2027 AI budget: how much to forecast and how to allocate it?

The 2027 budget cycle is underway in most executive committees. Between trade-offs, the same question keeps coming up: how much are we putting into AI next year, and exactly what for?

The benchmarks published this year exist. Above all, they tell a different story than what people are claiming: the amount matters less than the allocation.

“Technology budgets will increase for 75% of CFOs, and nearly half (48%) expect an increase of 10% or more.” Source: Gartner, survey of over 300 CFOs, February 2026

How much do companies plan to invest in AI in 2027?

Market benchmarks point to an average increase of about 10% in technology budgets, and nearly 60% of CFOs are increasing their finance department's AI investment by 10% or more. These figures come from the budget survey conducted by Gartner in October 2025 among more than 300 CFOs, published in February 2026.

The average masks sectoral differences: about a 15% increase in financial services, compared to 6% in manufacturing, again according to Gartner. One in four respondents (24%) expects a more modest increase in AI investment, between 4% and 9%.

The same survey contains the most useful figure for your 2027 exercise. For 47% of CFOs, AI still accounts for only 1% to 5% of the finance department's technology budget. The room for manoeuvre is there, in the allocation, not in a spectacular budget envelope.

In Canada, the reality remains more modest than the intentions. According to Statistics Canada (June 2026), 19.2% of Canadian businesses were using AI to produce goods or provide services in the second quarter of 2026, three times more than in 2024. Our analysis of AI adoption figures in Canada details these gaps.

Why do so many AI budgets fail to produce a measurable return?

Because spending follows licenses rather than processes, and at the time of budget approval, no one has documented the baseline situation. A tool deployed without a baseline measurement will produce anecdotes, never a return that can be defended before the board.

The most rigorous study in the country confirms this. According to Statistics Canada (April 2026), companies that adopt AI show 16.8% higher labour productivity, but the gap falls to 5.1% and loses all statistical significance once initial productivity and complementary capabilities, such as data analytics and training, are taken into account.

In other words, a good portion of the return attributed to AI belongs to the foundations. Budgeting for the tool without budgeting for the foundations amounts to paying twice: once for the license, and once for the catch-up.

The obstacles cited by Quebec businesses point in the same direction. For those that have not yet invested, La Presse reported in November 2025, based on data from the Institut de la statistique du Québec, three main barriers: high implementation costs, uncertainty of return, 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 spending.

How do you allocate a credible AI budget in 2027?

In three distinct envelopes: data foundations, one or two limited use cases, and team skills. The exact proportion depends on your starting point, but the order does not change.

The first envelope funds what the Statistics Canada study identifies as the true driver of return: data quality, system integration, and access governance. The second funds a specific process, with its baseline measurement and a person in charge. The third funds training, the item most often forgotten when the budget is submitted.

A few benchmarks to help you plan your exercise:

• 75% of CFOs expect an increase in technology budgets, with 48% expecting an increase of 10% or more (Gartner, February 2026)
• Nearly 60% are increasing their finance department's AI investment by 10% or more, and 24% by 4% to 9% (Gartner, February 2026)
• 47% of CFOs still allocate only 1% to 5% of their finance technology budget to AI (Gartner, February 2026)
• 88% of CFOs rank finance team productivity among their top three priorities (Gartner, February 2026)
• 19.2% of Canadian businesses were using AI in the second quarter of 2026, three times more than in 2024 (Statistics Canada, June 2026)
• 12.7% of Quebec businesses were using AI in production in the second quarter of 2025 (Institut de la statistique du Québec, November 2025)

Transparency note: these figures represent survey averages and stated intentions, not guaranteed returns for any specific project.

In the mandates PlanAxion carries out for finance departments, the second budget envelope rarely starts from a blank slate. A structured 4-week AI workshop is enough to turn scattered ideas into a prioritized portfolio: prepare, identify, prioritize, validate data, decide, and deliver. The investment varies based on scope and is confirmed during a short exploratory call.

The AI budget line should be named after a process, not a tool.

Where does AI provide the fastest return in financial processes?

In bounded, repetitive processes that are already rich in ERP data: cash application, reconciliations, and month-end closing. These are the candidates capable of producing a before-and-after measurement within a single quarter.

A typical example comes from multi-branch B2B distributors. One client pays 40 invoices with a single transfer, another deducts a credit note without documenting it: the accounts receivable team reconstructs the puzzle by hand while collections chases clients who have already paid. The cash application solutions PlanAxion implements target this exact opportunity, as described in our analysis of accounts receivable automation.

This choice has a direct budgetary consequence. A process already measured by your controller (entry hours, unapplied payments, closing time) provides its own justification to the board, without the need for additional studies.

Where should you start before submitting your AI budget?

Start with an inventory, not a dollar amount. List the processes that are bleeding resources every month, document the baseline measurement for two of them, then divide the budget into three envelopes: foundations, use cases, and skills. If this list doesn't exist yet, it is the first deliverable to fund, well before any software licenses.

Frequently asked questions about corporate AI budgets

What portion of the technology budget should be dedicated to AI in 2027?

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

How do you justify an AI budget to the board of directors?

With a documented baseline measurement: hours spent on the target process, exception rates, and cycle time. The return is then demonstrated by comparing those same indicators after one quarter in production. A budget tied to a specific process is always easier to defend than a general experimental fund.

What items should be included in an AI budget in 2027?

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

Where does AI adoption stand in Canadian businesses?

According to Statistics Canada, 19.2% of Canadian businesses were using AI in the second quarter of 2026, three times more than in 2024. In Quebec, the Institut de la statistique du Québec measured 12.7% in the second quarter of 2025. The finance and insurance sectors are clearly leading in adoption.