43% of finance leaders are prioritising AI for FY2027. But what are the actually buying?
Q4 is here and it’s changing conversations (if it’s not, well it should be)
Often experiments become business cases and the ideas that follow become budgets. Then the questions shifts from “what could AI Do?” to “What are we actually going to invest in?”.
According to Deloitte’s 2026 financial trends research, 23% of finance leaders prioritising AI and advanced technology for FY2027.
Meanwhile, 54% are involved in enterprise AI and technology, capital allocation, while
43% are prioritising changes to the finance operating model.
AI is no longer just a technology conversation. It is a business investment.
What are businesses actually buying?
It is easy to build a case around:
£X → AI platform → implementation → adoption
But a business-first business case looks very different:
£X → reduce tender processing time → increase operational capacity → process more opportunities → increase revenue
One is a technology investment, and the other is a business outcome with technology supporting it.
Start with the business problem
Before adding another AI capability to the 2027 roadmap, businesses should ask:
· Where are we losing the most time?
· Where is the operational capacity being constrained?
· Which processes create unnecessary friction?
· Where are skilled people spending time on repetitive work?
· What would change if we redesigned those processes?
Only then should technology conversation begin.
For a construction business that might mean redesigning how PQQs and tenders are processed. For finance it could mean reducing the time spent gathering and validating information before decisions are made. For manufacturing it could mean connected fragmented supplier and technical information.
The AI isn’t the business case, the business outcome is.
As organisations finalise their 2027 budgets perhaps the question isn’t “how much should we spend on AI”. It’s “What business outcome would make that investment worth it”.
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