AI Lag in the Mid-Market: Stop Waiting for 'Big AI' and Start Automating Cash Management Now
It's Friday evening. Your colleagues left for drinks an hour ago. You're still refreshing bank portals and reconciling transactions in spreadsheets while SAP Business One or ByDesign waits patiently in the background. This is the weekly reality for many mid-market finance departments. While AI promises to make manual hurdles a thing of the past, the real win isn't just tech - it's getting your Friday evenings back.
Yet while AI adoption has surged - with McKinsey reporting that 88% of organisations now use AI in at least one function - the mid-market is hesitating. Many finance teams remain trapped in manual workflows due to implementation concerns and are putting AI implementation off until it ‘can be done without a major project’.
It’s called ‘The Readiness Trap’
"Our data isn't clean enough." "We need better infrastructure first." "We're waiting for SAP to release more AI features."
These justifications sound like responsible governance. They sound sensible, but there is a fine line between being methodical and being stalled. That hesitation often blocks the very solutions that provide immediate relief. Many companies running SAP Business One or ByDesign often possess much of what AI automation tools require: a robust ERP managing financial operations with structured data flows, vendor master data, and integrated general ledgers.
While you are trying to perfect your business case, your competitors may be deploying a proven cash management automation that integrates directly with your SAP suite, and surprisingly, may not take a big effort to implement.
Here's what many SAP Business One and ByDesign users miss: Your platform is already built for this.
SAP Business ByDesign runs on SAP HANA and has a suite of open APIs designed for third-party integration. Similarly, SAP Business One offers more than 250 integration points and a robust Software Development Kit (SDK), allowing for deeply personalised automation. SAP has been expanding AI and automation capabilities across both platforms. Predictive analytics, and machine learning are now increasingly layered into core workflows. The building blocks are in place. The infrastructure for an AI-assisted use case such as treasury automation isn't a future roadmap item; it exists today. The question is whether you'll use them.
From batch files to real-time banking
One technical shift is also enabling more rapid deployment of treasury automation for SAP users: the move from batch-file banking to API-driven connectivity.
Traditional banking integration often required significant middleware investment, lengthy implementations, and ongoing maintenance by specialised IT staff. This has historically priced mid-market companies out of real-time connectivity. Finance teams downloaded bank statements as files, imported them through batch processes, and accepted delays of hours or days.
API-based connectivity changes this picture significantly. Modern treasury platforms, like Embat, that integrate with SAP can provide direct, real-time connections to UK and European banks through secure APIs enabled by Open Banking regulations.
That means no middleware costs and no batch-processing delays.
The ROI reality check
Despite growing investment, you need clear expectations. Deloitte's 2025 AI ROI research found that 85% of organisations increased their AI investment in the past 12 months. Yet most reported achieving satisfactory ROI within two to four years, significantly longer than the 7 to 12-month payback most expected for technology investments.
The lesson?
Target high-frequency use cases, such as bank reconciliation, as a measurable use case first.
Why? Bank reconciliation is one of the most time-consuming cash management tasks. Integrated vendor solutions using Open Banking integration can connect directly to bank accounts, downloading statements and importing them into SAP Business One automatically. Such systems typically suggest matches based on bank reference information, then create incoming payments and allocate them against invoices automatically, potentially transforming reconciliation from a manual, hours-long process to an exception-management workflow.
A practical implementation possibility
One common myth that may be holding you back is that AI implementation requires extensive timelines. Industry sources, however, suggest that many AP automation and treasury tools may complete implementations in weeks rather than months.
A practical approach for your firm could look as follows:
- Weeks 1-2: Conduct a focused workflow audit. Quantify baseline metrics like cost per invoice, processing time, error rates.
- Weeks 3-4: Select a single high-frequency workflow with clear ROI measurement like AP automation or bank reconciliation.
- Weeks 5-8: Deploy with a specialised vendor offering mature “plug-and-play” integrations for SAP Business One or ByDesign.
- Weeks 9-12: Monitor performance against baseline metrics and review the immediate ROI. With the manual “slog” eliminated, you can now focus on scaling these efficients across the department.
From strategy to action
The key message here is: a comprehensive AI transformation plan does not necessarily need to be approved by the board and implemented company-wide. It may simply require a decision to automate one high-impact cash management workflow and a commitment to moving from concept to implementation in a quarter or two.
Don’t wait for a ‘Big AI’ revolution that may never arrive. By leveraging purpose-built automation from partners like Embat, you can transition from manual workflows to real-time cash visibility in weeks, not years. It’s the fastest way to future-proof your finance department - and it might just ensure those early Friday drinks become a permanent fixture on the calendar.
This article was written for the UKISUG community, drawing on publicly available research, official SAP documentation, and insights from across the user group. Implementation timelines represent general industry guidance and results may vary based on organisational complexity and readiness.
About the author
Theo Wasserberg, Head of UK&I, Embat
Theo Wasserberg, Head of UK&I at Embat, is an SAP ecosystem veteran with an extensive background in SAP consultancy and systems implementation. After years of solving complex ERP challenges for UK & Irish businesses, and completed an MBA at INSEAD, Theo now focuses on helping finance leaders bridge the ‘AI gap” through seamless cash management automation.