I’m seeing a “good” problem emerging for our clients on a regular basis - the AI budget pot. Senior marketers are being handed this ambiguous line item on the budget spreadsheet, but the big question is how to use it sustainably. A question that becomes all the more important when you read Gartner’s 2026 research, suggesting that only 30% of brands are ready to scale their AI capabilities.
So if you’re looking for a smart way to allocate AI budget, here’s some practical thinking on the biggest mistakes to avoid, how to get started, how to ensure maximum returns - and for those who don’t already have an AI budget pot - how to build the business case for one.
Before we get into what to do, it’s important to start with two areas to steer clear of.
The first is Investing without consideration of the category a brand operates within. In pharma and biotech, 59% of AI citations come from earned media, while in fashion, social media accounts for a greater share, at 16.5% (WARC, 2026). Different categories, different audiences, different sources of influence, resulting in different solutions.
The issue is that ‘thought leadership’ in the market will rarely communicate this nuance, instead opting to capitalise on the uncertainty of emerging technology with generic, broad-brush ‘x hack to drive growth’ articles. We all saw this earlier this year with Reddit: 12 months of every Social Media Manager, SEO operator and Growth Marketeer touting Reddit as the platform to be on, only only for Reddit’s share of citations within ChatGPT to drop 86% overnight. I dread to think how much time, money and resource was allocated towards now ineffective tactics.
This is a great tee up for our second watch-out. Chasing trends without a strategy to fall back on. The landscape is fundamentally shifting on a monthly (and often weekly) basis. Listening to every tip, trick and hack will result in a dozen directions, a dozen content streams and AI investment spread too thin across each to truly make an impact.
Ultimately, both of these issues are based on the same fundamental flaw: brands moving away from their market, and their customers, believing that ‘AI Investment’ has to do something fundamentally new. It doesn’t.
Brands are discovered through their customers’ sources of influence. The platforms they look toward for inspiration, research, and comparison. The platforms they see themselves reflected within. Any AI budget that isn’t being invested into these areas, that isn’t bringing your brand closer to your customers, and that doesn’t align with your already highly considered marketing strategy, is budget that would be better spent elsewhere.
So, how do you determine where that is?
It sounds basic, but consider your objectives. With how much genuine innovation the adoption of AI can provide, it can be easy to be drawn to the shiny stuff.
“You can now generate Influencer content in a fraction of a second, at a fraction of the cost!” or “This agentic workflow will save [insert hyperbolic time saving] per week!”.
Enough big bets and one will no doubt pay off, but not before you’ve been called into the boardroom at least half a dozen times to explain what your investment is delivering, and why it should make next quarter’s financial plan.
The smartest (and most successful) allocation of AI budget is typically viewed in the same way as investment against media, SaaS platforms and agencies: commercially accountable, and measurable against an end goal. At Journey Further, we identify that end goal, and build from there.
Next, look at where you’re already investing. These are the capabilities that support any business in delivering against those goals. Let’s ground this in an example… X brand wants to drive GEO visibility, because a post-purchase survey told them that 17% of customers last month came from ChatGPT.
The first is execution, the second is technology, the third is capabilities - and all are equally valid use cases for utilising AI budget. But you can only arrive at the right one by knowing what you expect that budget to deliver, and what’s stopping you from delivering that in their current state.
At Journey Further we use Map, Means and Metrics.
Map tells us where customers are actually discovering and evaluating the brand, and where AI is influencing that journey. Means identifies what’s stopping the brand from winning in those spaces — whether that’s capability, technology, resource or execution. Finally, Metrics then gives us a clear way of measuring whether the investment is actually delivering.
This helps us ensure that we aren’t starting with the technology, and looking for a problem to solve. Instead, we start with the commercial objective, understand the discovery landscape, identify the constraint, and then put the budget against the thing most likely to move the needle.
Using the Map, Means, Metrics framework above, as well as the rest of this article, you should hopefully have a clear understanding of your objective, what’s stopping you from achieving it, what you need to do to overcome that obstacle, and how you plan on measuring it. You’re 95% of the way there. The last step is packaging that up in a pitch that maximises the chance you get the budget signed off.
First, a quick watch out: pitching an AI budget as a technology investment immediately invites scrutiny around tools, efficiency savings and speculative returns. Instead, make the case for a ring fenced growth and innovation fund, with AI as one of the means through which it delivers value.
Then, you want to frame that fund against these three areas:
The strongest business case is that there are identifiable opportunities to grow, clear constraints preventing you from capturing them, and a structured way to invest in overcoming those constraints.
So if you’re looking for a smart way to allocate AI budget, here’s some practical thinking on the biggest mistakes to avoid, how to get started, how to ensure maximum returns - and for those who don’t already have an AI budget pot - how to build the business case for one.
The biggest mistakes brands make when investing in AI
Before we get into what to do, it’s important to start with two areas to steer clear of.
The first is Investing without consideration of the category a brand operates within. In pharma and biotech, 59% of AI citations come from earned media, while in fashion, social media accounts for a greater share, at 16.5% (WARC, 2026). Different categories, different audiences, different sources of influence, resulting in different solutions.
The issue is that ‘thought leadership’ in the market will rarely communicate this nuance, instead opting to capitalise on the uncertainty of emerging technology with generic, broad-brush ‘x hack to drive growth’ articles. We all saw this earlier this year with Reddit: 12 months of every Social Media Manager, SEO operator and Growth Marketeer touting Reddit as the platform to be on, only only for Reddit’s share of citations within ChatGPT to drop 86% overnight. I dread to think how much time, money and resource was allocated towards now ineffective tactics.
This is a great tee up for our second watch-out. Chasing trends without a strategy to fall back on. The landscape is fundamentally shifting on a monthly (and often weekly) basis. Listening to every tip, trick and hack will result in a dozen directions, a dozen content streams and AI investment spread too thin across each to truly make an impact.
Ultimately, both of these issues are based on the same fundamental flaw: brands moving away from their market, and their customers, believing that ‘AI Investment’ has to do something fundamentally new. It doesn’t.
Brands are discovered through their customers’ sources of influence. The platforms they look toward for inspiration, research, and comparison. The platforms they see themselves reflected within. Any AI budget that isn’t being invested into these areas, that isn’t bringing your brand closer to your customers, and that doesn’t align with your already highly considered marketing strategy, is budget that would be better spent elsewhere.
So, how do you determine where that is?
The first thing you should do with unallocated AI budget
It sounds basic, but consider your objectives. With how much genuine innovation the adoption of AI can provide, it can be easy to be drawn to the shiny stuff.
“You can now generate Influencer content in a fraction of a second, at a fraction of the cost!” or “This agentic workflow will save [insert hyperbolic time saving] per week!”.
Enough big bets and one will no doubt pay off, but not before you’ve been called into the boardroom at least half a dozen times to explain what your investment is delivering, and why it should make next quarter’s financial plan.
The smartest (and most successful) allocation of AI budget is typically viewed in the same way as investment against media, SaaS platforms and agencies: commercially accountable, and measurable against an end goal. At Journey Further, we identify that end goal, and build from there.
Next, look at where you’re already investing. These are the capabilities that support any business in delivering against those goals. Let’s ground this in an example… X brand wants to drive GEO visibility, because a post-purchase survey told them that 17% of customers last month came from ChatGPT.
- It could be that they’re already tackling Content, Digital PR and Owned Media through their SEO team, in which case ‘AI budget’ might be best allocated towards scaling their most successful tactics
- Alternatively, they might not be aware of what’s driving this visibility, so ‘AI budget’ should be allocated towards GEO tracking platform(s) to understand what’s working, and therefore where to invest
- Or, they might be under-investing in Owned and Earned media, so ‘AI budget’ should actually be allocated against an agency partnership or internal hire to drive forward these areas.
The first is execution, the second is technology, the third is capabilities - and all are equally valid use cases for utilising AI budget. But you can only arrive at the right one by knowing what you expect that budget to deliver, and what’s stopping you from delivering that in their current state.
A framework to follow
At Journey Further we use Map, Means and Metrics.
Map tells us where customers are actually discovering and evaluating the brand, and where AI is influencing that journey. Means identifies what’s stopping the brand from winning in those spaces — whether that’s capability, technology, resource or execution. Finally, Metrics then gives us a clear way of measuring whether the investment is actually delivering.
This helps us ensure that we aren’t starting with the technology, and looking for a problem to solve. Instead, we start with the commercial objective, understand the discovery landscape, identify the constraint, and then put the budget against the thing most likely to move the needle.
“I don’t have an AI budget, what can I do?”
Using the Map, Means, Metrics framework above, as well as the rest of this article, you should hopefully have a clear understanding of your objective, what’s stopping you from achieving it, what you need to do to overcome that obstacle, and how you plan on measuring it. You’re 95% of the way there. The last step is packaging that up in a pitch that maximises the chance you get the budget signed off.
First, a quick watch out: pitching an AI budget as a technology investment immediately invites scrutiny around tools, efficiency savings and speculative returns. Instead, make the case for a ring fenced growth and innovation fund, with AI as one of the means through which it delivers value.
Then, you want to frame that fund against these three areas:
- Priority opportunities. Where are the biggest constraints to growth? Where are customers discovering competitors instead of you? Where are you under-invested, or unable to act on opportunities because you lack the right capabilities? And most importantly, what data do you have that supports each of these areas? That's the opportunity you're asking the business to fund.
- Tangible activity. Identify a handful of initiatives that address those constraints, whether that's AI-enabled execution, new technology, better measurement or specialist partnerships. Each should have a clear hypothesis, an estimated investment and an agreed measure of success over a specified time horizon. You don't need to promise transformational returns upfront, but you do need to demonstrate a credible path towards them.
- Accountable returns. For the budget, agree how initiatives will be prioritised, and establish clear criteria for scaling, iterating or stopping them. This makes the investment feel less like a blank cheque for experimentation and more like a controlled portfolio of growth opportunities.
The strongest business case is that there are identifiable opportunities to grow, clear constraints preventing you from capturing them, and a structured way to invest in overcoming those constraints.
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