Linking AI implementation to P&L and Balance Sheet Items
The role of AI in value creation…
AI isn’t just a technology story. It’s a financial one.
Since 2009, I’ve been at the frontline of technology implementation—first in banking, then across Fortune 500 companies—collecting hard data, case studies, and lessons from the field. From the “boring” ERP rollouts to the latest AI pilots, one truth has stayed constant: every automation and efficiency gain eventually shows up on the P&L or balance sheet.
Revenue, margins, cash flow—they’re all touched by the way a company uses (or fails to use) technology.
From my own research and interviews, I believe lower middle-market companies are uniquely positioned to feel the ripple effect of successful AI implementations. They’re lean, they move faster, and the financial impact of each efficiency gain compounds more visibly than in sprawling corporates.
And a quick disclosure: when I say “AI,” I don’t mean a magic pill. I mean the combination of human expertise, process redesign, LLM fine-tuning, and smart integration into legacy systems. It’s how we embed it and how people use it that unlocks real value.
1. Sales & Customer Experience: Faster Cycles, Lower SG&A
Revenue growth → Proposal automation and AI-driven customer support shorten sales cycles, which means deals close faster and revenue is recognized earlier. This accelerates cash inflows and boosts top-line growth.
SG&A savings → Automating proposal prep and routine support reduces manual workload, lowering labor costs and expanding operating margins.
Working capital gains → Faster deal closures improve Days Sales Outstanding (DSO), enhancing cash conversion.
Recurring revenue stability → Faster, higher-quality service improves customer satisfaction, reducing churn and protecting recurring revenue streams.
📊 Impact example: According to HBS publication*, companies adopting AI in sales and CX report 4–6% EBITDA uplift within the first year, driven by shorter sales cycles and lower operating costs. (*links and resources at the end)
2. Inventory & Logistics: Direct Hits to COGS and Working Capital
COGS → AI demand forecasting and replenishment reduce excess stock and obsolescence, cutting inventory costs by 20–30%. Lower waste = lower COGS.
Supply chain expenses → AI route optimization, shipment tracking, and supplier analytics cut logistics costs by 10–20%, reducing fuel, overtime, and expedited shipping.
SG&A → Automating warehouse ops and fulfillment reduces labor costs and errors, trimming overhead.
Inventory carrying costs (balance sheet) → Optimized stock levels reduce working capital tied up in inventory, freeing cash for growth or debt reduction.
Revenue upside → Faster delivery and better product availability lift sales conversion and reduce lost revenue from stockouts.
📊 Impact example: A consumer goods firm using AI forecasting freed millions in working capital while improving fill rates—turning inventory efficiency into both margin expansion and revenue growth.
3. Why This Matters to CEOs and CFOs
AI-driven efficiency gains don’t just lower costs—they improve margin resilience and balance sheet strength:
EBITDA expansion → Lower SG&A and COGS, higher gross margins.
Cash flow improvement → Better DSO and inventory turnover reduce working capital needs.
Top-line growth → Faster response times and availability increase conversion and retention.
AI is therefore a dual lever: cost-out + growth-up.
4. Key CFO Questions (and Where AI Fits)
Which P&L categories capture inventory carrying cost reductions?
→ Typically balance sheet inventory plus SG&A (handling), depending on accounting policies.
How much can COGS decline from AI-driven logistics efficiency improvements?
→ Benchmarks show 10–20% logistics cost reduction, translating directly to lower COGS.
How should I allocate labor automation savings between COGS and SG&A?
→ Depends on function: warehouse and fulfillment savings → COGS; sales, support, AP → SG&A.
What EBITDA uplift timing should I expect after inventory turnover improves?
→ Firms see working capital relief within 1–2 quarters, with 4–6% EBITDA uplift in year one.
How do channel discounts or fulfillment fees change with AI-led stock optimization?
→ Improved fill rates reduce penalty fees and reliance on costly last-mile fulfillment, lifting gross margin.
5. The Bottom Line
For mid-market firms, AI is not a “nice to have.” It’s a structural driver of financial performance.
On the P&L, it lowers COGS, trims SG&A, and grows revenue.
On the balance sheet, it frees working capital, improves cash conversion, and stabilizes recurring revenue.
The hidden cost of doing nothing is real: slower sales, bloated inventory, higher logistics spend, and tighter cash positions. Competitors with AI roadmaps are already compounding these advantages into stronger EBITDA and balance sheets.
The smartest play? Start with a 90-day pilot tied to a P&L line. Prove the impact, measure the financial gain, and scale.
Curious where AI could move your margins and cash flow fastest?
Book a discovery Call and see how we can help tie AI directly to your P&L.
Some resources to go further:
https://media-publications.bcg.com/BCG-Executive-Perspectives-Future-of-Sales-with-AI-EP2-5Aug2024.pdfhttps://online.hbs.edu/blog/post/ai-in-business
https://hbr.org/2025/08/how-finance-teams-can-succeed-with-ai
