystem, there’s nothing to suggest a wholesale transformation of the balance of risks,” Barr said. “Of course, keeping pace will pose challenges.”

In finance, generative AI may bring incremental gains as, for example, community banks use chatbots to provide customized financial advice based on local knowledge, Barr said.

Financial institutions of all sizes would continue to make strides by using generative AI in compliance, fraud detection, risk management and document analysis, he said.

In the second scenario, generative AI would spark profound change, making finance "radically different,” Barr said.

On this pathway, “individuals with access to hyper-personalized financial planning and businesses with innovative products and services seamlessly connect with one another through near-frictionless or novel forms of financial intermediation,” he said.

Traders and risk managers would use generative AI analytic tools that tap dynamic, real-time data from both public and private sources, Barr said.

In order to harness the gains from generative AI while limiting its risks, the Fed and financial institutions should invest in the technology, incorporate it in their work flows and train staff on how to use it responsibly, Barr said.

“The financial regulatory community should approach the changing landscape with agility and flexibility,” he said. “And beyond the financial sector, collaboration between governments, private industry and research institutions will be critical to ensure that GenAI systems are not weaponized in catastrophic ways.”

Artificial intelligence agents — tools designed to take on workplace tasks — could fundamentally reshape the corporate finance function in coming years, rendering some jobs obsolete while creating new ones, according to Georg Glantschnig, vice president of Dynamics 365 AI ERP at Microsoft.

The technology is still in the early stages of development, and some analysts say it may be too soon for rapid adoption when it comes to functions such as corporate finance.

Eventually, however, AI agents could act as “skilled virtual coworkers, working with humans in a seamless and natural manner,” according to a McKinsey report published last year.

Microsoft envisions every business process in an organization being impacted by AI agents, Glantschnig told CFO Dive. Such agents can help finance teams automate labor intensive processes like the financial close, he said.

The following is a Q&A, conducted via email, between Glantschnig and CFO Dive’s Alexei Alexis. The exchange has been edited for clarity and brevity. 

CFO Dive: How do you define AI agents or agentic AI, and how much of a potential game-changer is this emerging space when it comes to business automation, particularly in the corporate finance function?

Georg Glantschnig: An agent uses AI to execute tasks and take action on your behalf. Agents work alongside or on behalf of a person, team, or organization and range from simple, prompt-and-response agents that carry out a simple query or a single task like invoice approval to more advanced, fully autonomous agents that orchestrate end to end processes such as order to cash.

Ensuring accuracy and compliance of financial operations and reporting is a fundamental responsibility of every finance department. With financial data dispersed across multiple data sources, financial transactions flowing in and recorded from internal and external sources, maintaining financial data accuracy is a daunting task, often done manually and prone to human errors.

By leveraging agents to automate key financial processes, finance professionals can benefit from time saved searching across systems without sacrificing, or even increasing, accuracy and compliance. 

Furthermore, the agent’s ability to dynamically adapt and constantly learn makes an agent-driven automation far more sustainable than a traditional rule-based one that requires more ongoing maintenance.

CFO Dive: Are fully autonomous AI agents a reality or just an aspiration at this stage and is the market ready for this?

Georg Glantschnig: Our customers’ trust and confidence in AI is top of mind for us. Therefore, we started with assistive capabilities in 2024 across our full ERP portfolio. Today, 50% of our users are using Copilots in Dynamics 365 apps. In the same responsible way we’re introducing agents, gradually increasing their autonomy at a pace suitable for each individual customer. Different customers and teams differ in their AI journey and how quickly they adopt new technologies, but we already seeing many examples for customers moving quickly.  

Customers are already building their own agents with Microsoft Copilot Studio. For example, Pets at Home, the UK’s biggest pet care company, created an agent for its profit protection team to more efficiently compile cases for skilled human review, which could have the potential to drive a seven-figure annual savings. Organizations like McKinsey & Company, Thompson Reuters, Clifford Chance, and more around the world are also seeing incredible impact from building their own custom agents in Copilot Studio.

Copilot for Finance also provides both an assistive and automated agent experience to complete data reconciliation, enabling the user to choose the level of automation required. With assistive, users are involved in each step of the process and can “graduate” to the fully agentic experience once confident.

CFO Dive: From your company’s perspective, how important is the human element when it comes to corporate finance adoption and use of AI agents, and how might that change as the technology evolves and becomes more mature?

Georg Glantschnig: Agents automate business processes and can vary in complexity, scope, and autonomy — from generating insights on request, to running discrete tasks, to dynamically planning, managing, and orchestrating complete processes independently. Agents won’t interact with end users directly but with those users’ copilots. In AI-first companies, we anticipate that every employee will have their own copilot, and they will be supported by tens of thousands of agents. Our objective is to have a copilot for every worker and an agent for every business process.

We anticipate that with time, humans will take a more supervisory role, overseeing the work done by the agents, and the agent’s learning processes. 

Agents created in Copilot Studio are limited by the actions and tools that are explicitly defined by the author. Each interaction an author has with an agent is logged, so authors are able to review the record to see which actions are called by the agent and why.   

Agents created for Dynamics 365 include “human in the loop” approvals. For example, the Account Reconciliation Agent in Dynamics 365 Finance automatically reviews and reconciles transactions between subledgers and the general ledger. When it finds discrepancies, it escalates them to a human for further review.

Humans remain in control by selecting the functions the agent handles and can update these settings at any time. The agent suggests solutions for discrepancies based on previous human resolutions. As it works alongside humans, the agent learns and proactively proposes updates to rules and actions enabling it to gradually become more autonomous. At any time, humans can review the agent's operations, ensuring full visibility and establishing trust.

CFO Dive: Is there a risk that certain roles within the corporate finance function could be displaced by AI agents in the future? If so, how much of this could we see? 

Georg Glantschnig: AI agents are helping revolutionize many financial workflows, by automating and streamlining labor intensive processes like financial close. By doing so, financial professionals are able to spend more time focusing on providing strategic insights and driving business growth, while ensuring accuracy and organizational compliance. We are seeing AI agents help drive similar shifts across sales, service, and other business functions and are optimistic about the future of AI-first business processes.

We see the AI revolution as one that is fundamentally reshaping work and how work gets done. While it’s too soon to determine the exact impact on the finance workforce, it’s likely that some jobs will disappear, and some new ones will emerge. As mentioned above, administrative jobs might turn into supervisory roles, and we’re seeing a new role of “agent business administrators” emerging — with a responsibility for setting up and continuously improving the agents.

When it comes to successfully implementing AI inside of their finance functions, today’s CFOs are weighing “two different aspects” against each other, said Vivek Saxena, SVP and service line lead for finance & accounting at SaaS provider Genpact.

Firstly, finance leaders are looking closely at costs, Saxena said in an interview — including both the costs of the technology itself and the expenses related to running a modern finance function. They are then weighing those costs against value, he said; both the value finance provides today, versus how the technology could impact the value that function could provide in the future.

For example, when it comes to something like improving forecasting, “that is not a cost game — that's a value from finance game,” Saxena said. “Once you get the right insights, how will you be able to monetize that or quantify that?”

Risk versus reward

The challenge of balancing short-term costs against long-term impacts is not a new one for finance chiefs. However, dong so with AI can be tricky for CFOs who need to keep pace with changing regulations, constantly evolving technologies, and macroeconomic factors such as pricing pressures to determine how implementing AI could impact their companies.

With the advent of new AI solutions, such as “agentic AI” tools, the focus for many finance chiefs is on risk management, Saxena said.

Presently, those looking to implement AI “will spend more time [figuring] out whether the adoption of these AI modules or agents will impact their existing control environment effectiveness,” he said. CFOs then need to determine what steps they should take to mitigate that risk.

Genpact offers several enterprise solutions supported by AI, and recently partnered with Databricks to build an “AI gigafactory” that will help financial service firms better move their AI products into production, according to reports. An 18-year veteran of the New York-based company, Saxena has served in his current role since September 2022, according to his LinkedIn profile. Before joining Genpact, he served as manager, CPM product management for Oracle.

Agentic AI has steadily filtered into the spotlight over the past year, with large-scale players such as Microsoft and Salesforce offering such agents to help financial leaders with key processes and workplace tasks, CFO Dive previously reported.

While AI agents could potentially help to improve profitability or reduce expenses by cutting down on the time it takes finance employees to finalize routine tasks — such as the financial close process — both industry leaders and regulators have expressed concerns about the technology’s use. The technology’s propensity to “hallucinate” or to provide erroneous information has raised flags, with questions also arising over its safety and security.

CFOs therefore need to pay careful attention to where they are looking to apply such tools and the reporting or regulatory standards when it comes to those processes, Saxena said. For example, “the dependency on traceability and auditability of AI models is much higher when it is…in the journey of preparation of financial statements versus when it comes to preparation of management reporting,” Saxena said.

The data mandate

The availability of AI agents may also lead to a shift in how CFOs think about their staffing needs, Saxena said. As such agents become more available, finance leaders may start to reconsider the ratio of employees versus automated tools, and where to apply each of them, he said.

“The challenge is, in many companies, the CEOs have given a mandate: adopt AI, deploy AI, and CFOs don't want to be behind,” Saxena said. AI and large language models have also steadily become more available for use in key financial processes such as accounts payable, or financial planning & analysis, Saxena said. At the same time, “training them [has] become comparatively cheaper,” he said.

That could lead to a potential future where companies are spending more on AI agents, shrinking the budget for hiring. As AI agents become more commonplace, certain finance jobs could ultimately disappear, Microsoft’s Georg Glantschnig, vice president of Dynamics 365 AI ERP told CFO Dive — though the shift will also make room for new jobs, he said.

There are still some roadblocks to implementing AI agents and related tools at scale, however. Costs are still high for certain key aspects of the technology, such as aggregating data.

Improving both the quality and flow of one’s data is a “multi-year journey” companies will need to undergo as the technology continues to evolve, Saxena said. To take full advantage of emerging technologies, CFOs need to have a clear understanding of both the reliability of their data as well as be able to trace where it’s coming from, he said.

As technology CFOs grapple with numerous challenges, including rising costs and the impact of artificial intelligence, holding on to top talent is moving to the top of their priority list. Generative AI is still in the spotlight, putting a premium on talent with the necessary skills to utilize such tools effectively. At the same time, inflation, a glut of technology layoffs, and other factors have both narrowed compensation growth and boosted attrition in the tech sector.

Creating “cultural stickiness” is emerging as a key way for finance chiefs to retain the talent they need, said Andrea Schulz, partner, audit services for Grant Thornton LLP and national managing principal of technology at Grant Thornton Advisors. In a recent survey of technology CFOs by Grant Thornton, 58% said “maintaining or improving organizational culture” was a top priority when it comes to human capital during the next 12 months.

“You don't want that attrition with your top talent, and so we have a refresh of, ‘we can't solve this churn issue with just writing checks to people and increasing salaries,’” Schulz said in an interview. “It's really going to need to come from, ‘what are we differentiating ourselves through?’”

The question of culture

The talent challenge remains top-of-mind for finance chiefs, with 50% stating finding and retaining talent was a key priority, according to Grant Thornton’s survey. However, today’s technology CFOs are dealing with a complicated talent environment. Even as demand for generative AI skill sets rose, salaries for IT workers grew by 1.2% last year, with nearly half of employed professionals in the tech sector stating they actively searched for new roles in 2024, Industry Dive sister publication CIO Dive reported, citing data from tech career site Dice.

With salaries stagnating as firms attempting to balance leaner budgets moving into 2025, the industry has moved away from a “growth at all costs” mandate to one focusing more on “efficient,” rather than hyper, growth, Schulz said. That shift has changed how many CFOs are thinking both about hiring, and about culture’s role in retaining talent.

“I think in the past, when CFOs were trying to figure out company culture, it was, ‘I'm going to write a check to create this fun company culture,’” Schulz said. Nowadays, that’s evolved into a question of investment — where finance chiefs are asking, “how am I actually engaging with my teams to develop them out and make sure that they're getting a fulfilling experience, while achieving whatever the strategic priorities are for the company?” she said.  

When it comes to technology talent especially, an essential part of creating that necessary “cultural stickiness” for CFOs is channeling one’s resources in the right place. That includes potentially crafting training programs to upskill employees on emerging tools like AI, or examining the needs of back-office teams, such as finance, which often run lean, Schulz said — “many of these companies grew extremely fast and neglected their back-office operations and so we have a lot of interest in finance transformation, right now, tech modernization,” Schulz said.

“I think what that ultimately means for CFOs trying to deliver that culture is an understanding of where maybe there should be more of that strategic investment in the organization to help with the load lifts that people experience,” she said.

The AI exception

Another trend impacting tech CFOs’ talent challenges is the continued development of generative AI tools — an area that is simultaneously contributing to technology layoffs, and rising demand for skilled tech workers. When it comes to tech workers’ compensation, AI has proven the exception to the rule; those with AI skills on their resume saw an 18% increase in their salaries compared with those without, CIO Dive reported.

A company can strengthen its culture by creating programs that help employees hone their skills in AI and other areas, Schulz said.

Such efforts are a way of saying, “‘We're getting in front of this wave, we're training you up,’” Schulz said. “’You're going to be more efficient at your job, and we're giving you the skill set to advance.’”

Prioritizing talent retention should also be top-of-mind as the technology continues to see widespread changes, including layoffs. In the early weeks of 2025, larger firms such as Microsoft and Meta have announced layoffs, with Meta planning to cut 5% of its staff as it increases its investments in AI, according a CNBC report.

Forty-six percent of tech CFOs stated economic conditions could lead to layoffs in the next six months, Grant Thornton’s survey found.

However, Schulz expects something of a normalization when it comes to headcount in 2025, with layoffs shifting to more natural attrition — for instance, companies utilizing automation in more areas may choose not to replace a departing employee, she said.

As technology CFOs aim to identity the best return on investment for tools such as generative AI and automation, that will also start to influence, if not necessarily layoffs, “some role replacement, where people are becoming more efficient,” Schulz said. “And as natural attrition occurs, there might not be that desire to go put a requisition in the market for further headcount.”

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.”