AI Budget 2027: How Much to Plan and How to Split It

The 2027 budget cycle is underway in most executive committees. Between two trade-offs, the same question keeps coming back: how much goes to AI next year, and on what exactly?

This year's published benchmarks exist. Mostly, they tell a different story than the one they get quoted for: the amount matters less than the allocation.

"Technology budgets are set to rise for 75% of CFOs, and nearly half (48%) plan increases of 10% or more." Source: Gartner, survey of more than 300 CFOs, February 2026

How much are businesses planning to invest in AI in 2027?

Market benchmarks point to an average technology budget increase of about 10%, and nearly 60% of CFOs are raising their finance function's AI investment by 10% or more. The figures come from Gartner's budget survey of more than 300 CFOs, run in October 2025 and published in February 2026.

The average hides sector gaps: roughly a 15% increase in financial services against 6% in manufacturing, according to the same survey. One respondent in four (24%) plans a more modest AI increase, between 4 and 9%.

The same survey holds the most useful number for your 2027 exercise. For 47% of CFOs, AI still represents only 1 to 5% of the finance function's technology budget. The room to move is there, in the allocation, not in a spectacular envelope.

In Canada, the ground reality remains more modest than the intentions. According to Statistics Canada (June 2026), 19.2% of Canadian businesses used AI to produce goods or deliver services in the second quarter of 2026, triple the 2024 rate. Our analysis of Canada's AI adoption numbers details those gaps.

Why do so many AI budgets produce no measurable return?

Because the spending follows licences rather than processes, and at budget approval time nobody has documented the starting point. A tool deployed without a baseline will produce anecdotes, never a return you can defend to the board.

The most rigorous study in the country confirms it. According to Statistics Canada (April 2026), AI-adopting firms show labour productivity 16.8% higher, but the gap drops to 5.1% and loses statistical significance once initial productivity and complementary capabilities are accounted for, such as data analytics and training.

In other words, a large share of the return attributed to AI belongs to the foundations. Budgeting the tool without budgeting the foundations means paying twice: once for the licence, once for the catch-up.

The obstacles Quebec businesses name point the same way. For those that have not yet invested, La Presse reported in November 2025, based on Institut de la statistique du Québec data, three main barriers: high implementation cost, uncertain returns and a lack of specialized knowledge. All three are solved by method, not by a bigger budget. Our approach to measuring AI ROI describes the four indicators to document before the spend.

How do you structure a credible AI budget for 2027?

In three distinct envelopes: data foundations, one or two bounded use cases, and team capability. The exact proportions depend on your starting point, but the order does not change.

The first envelope funds what the Statistics Canada study identifies as the real driver of returns: data quality, system integration, access governance. The second funds one specific process, with its baseline and its owner. The third funds training, the line most often forgotten when the budget is filed.

A few benchmarks to situate your exercise:

• 75% of CFOs plan a technology budget increase, including 48% at 10% or more (Gartner, February 2026)
• Nearly 60% are raising the finance function's AI investment by 10% or more, and another 24% by 4 to 9% (Gartner, February 2026)
• 47% of CFOs still allocate only 1 to 5% of finance technology spend to AI (Gartner, February 2026)
• 88% of CFOs rank finance staff productivity among their top three priorities (Gartner, February 2026)
• 19.2% of Canadian businesses used AI in the second quarter of 2026, triple the 2024 rate (Statistics Canada, June 2026)
• 12.7% of Quebec businesses used AI in production in the second quarter of 2025 (Institut de la statistique du Québec, November 2025)

A transparency note: these figures describe survey averages and stated intentions, not the guaranteed return of any given project.

In the engagements PlanAxion leads with finance departments, the second envelope rarely starts from a blank page. A structured AI workshop over 4 weeks is enough to turn scattered ideas into a prioritized portfolio: prepare, identify, prioritize, validate the data, decide and deliver. The investment varies with scope and is confirmed during a short exploratory call.

The AI budget line should carry the name of a process, not the name of a tool.

Where does AI pay off fastest in finance processes?

In bounded, repetitive processes already rich in ERP data: cash application, reconciliations and the month-end close. These are the candidates able to produce a before-and-after measure within a single quarter.

The textbook example comes from multi-branch B2B distributors. One customer settles 40 invoices with a single wire, another deducts a credit note without documenting it: the accounts receivable team rebuilds the puzzle by hand while collections chases customers who have already paid. The cash application solutions PlanAxion puts in place target exactly this pool, described in our analysis of accounts receivable automation.

That choice has a direct budget consequence. A process your controller already measures (entry hours, unapplied payments, close duration) supplies its own justification to the board, with no extra study.

Where should you start before filing your AI budget?

With the inventory, not the amount. List the processes that bleed every month, document the baseline for two of them, then split the budget into three envelopes: foundations, use cases, capability. If that list does not exist yet, it is the first deliverable to fund, well before the licences.

Frequently asked questions about AI budgets in business

What share of the technology budget should go to AI in 2027?

There is no magic percentage. Gartner observes that 47% of CFOs still allocate 1 to 5% of finance technology spend to AI, while nearly 60% plan an increase of 10% or more. The right share is the one that covers a measured process, its data foundations and the training.

How do you justify an AI budget to the board?

With a documented baseline, meaning hours spent on the target process, exception rate and cycle time. The return is then demonstrated by comparing the same indicators after a quarter in production. A budget tied to one specific process always defends itself better than a general experimentation envelope.

What line items belong in a 2027 AI budget?

Three envelopes cover the essentials, namely foundations (data quality, integration, governance), one or two bounded use cases with their baseline, and team training. Statistics Canada shows that the return attributed to AI depends mostly on the complementary capabilities already in place.

Where does AI adoption stand in Canadian businesses?

According to Statistics Canada, 19.2% of Canadian businesses used AI in the second quarter of 2026, triple the 2024 rate. In Quebec, the Institut de la statistique du Québec measured 12.7% in the second quarter of 2025. Finance and insurance clearly lead adoption across sectors.