When you’re ready to start your autonomous finance transformation journey, you’ll likely be presented with two less-than-ideal options.
First is an approach that’s been championed by Forrester in their analysis of AI use cases in AR and AP: Carefully review the sub processes within your O2C and P2P cycles where the relevant AI technologies are most obviously useful and have the clearest vendor roadmap. Then start by adopting them as low-hanging fruit that allow you to build an integrated workflow over time, step by step, and solution by solution.
It’s a sensible and moderate path, especially for organizations with complex operational needs that span multiple different territories, processes, systems of record, and data integration approaches. But it does have its disadvantages. A piecemeal approach to adoption isn’t likely to make your tech stack any less complex.
Standalone “best of breed” solutions can outperform generalist platforms in their areas of strength, but they often lose out overall. Especially when we factor in the complexities of integrating and managing data flows between different systems.
After all, different vendors have different strengths. A leader in RPA might not have quite what you’re looking for when it comes to prescriptive analytics. Companies building tools on generative AI models can’t necessarily provide strong predictive analytics or machine learning approaches well suited to your data sources and workflows.
The second option is what we might call the “clean break” approach: invest in an integrated system that incorporates all the AI functionalities you need out of the box.
In theory, this is the “ideal” approach. But while integrated systems would certainly make handling data flows across your finance operations easier and might set your organization up in a stronger position for the long haul, they also have distinct disadvantages. They generally carry a higher initial investment, for which leadership teams might not have the greatest of appetites in a period of ongoing economic uncertainty.
It may also be the case that your organization simply isn’t prepared to make this kind of investment. You may see a clear business case for AI in one area, but not in others—even if you’re likely to need it later as your organization grows and its needs evolve.
In these circumstances, a full bells and whistles solution represents a misallocation of precious capital that could be better tactically invested elsewhere. To say nothing of a potential source of disruption to core workflows that comes back to haunt you in the form of runaway operational expenses.
Something CFOs and their board colleagues should be very wary of given current economic realities. What’s more, for most large organizations, a clean break simply isn’t practical, and few if any vendors currently in-market are equipped to facilitate it.
A project of this size is a multi-year effort. It will no doubt require extensive third-party consulting support. And by the time it’s ready to go live, technology will already have advanced so much as to make it obsolete. CFOs need to access the benefits of AI, working capital intelligence, and autonomous finance now, to solve problems that exist now.
Step-by-step adoption of an integrated solution
At Serrala, we believe there’s a better way to implement AI into your core finance processes. One that gives you the best of both worlds in terms of the staged adoption and full-freight adoption pathways outlined above.
This approach demands that we all view finance operations and AI not as a series of stations in an assembly line that take us from raw components to increasingly finished products. But as a carefully balanced symphony of different technologies, processes, and people working together to create a greater whole.
If we look at it like this, we can create a useful analogy. In an orchestra, different instrumentalists first hone their skills and practice their parts in a piece alone. Then they come together with others in their section. It’s only after they’ve all worked individually and in small groups that they start playing together as an ensemble.
But every stage of the process is conducted with that final team effort in mind.
This is how we believe finance leaders—and tech vendors in the space—must approach the question of AI so it can deliver the kind of tangible, integrated value that we already know it’s capable of delivering.
What does this mean for finance leaders? It means that finance automation vendors must take a radically different approach to the way they architect and build their solutions.
CFOs should carefully select tech partners based on their AI readiness. AI must be a core part of the workflows they want to create for customers like you.
But they won’t be able to present all this as a singular, monolithic solution into which different teams plug different inputs and data sources—in the manner of a traditional finance system of record or ERP platform.
Instead, they’ll have to create something that organizations like yours can invest in step by step. Making smaller investments in specific parts of a much larger whole which can scale not only with volume but also with functionality as needs and demands change over time according to evolving business priorities.
This represents a much more helpful approach to transformation for finance leaders like you. Rather than having to tackle the problem as a mountain to summit all in one go, or face the potential difficulties of a piecemeal approach in the future, transformation can become something you pursue at a pace that makes sense for you.
The first step (after cleaning your data to make it legible and readable by AI-enabled systems) is planning your own investment roadmap.
Forrester’s guidelines referenced above are a great place to start, and offer a great step by step play.
Begin by prioritizing your adoption of AI technologies according to the use cases which are most mature, and which you can most easily implement.
This’ll help you to both demonstrate value and unlock resources for future rounds of investment and development.
What’s more, it’ll also allow you to plan for a change approach that provides ample time to educate and support your teams to fully understand the benefits and make the best possible use of technologies while also implementing working approaches to successfully manage increasing exposure to AI risk.
This gentler approach will also allow you to escape the trap highlighted in MIT’s assessment of attempted AI adoption in enterprise: top-down imposition of AI by leadership that favors flashier and more visible functions as opposed to improvements to higher-ROI fundamentals, and which ultimately stalls when the time comes to scale up.
How can Serrala help your organization integrate finance automation with your existing ERP investment to leverage the power of AI and autonomous finance?
At Serrala, we’ve been helping CFOs and their teams automate finance operations for over 40 years. It’s our job to help you integrate new technologies within your organization in a way that makes sense both for your challenges and their capabilities.
We’ve developed our newly released Serrala Finance Platform with AI-readiness and autonomous finance principles in mind.
A single working capital intelligence hub that provides the foundation to bring AR, AP, payments, and treasury workflows together in a flexible system that adapts to individual organizations’ digital transformation roadmaps while enabling AI integration in every single process.
Most importantly, the Platform is designed to make the kind of data clarity and quality necessary to leverage AI for autonomous processes simpler for organizations to achieve. We leave storage to your ERP—after all, that’s what it’s designed for—and allow every part of the finance department to access it to automate workflows, accelerate decisions, and deliver measurable ROI.
This allows us to provide the integrated architecture to deploy all AI use cases in a way that ensures total and seamless operational efficiency while still providing complete choice and flexibility as to which parts of the offering your organization uses (and pays for) at every stage of your transformation journey.
This means our solutions empower your organization to start with the workflows you need today, then expand as your needs grow and your transformation plans mature.
If you’re ready to learn more, check out our full report on the Road to Autonomous Finance here, or get in touch with a Serrala expert today to book a demo.
