Why Finance Teams Can’t Afford to Delay AI Adoption Any Longer

AI has quickly become one of the most transformative forces in finance, yet many organisations are still hesitant to take the first step. During our recent webinar with global AI expert Danilo McGarry, we explored why delaying AI adoption is no longer a neutral decision. In today’s finance landscape, waiting comes with a real cost: slower processes, reduced visibility, and widening competitive gaps.

Here’s a concise walkthrough of the biggest insights from the session.

Finance and AI: Where Teams Are Today

During the live poll, more than half of attendees shared that their organisation hasn’t yet adopted AI in any financial process. While common, this hesitation comes at a time when AI has become significantly more accessible and far more impactful.

Danilo noted that finance teams who have already embedded AI into their operations are seeing benefits such as:

• Faster, more accurate reporting

• Dramatically reduced manual work

• Better forecasting and decision-making

• More predictable cash flow

• Improved team capacity and morale

These teams aren’t just gaining efficiencies, they’re building what Danilo calls the “compounding interest of knowledge.” Every month they learn, refine and improve, putting even more distance between themselves and organisations still standing at the starting line.

The True Cost of Waiting

Postponing AI adoption doesn’t simply maintain the status quo, it creates drag.

1. Competitive disadvantage

Teams using AI today can operate 20% faster (or more) across forecasting, reporting, and communication. That speed compounds across an organisation, influencing pricing, planning, and strategic agility.

2. Delayed decision-making

AI powered predictive analytics gives finance leaders clearer forward-looking insight. Without it, decisions take longer and carry more risks.

3. Inefficient operations

Manual AP and AR tasks — keying invoices, chasing approvals, following up on late payers, resolving disputes — quickly pile up. Without automation and AI, these bottlenecks slow cash flow and increase error rates.

4. Talent risk

Finance teams today expect modern tools. When repetitive, manual work dominates their day, engagement drops and turnover risk increases.

Where AI Is Delivering Value Right Now

One of the strongest messages from the webinar was this: AI in finance is not theoretical anymore - it’s practical, proven, and already delivering results.

“AI is more than a technology for us - it’s a catalyst for possibility. It’s empowering our finance team to move beyond the numbers and focus on shaping the future of our business. By lifting the burden of routine work and opening the door to deeper insight, AI gives us the clarity and confidence to lead with purpose, innovate boldly, and create meaningful value for Quadient and our customers.” - Lyuda Zhuk, UK CFO UK & Ireland, Quadient

✅ In Accounts Payable (AP)

AI is streamlining the highest volume, most repetitive tasks — capturing invoice data, routing approvals, flagging duplicates and improving coding accuracy. **Quadient AP** helps teams reduce manual data entry by over 80%, gain real-time visibility into spend, and eliminate the delays that typically slow AP cycles.

✅ In Accounts Receivable (AR)

AR teams are experiencing some of AI’s biggest wins through predictive analysis. By analysing historical payer behaviour, AI helps teams prioritise high-risk accounts, reduce bad debt, and accelerate cash collection. With **Quadient AR**, teams gain clearer forecasting, automated reminders, and better visibility across the entire order-to-cash process.

How to Get Started: Danilo’s Five Step Approach

Danilo outlined a simple, practical blueprint for finance leaders ready to begin:

1. Educate your teams - build awareness and reduce fear.

1. Build skills - empower people to rethink how work can be done.

1. Reimagine processes - identify high-volume, high manual areas.

1. Adopt the right tools - don’t reinvent the wheel; choose platforms that scale.

1. Create governance - standardise best practices as you expand.

Most importantly: Start small. Pick one problem - like invoice intake, approvals or collections prioritisation - and run a quick proof of concept. Early wins generate buy-in and momentum.

Final Takeaway

AI isn’t optional anymore. It’s a multiplier for every finance team, enabling smarter decisions, faster cycles, and more strategic impact. Organisations that continue to delay adoption risk falling behind peers who are already moving.

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