Creative Production

Why marketing procurement is struggling to derive value from AI

By Lauren McBride

The focus on generative AI has detracted from where real marketing value can be found, which is AI for operational efficiency and effectiveness.

Hidden Values

For procurement professionals tasked with ensuring value from technology investments, this presents a significant challenge. The tools capturing the largest share of budget may not be delivering proportional returns. Meanwhile, less flashy but potentially more valuable operational applications remain unexplored or underfunded.

Since the explosion of ChatGPT 3.5 in late 2022, we’ve witnessed a seismic shift in how businesses approach artificial intelligence. Marketing departments, traditionally at the forefront of technological innovation, have enthusiastically embraced AI – particularly generative AI – with investment increasing exponentially across the sector. The allure is understandable: the ability to generate compelling copy, eye-catching imagery, and engaging videos with minimal human intervention promises significant time and cost savings.

However, this rush toward content creation capabilities has potentially obscured a more valuable application of AI technology. While there is little doubt that the evolution of generative AI is and will be transformational for businesses, it’s our experience that the singular focus on “creation” represents only a fraction of AI’s potential value to marketing operations. The true power of AI may lie not in its creative capabilities, but in its operational applications – the systems and processes that underpin effective marketing execution.

At ITG, we believe the real value of AI technology is found in what we call “operational AI” – applications that enhance efficiency, effectiveness, and measurable outcomes across the entire marketing workflow. For procurement teams tasked with driving value from their organization’s marketing investment in AI, shifting focus toward operational applications may deliver substantially greater returns than creative tools alone.

The current state of AI in marketing: Creative fascination, operational neglect

The current landscape of AI adoption in marketing reveals a clear pattern: disproportionate investment in generative capabilities at the expense of operational applications. According to recent industry surveys, over 70% of marketing AI budgets are allocated to content generation tools, with only 30% directed toward operational improvements. This imbalance reflects a natural tendency to pursue the most visible and immediately impressive applications of new technology.

Marketing leaders, understandably captivated by AI’s creative potential, have eagerly incorporated tools that can generate blog posts, social media content, and even design elements. The appeal is immediate and tangible – showing executives an AI-generated advertisement provides an impressive demonstration of the technology’s capabilities. However, this fascination with creative applications has created several challenges.

First, the market has quickly become saturated with AI-generated content, diminishing its initial impact and novelty. Second, many organizations report difficulties integrating these creative tools into existing workflows, creating bottlenecks rather than efficiencies. Finally, and perhaps most importantly, measuring the ROI of purely generative AI has proven elusive, with many marketing departments struggling to demonstrate how these investments translate to improved business outcomes.

The untapped potential of operational AI in marketing

Operational AI represents a fundamentally different approach to leveraging artificial intelligence in marketing. Rather than focusing primarily on content creation, operational AI enhances the systems, processes, and decision-making frameworks that enable effective marketing execution. These applications may lack the immediate “wow factor” of generative tools but often deliver more substantial and measurable business impact.

Key operational AI applications include:

Content intelligence and management

Automated analysis and tagging of content assets
AI-assisted briefing across channels and markets, aligned with campaign activation strategies
Driving production efficiencies by finding and recommending the right content for every briefing requirement
Culturally relevant AI-driven localization of assets

Compliance and quality assurance

Automated review for brand, campaign, legal, and regulatory compliance
Consistency checks across multichannel assets
Proactive identification of potential issues before campaign launch

Personalization and optimization

Dynamic content composition using audience data and insights
Enabling personalization at scale across all channels
Measuring and managing creative effectiveness through ongoing optimization

Data integration and orchestration

Connecting data and content across the content ecosystem and production lifecycle
Consolidating and remediating data to enable effective data-driven actions
Building the foundations for advanced analytics and insights

Operational AI employs multi-modal LLMs and LLM agents to analyze and orchestrate content, as well as to manage intelligent automation, workflows, and data associations. It also leverages other advanced technologies such as knowledge graphs and statistical techniques to drive meaningful improvements in marketing operations.

The value proposition of these applications is compelling. Unlike purely creative tools, operational AI addresses fundamental challenges that marketing departments face daily: efficiency, consistency, compliance, personalization, and measurement. These applications don’t just create content – they enhance the entire system by which marketing delivers value to the organization.

Procurement’s strategic role in realizing AI value

For marketing procurement professionals, the distinction between creative and operational AI applications has significant implications. As strategic enablers of technology value, procurement teams are uniquely positioned to help organizations rebalance their AI investments toward applications with clearer, more measurable returns.

This strategic shift requires procurement to:

Reframe the AI value proposition

Rather than evaluating AI tools primarily on their creative capabilities, procurement should assess potential investments based on their ability to address key operational challenges. Questions like “How will this improve workflow efficiency?” or “What measurable outcomes will this enable?” should take precedence over “What can this create?”

Establish clear success metrics

Operational AI naturally lends itself to more concrete measurement. Procurement can help establish KPIs that reflect genuine business impact: reduced production time, improved compliance rates, increased asset utilization, or enhanced campaign performance. These metrics provide a more robust foundation for ROI calculations than the often subjective assessments of AI-generated creative.

Foster cross-functional collaboration

Implementing operational AI effectively requires alignment between marketing, IT, and business stakeholders. Procurement can serve as a bridge between these functions, ensuring that technology investments address genuine operational needs while integrating smoothly with existing systems.

Prioritize scalable solutions

Rather than pursuing point solutions for specific creative tasks, procurement should advocate for platforms and approaches that can scale across the marketing operations ecosystem. Operational AI often offers greater potential for application across use cases, maximizing the return on technology investments.

The business case for operational AI typically proves more compelling than that for purely creative applications. While generative tools may offer impressive demonstrations, operational applications deliver measurable improvements in efficiency, effectiveness, and outcomes. For procurement professionals tasked with demonstrating value, this distinction is crucial.

Balancing creation and operation: The path forward

The future of AI in marketing isn’t about choosing between creative and operational applications – it’s about finding the right balance that delivers maximum value. As the initial fascination with generative AI matures into a more nuanced understanding of the technology’s potential, organizations have an opportunity to recalibrate their approach.

For procurement teams, leading this recalibration means advocating for a more balanced portfolio of AI investments. This doesn’t mean abandoning generative AI entirely – these tools can certainly have their place in the early stages of creative ideation. Rather, it means ensuring that operational applications receive appropriate attention and funding relative to their potential business impact.

The organizations that derive the greatest value from AI will be those that understand it not as a creative novelty but as a transformative force across the entire marketing operation. They will leverage AI not just to create but to orchestrate, optimize, and measure – driving improvements at every stage of the marketing lifecycle.

As marketing departments continue to navigate the rapidly evolving AI landscape, procurement professionals have a unique opportunity to guide investments toward applications that deliver genuine, measurable value. By shifting focus from the dazzling but limited world of generative AI toward the broader potential of operational applications, they can help their organizations realize the true transformative potential of this revolutionary technology.

The future of marketing AI isn’t just about creating better content – it’s about creating better systems for delivering the right content to the right audience at the right time. For procurement professionals looking to drive value from their organization’s marketing investment in AI, that operational focus may well pay the greatest dividends.

About the author

Lauren McBride, Head of AI at ITG