For decades, the advertising world has operated in a cycle of human-driven processes – from RFP responses, sales proposals, and media plan creation to campaign execution, reporting, and renewal efforts. While advanced data and analytics have slowly made their way into media companies’ toolkits, the process remains fragmented and labor-intensive.
However, a technological transformation is underway that will fundamentally reshape advertising workflows. Generative artificial intelligence (GenAI) coupled with machine learning capabilities are ushering in a new era of intelligent automation and optimization for advertising sales and media planning. Early adopters of these “sales copilots” are expecting significant near-term rewards, and the impacts will only accelerate as the technology matures.
STREAMLINING THE RFP RESPONSE CYCLE
For media companies, the RFP response process has long been an arduous affair – distributors, networks, publishers, and platforms all dedicate substantial resources to tailoring proposals, campaign strategies, media plans, pricing models and more for each opportunity. Despite their experience, teams must start from scratch recreating similar materials over and over.
GenAI is poised to completely revolutionize this inefficient process. By training AI models on a media company’s historical RFP responses, media plans, case studies, brand voice, market research and more, these systems can automatically generate materially complete drafts of new RFP proposals. Human experts simply need to review and refine the AI-generated deliverables, expediting turnaround times.
However, these AI assistants go far beyond simply replicating past content. By ingesting a multitude of data sources, GenAI will be able to instantly craft customized recommendations tailored to each prospect’s specific goals, budgets, and KPIs — and deliver plans with infinitely optimized yield.
Audience Insights and Media Mix Optimization – Today’s media planners struggle under the volume of data sources and manual steps required to build out a holistic, cross-channel media plan. GenAI models can ingest, analyze, and connect disparate data streams on audience behavior, media consumption patterns, purchase data, market research, digital engagement metrics, and more.
This unified data pipeline allows the AI to build sophisticated audience profiles and personas, identifying the optimal targeting strategies and media mix to achieve an RFP’s specific KPIs. Whether the goal is driving awareness, consideration, conversions, or something else, the AI will be able to rapidly model out and optimize channel strategies, media weights, timing, and delivery across linear TV, CTV, video, digital, audio, out-of-home, sponsorships, and more.
However, as history has shown, those that embrace technological disruptions and adapt are the ones who thrive long-term. Advertising has seen several waves of disruption, from print to digital, from direct to programmatic, from linear to Connected TV. Generative AI represents the next frontier.
Dynamic Simulations and Scenario Planning – Armed with unified data pipelines, GenAI can run limitless scenarios to customize and optimize each media proposal. Need to model out different budget levels, pacing strategies, audience concentrations, promotional tactics, or creative options? The AI will be able to simulate virtually infinite permutations, making recommendations while visualizing the tradeoffs and performance impact of each scenario.
Throughout a campaign, the AI will also ingest real-time performance data, automatically re-optimizing weights and allocation based on what’s driving incremental impact. No longer will planning be a static, upfront exercise – the AI will enable true unified data-driven planning across the entire lifecycle.
Intelligent Automated Execution and Optimization – Beyond media plan creation, AI will also accelerate advertising’s execution layer. For TV and digital video advertising, AI will be able to automatically analyze millions of ad placements, content ratings, household viewership data, and existing commitments to autonomously identify and secure optimal inventory for each advertiser’s KPIs.
AI reserves will bid on the ideal ad placements across programmatic pipes in real-time based on their projected and actual performance. This streamlines the labor-intensive work of manual allocation, stewardship, and ad serving optimization that’s currently required.
With new AI models advancing areas like predictive analytics, multitouch attribution, media mix modeling, and unified data pipelines, the opportunities to drive advertising returns will only grow. Ultimately, AI co-pilots will be embedded at every stage of the ad cycle, from upfront planning and guaranteed buying to unified investment management and intelligent autonomous execution.
A DAUNTING CHANGE ON THE HORIZON
For an industry rooted in human relationships and manual processes, the rise of autonomous intelligent automation may seem unnerving. However, companies that resist AI may be rendered obsolete, while those that lead the transformation will be rewarded.
The path won’t be simple – implementing unified data pipelines, training AI models, and building new partnership and revenue models will require substantial investment, talent, and change management. Developing or sourcing ethical and unbiased AI systems that respect privacy, empathy, and transparency will also be paramount.
However, as history has shown, those that embrace technological disruptions and adapt are the ones who thrive long-term. Advertising has seen several waves of disruption, from print to digital, from direct to programmatic, from linear to Connected TV. Generative AI represents the next frontier.
The opportunities for media companies are immense – driving unprecedented efficiency in operations, higher-value deployment of human capital, and most importantly, superior data-driven strategies to maximize advertiser ROI and business impact. Those that move swiftly will secure a decided advantage in the AI-driven future of advertising.
Lastly, a plug: check out Operative’s Adeline AI. In addition to delivering the information needed to speed tasks, it can also act as a Sales CoPilot. It can instantly generate plans helping you optimize inventory yield and respond to RFP’s more quickly than ever before. See what it’s all about!
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