By Kevin McBride, Senior Vice President, Corporate Controller and Chief Accounting Officer, ServiceNow For ServiceNow Chief Accounting Officer and Corporate Controller Kevin McBride, deploying generative AI in the finance organization is a cross-business game changer - and the time for finance leaders to embrace it is now.
That foresight enabled the global company to confidently orient its entire platform, product line and solution set around AI at a time when many companies were still in strategy mode—empowering their 8,000+ global customers and, just as importantly, their nearly quarter-million employees to put AI to active, results-focused everyday work.
One of the voices leading this internal charge is Kevin McBride. As ServiceNow’s Corporate Controller and Chief Accounting Officer, Kevin leads a team responsible for global accounting and financial reporting, financial services and operations including order to cash, accounts payable, global payroll and travel, and sales commissions. Decisions and actions taken within his organization reverberate across the entire business and its ability to operationalize strategy. In a function where speed, accuracy and transparency are vital to success, he is a passionate generative AI champion.
Kevin recently connected with The Maven Report Editorial Director Sheila Lothian to offer an inside look at how his teams are using generative AI to drive accelerated innovation and improved outcomes not just within their own organization but far beyond it. He also shares his thoughts on why embracing these technologies is the key to better, faster financial decision making, and how finance leaders can get started on the path to successful and impactful generative AI integration.
Sheila Lothian: Generative AI hit the mainstream in November 2022 with the advent of ChatGPT. When did you realize this technology’s potential to transform finance operations and start embracing it in your organization?
Kevin McBride: AI technologies have been around for years, and leading finance organizations have been using AI technologies to drive value for some time. ChatGPT is no exception. At ServiceNow we’ve been following the technology’s development and potential since its first release, which is why we have been a first mover to adopt generative AI in our platform.
Our vision is to be the AI platform for business transformation. This is enabling our customers to be some of the first companies to derive value from generative AI. In finance, we initially embraced generative AI in our case management workflows in 2022 and are expanding it to include manual close activities and finance analysis.
SL: What are some of the traditional pain points in financial decision making that generative AI can address?
KM: Generative AI can be applied to business analysis, operational workflows, and risk management and compliance to address traditional operational efficiency and effectiveness challenges in finance. There is so much manual work in finance, with finance professionals spending their time and energy searching for data, flagging risks, reconciling and moving data from system to system instead of bringing critical insights to business leaders for action.
But it’s not just about efficiency. Insights are a competitive advantage. Business leaders know this and expect finance to bring insights that uncover actions that decrease time to market and sales cycle times, increase market or customer penetration and decrease the friction of doing business. Business leaders and shareholders benefit from the positive outcomes driven by AI-enabled finance operations.
SL: How did your organization begin integrating generative AI into financial processes?
KM: Our primary engagement is working with our product and IT organizations on adopting the ServiceNow platform capabilities. For finance, those capabilities are initially focused on case management operational efficiencies. We receive tens of thousands of employee, customer and vendor inquiries a year that our people address through our case management products built for finance. Generative AI capabilities enable us to deflect questions more rapidly through self-service tools, develop responses and knowledge-related guidance through content generation, and suggest next steps for our case managers based upon case summarization. This leads to better experiences for our customers, vendors and employees.
We also engaged our finance organization through a series of workshops on the AI landscape and the best opportunities fit for AI technologies. We had some fun and creative sessions where our finance professionals competitively ideated use-case opportunities. The idea was to create excitement, demystify the technology, and drive business agility by enabling real-time education increasing speed and accuracy of communication between finance in the enterprise. We are working with IT on designing and implementing the winning use cases.
SL: How did you partner with your IT organization to adopt and accelerate AI earlier in the process?
KM: Being an innovative and fast-paced enterprise software provider inherently requires close collaboration across the enterprise, and our connection to IT is no different. Our close partnership with IT has allowed us to focus on impactful use cases that hit the heart of our pain points making our AI investments more meaningful. Through this partnership we leveraged a skilled technology team that has been able to take our use cases, bring them to life with human centric design principles, delivering amazing experiences for our employees which, in turn, drives greater adoption and ROI on our AI investments.
SL: What are some of the tangible benefits your teams have experienced since adopting generative AI?
KM: Faster case and inquiry resolution times for customers and internal employees while maintaining the quality and content of responses. Our accounts receivable and sales compensation specialists have saved time reviewing prior correspondence and preparing customized responses. Because our response times are so much faster with AI, we find our business partners are more empowered and educated which leads to a stronger positive sentiment about the service our business partners receive from finance.
SL: Has the implementation of AI in finance delivered wins in any other areas of the business?
KM: As a company, our generative AI strategy focuses on infusing intelligence into the flow of work, end-to-end, across the enterprise. With our native integrations, we already help people orchestrate across different systems and data sources. When you look at our own deployment of Now Assist, our IT help desk is saving 45 minutes per avoided case. In Customer Service, our people are saving 30 minutes every time the computer generates a knowledge-based article for them. Our people will save 21,000 hours with faster self-service, and our developers are completing non-complex scripts in half the time.
Within finance, we are delivering better service and insights to sales by providing early guidance into deal economics, structuring options and terms. This ability to respond rapidly to simple inquiries means that we can shorten sales cycles, guide our sales colleagues towards accretive deal considerations, and devote the time of our sales-facing finance teams toward partnering on more complex opportunities. With generative AI, we can also complete our post-mortem of deals faster and provide critical and timely insights to shape our deal pipeline and new prospects in coming quarters.
SL: Did you meet with any cultural or organizational challenges or resistance during the integration process?
KM: Again, we are an innovative and fast-paced enterprise software provider. We culturally foster and cultivate change-ready people with a growth mindset. I believe our organization sees AI technologies as an opportunity to innovate, shift even more capacity to analyzing products, markets and customers to help our business leaders provide excellent products and services to our customers at competitive prices while carefully managing and safeguarding our assets. The ideation event I previously mentioned helped to increase knowledge and awareness and break down barriers in a way that quickly moved us towards adoption.
As we roll out our AI initiatives, we’ve experienced an overwhelming demand from our finance professionals to expand our use cases. As our team has experienced what the technology is capable of, they are dreaming big about how it can transform finance.
SL: What specific steps or strategies should finance leaders prioritize to ensure successful AI integration and application?
KM: A few things come to mind… and they are not necessarily unique to AI:
Ensure your North Star for the finance strategy is well-known and well-defined. Where are you headed as an organization…and why? Have you considered the demands of the business and your employees? What is your competitive environment? These questions, and others, shape your North Star.
Know what you’re optimizing for. Is it scale, cost, speed, volume? You must know the value vectors of your strategy.
Evaluate goals against opportunities. Understand the problem you are trying to solve and require your teams to clearly articulate that problem and how the outcomes expected from each opportunity will help you achieve your North Star and measure against your value vectors.
Assess your data accessibility. This one is specific to generative AI, which relies heavily on large volumes of data to function effectively. You need to make sure your data is accessible, high-quality, real-time and contextualized. That should be a strategic and funding priority.
Prepare for learning cycles. Unlike the implementation of traditional technology, where you design test scripts, perform regression testing, etc., with generative AI, you need to approach the technology, and the continual oversight of the technology, similar to how you approach an employee. It’s active management, which also depends on accessible high-quality data to be optimally successful.
Consider the change readiness of your organization. Organizations are all about people, and you need to bring your people along the journey. There are so many opportunities to help your business win in the marketplace, to help your customers achieve their goals, and for finance professionals to drive business outcomes while building marketable skills that differentiate them in the marketplace. It’s an exciting time!
SL: We’ve talked quite a bit in The Maven Report about the “collision of ideas” around generative AI. How should finance leaders manage the deluge of input on AI implementation coming from the wider organization and make decisions about what does and does not get funded?
KM: I like that phrase, collision of ideas. It is a common problem for an innovative company evolving at pace. We hire and develop the best financial professionals that aspire to improve their work and drive meaningful business outcomes. There is never a shortage of ideas. There are, however, constraints around time and investments. To ensure that we provide our customers with the best products and services using efficient and scalable processes, we must prioritize.
It’s not just prioritizing generative AI…it is prioritizing the cross-finance initiatives to ensure that we are achieving our finance vision of delivering actionable insights that shape the future for ServiceNow. This means focusing on measurable outcomes and prioritizing those outcomes on business value, customer and employee experience.
SL: Any final recommendations you want to share with your fellow finance leaders about navigating their teams through this transformative era?
KM: What I’ve loved about working in the tech industry for over 30 years is the innovation and disruption technologies. As with all new technologies, we will need to adapt our processes, policies and people. We need to develop new skills and new methods of ingesting the technology in a way that fulfills our finance vision.
There will be other technological advances in the next 5-10 years. To be a winning finance organization that drives competitive differentiation, you must adopt technologies to attract, develop and retain the best talent, and dedicate yourself to enabling, developing and upskilling your people to be tech enabled business partners that can drive business outcomes. It is a competitive environment, and employees are hungry to leave behind the manual work and put the power of their creativity and insight into action.
