Agentic AI Transforms Marketing Spend: 2026 Budget Trends & Strategies

The Key Change: Marketing Spend as a Continuous Investment

The key change in marketing spend is the transition from periodic budget reviews to continuous, AI-driven optimization. Instead of annual or quarterly planning cycles, brands like Hershey are deploying agentic AI—multi-agent systems that autonomously monitor, analyze, and reallocate marketing dollars in near real-time. This shift redefines marketing not as a cost center to be managed but as an investment portfolio requiring ongoing performance scrutiny.

Hershey’s $2B AI Bet: Agentic AI in Action

Hershey, the confectionery giant, is leveraging agentic AI to transform how its roughly $2 billion marketing investment is deployed. According to a July 2026 report on WhatAboutMkt, the company is using a multi-agent system to move its marketing mix modeling (MMM) from a slow, periodic analysis to a continuous, near-real-time capability. This allows Hershey to be more responsive and accountable, treating marketing spend as an investment with ongoing performance scrutiny rather than a periodic review.

An Adweek exclusive detailed that Hershey’s approach involves multiple AI agents working in parallel: one agent monitors market conditions, another tracks campaign performance, and a third recommends budget reallocations across channels. Human marketers then validate the recommendations before execution. This system addresses what the company described as a "$2 billion blind spot"—the inability to dynamically adjust spend between digital, TV, retail media, and promotions based on real-time ROI data.

The implications are profound. Hershey’s move signals that even the largest consumer packaged goods (CPG) brands are convinced that traditional MMM—which often relies on regression analysis of historical data—is too slow for today’s fragmented media landscape. By adopting agentic AI, Hershey aims to capture incremental lift from faster budget rebalancing, potentially increasing ROI by 10-15% based on industry benchmarks.

Budget Growth Trends: 2027 Outlook

Marketing budgets are expected to grow significantly in 2027, but the allocation strategy is shifting. Research from Marketing Interactive, published July 22, 2026, reveals that 89% of B2B and 91% of B2C marketers anticipate budget increases. However, the emphasis is not simply on spending more—it’s on redirecting investments toward AI readiness, answer engine optimization (AEO), and marketing-specific AI capabilities.

This research underscores a strategic pivot: marketers are moving beyond basic AI adoption (e.g., using ChatGPT for copy) toward building operational foundations for sustainable business value. Specifically, the report highlights that increased budgets will fund:

• AI infrastructure (data pipelines, model training, agent orchestration)
• AEO-related content and technical SEO for generative AI search
• Training and upskilling teams to work alongside AI agents
• Experimental budgets for testing AI-driven attribution models

The finding that 91% of B2C marketers expect growth aligns with broader macroeconomic trends. As brands compete for attention in an AI-mediated environment, marketing spend is becoming a technology investment as much as a creative one.

The Rise of AI Agents: Impact on Consumer Spending

Perhaps the most forward-looking data comes from a collaboration between PHD and WARC. Their July 2026 research, titled "From Abundance to Agents," projects that AI agents will influence consumer spending at an accelerating rate, tripling from $944 billion this year to $3.35 trillion by 2030. This reshaping of the customer journey means that brands must learn to market not just to humans but also to machine intermediaries—AI agents that autonomously compare prices, check reviews, and make purchase decisions on behalf of consumers.

For marketing spend strategy, this has critical implications:

Aspect	Traditional Marketing	Agentic AI-Driven Marketing
Budget cadence	Annual/quarterly planning	Continuous real-time rebalancing
Optimization engine	Human analysts + MMM	Multi-agent AI systems
Target audience	Human consumers	Humans + AI agents acting on their behalf
Success metric	Last-click or multi-touch attribution	Agent influence score, lifetime value in agent-mediated journeys
Data velocity	Weekly/monthly reports	Millisecond response to market signals

• New metrics needed: Marketers will need to measure "agent influence"—how often their brand is recommended by an AI shopping assistant or agent. This may become a key performance indicator for marketing spend allocation.
• Channel mix shifts: Budgets may shift from direct-to-consumer advertising to paying for placement in AI agent ecosystems (e.g., Amazon’s Rufus, Google Shopping AI, or emerging agent marketplaces).
• Content standardization: To be easily digestible by AI agents, product data, reviews, and brand info must be structured, consistent, and verifiable. Marketing spend on content enrichment and schema markup could rise.

The AI Marketing Backlash: Why 'AI-First' Brands Are Starting to Fall Flat

Not all AI-driven marketing spend is succeeding. A growing backlash against "AI-first" brands is documented by Breef in a July 2026 analysis. The article "The AI Marketing Backlash: Why 'AI-First' Brands Are Starting to Fall Flat" warns that consumers are becoming skeptical of overly automated, impersonal brand interactions. Cases of AI-generated content that feels generic, chatbots that fail to handle nuanced complaints, and hyper-targeted ads that creep out users have led to negative brand sentiment.

This backlash has tangible spend implications. Brands that rushed to cut human creative roles in favor of AI may see declining engagement and higher customer acquisition costs. The lesson: AI should augment marketing teams, not replace them entirely. Budgets should allocate for human oversight—editors, strategists, and relationship managers—to maintain brand authenticity.

Practical Ecommerce’s analysis on one metric for total marketing payoff reinforces this: no matter how sophisticated the AI, the ultimate measure of marketing spend effectiveness remains contribution margin minus marketing costs. AI helps but does not change the fundamental need for profitable growth.

Practical Implications for Marketers

For CMOs and marketing leaders navigating 2026-2027, here are five actionable takeaways:

1. Invest in AI infrastructure now. The shift to continuous optimization requires clean, real-time data pipelines. Budget for data engineering and agent orchestration platforms, not just AI content tools.
2. Prepare for agentic consumers. Ensure product catalogs, reviews, and pricing data are structured for machine consumption. Schema markup and API-accessible product feeds will become as important as ad copy.
3. Redefine ROI models. Move beyond last-click or multi-touch. Incorporate agent influence scores and model the value of being recommended by an AI assistant.
4. Balance automation with humanity. As the backlash shows, consumers still value authentic human connection. Keep a portion of budget for high-touch, experience-driven campaigns.
5. Monitor emerging measurement standards. Organizations like WARC and PHD are developing frameworks for agent-influenced marketing. Stay updated to benchmark your spend effectively.

Conclusion

Marketing spend is entering a new era defined by agentic AI, continuous optimization, and the rise of machine consumers. Hershey’s $2 billion agentic AI initiative exemplifies the scale of change, while PHD and WARC’s research quantifies the opportunity. However, the AI marketing backlash reminds us that technology must serve human goals, not replace them. By strategically increasing budgets—89% of B2B marketers plan to—and redirecting toward AI readiness and AEO, brands can capture growth in this transformed landscape. The metric that matters most remains the one Practical Ecommerce emphasizes: total marketing payoff. Agentic AI, used wisely, can maximize it.