AI has become a vital tool in marketing workflows, enabling teams to save time and maintain a strong connection with their audiences. According to new data from Clutch, 61% of marketers already use AI for planning, data analysis, and personalization. But 83% expect to allocate less than 20% of their marketing budget to AI tools.
This gap between usage and investment raises important questions for 2026. If AI is already embedded in marketing operations, why are budgets still so conservative? And what does it mean for your strategy in the new year?
Where Marketers Are Actually Using AI Today
Most marketers today use AI to improve existing workflows instead of replacing them with new ones. The most significant sources of adoption include:
- Media planning and optimization: Automated bid adjustments and other capabilities improve media buying efficiency. For example, an AI tool can identify the optimal budget breakdown across social media, email, and pay-per-click (PPC) ads based on your performance across each.
- Audience segmentation and data analysis: AI processes large amounts of data faster than humans, finding new behavior patterns that companies use to refine their targeting strategies. This can lower new customer acquisition costs over time.
- Content personalization: Dynamically adjusted messaging and creative content align to match more precise behavioral signals. Marketers use these capabilities to ensure each message they send to leads is personalized and impactful.
These use cases are leading AI adoption in marketing because they feel relatively “safe.” They support existing workflows and human-led decision-making instead of transforming the marketing process entirely. This makes adoption easier for employees, leading to fast insights and performance gains. This explains why 61% of marketers already use AI. It has become a new layer that makes existing marketing systems more efficient without requiring significant process transformation.
Why Budget Commitment Remains Low
Despite broad adoption, Clutch data shows that 83% of marketers expect AI to account for less than 20% of their overall budgets. Several factors are driving this restraint:
- ROI is difficult to isolate: AI’s financial impact can be hard to measure in isolation, which makes it difficult to justify when planning a budget.
- Internal capability gaps: Without the internal skills to fully leverage advanced AI features, additional investment can feel premature.
- Risk and control concerns: Brand safety and compliance issues also limit how aggressively teams are willing to scale their AI usage.
According to Deloitte research, leaders today believe AI rarely delivers value in isolation. One executive noted, “We only managed to get a ballpark estimate of benefits because it was hard to separate AI from [other] initiatives.”
Hype vs. Reality: Where AI in Marketing Is Overpromised
High adoption rates indicate that marketers recognize the value of AI, but investment remains a small slice of budgets. Platforms may market themselves as offering fully autonomous campaign management. But research from IBM shows teams have several concerns preventing them from taking full advantage of these benefits, including:
- 45% have concerns about data accuracy and bias.
- 42% of those surveyed say they don’t have enough proprietary data available to customize models.
- 42% report having insufficient expertise in generative AI.
AI systems are only as accurate as the data they receive and the humans supporting them. Investment in AI could remain a relatively small share of marketing budgets until organizations develop the internal expertise to leverage the technology more effectively.
Strategic Recommendations for Smarter AI Investment
Marketing leaders hoping to get more value from AI tools often need to allocate their resources more deliberately to get there. That means:
- Connecting AI to a single business metric: Build AI investments around clear outcomes like improving customer acquisition costs or conversion rates.
- Funding enablement alongside software: Investing in training, workflow redesign, and new governance processes can deliver more long-term ROI than additional tools.
- Scaling from proven wins: Leaders should expand AI investment only after pilot programs prove repeatable performance gains.
- Assigning clear task owners: Oversight of new AI tasks should be assigned to specific people to avoid confusion and delays.
- Start with data you trust: AI tools use data to deliver insights. To maintain the accuracy of those insights, start with datasets that you trust before expanding to more complex workflows.
Following these principles will help your marketing leaders focus AI spend where it delivers the most significant impact in the new year.
What This Means for 2026 Marketing Leaders
AI has become an essential component of many marketing workflows, but the financial commitment still lags behind adoption, as evidenced by the numbers: 61% of marketers are using AI, yet 83% are spending less than 20% of their budget on it. In 2026, the teams that see the best returns on AI spending will be those that align their investments to match clear business priorities and internal capabilities.