TL;DR: This explores the evolution of the downstream functions: Judging and Actioning across three AI eras: Experimentation (2024-2026), Acceleration (2026-2028), and Elevation (2028-2030). It highlights how AI will progress from a supportive tool to an active participant in decision-making for Judging, and from task assistance to autonomous execution in Actioning. The piece emphasizes the changing roles of marketers and agency professionals, who will need to adapt to working with increasingly sophisticated AI systems while maintaining ultimate responsibility for decisions and oversight of AI-driven processes.
- Key focus: Transformation of Judging and Actioning functions through AI integration
- Spotlight on the balance between AI-driven insights and human judgment in decision-making
- Emphasis on the shift from hands-on execution to strategic oversight in task management
As covered, AI offers immense opportunities to enhance productivity and drive innovation within the marketing industry. In the upstream section, we focused on three executive functions: Sensing, Visioning, and Defining. In the midstream section, we examined the engine room of marketing – Generating and Developing executive functions – due to experience a lot of change.
In this section, we will shift our focus to the downstream executive functions within marketing – where the rubber hits the road and where a sizable percentage of people working in marketing spend most of their time: Judging and Actioning. Again, we will assess each of these functions across three eras of development: the Experimentation Era, the Acceleration Era, and the Elevation Era.
Judging, a crucial executive function, entails the evaluation of options and making informed judgments. For individuals in high-level decision-making roles, such as CEOs, CMOs, and CSOs, the impact of machine learning and generative AI on this function will not be insignificant; with an index score of 84.
Judging in the AI Experimentation Era (2024-2026)
In this period, the integration of AI in decision-making is in its infancy, especially in the realm of marketing management. Initial applications will likely be in the form of GenAI tools that can process and provide data-driven insights. However, the role of AI in making final decisions will remain moderate, as these tools are primarily for support and enhancement rather than direction. Whilst many decision-makers may start to familiarize themselves with AI capabilities and learn to interpret the insights provided, the
Malcolm Devoy, Chief Planning Officer, PHD Worldwide – Interviewed June 2024
ultimate judgment will rest with the human executives.
Although only 17% of respondents predicted that the Judging function will be replaced by AI within the period to 2026, it does indicate a coming change – for later eras. For an increasing number of day-to-day functions that require human judgment and ‘decisioning’, AI will be used.
This will liberate individuals to take on more Developing functions – where greater value can be extracted. An example is in the application of automated media buying and creative optimizing operating platforms – from third-party platforms such as Google Performance Max or building bespoke bid-factor algorithms, augmenting existing ML approaches with Gen-AI to enhance Judging algorithms.
Judging in the AI Acceleration Era (2026-2028)
As AI technology matures, there will be a marked increase in its integration into decision-making processes. Bespoke versions of GPT and other AI models may be developed to aid decision-makers, offering assessments on the potential outcomes of various options. This era will see AI becoming a more active participant in the decision-making process, providing more in-depth analyses to inform judgments. Training for executives will focus on how to utilize these AI tools effectively and critically evaluate the options presented, ensuring that decisions are made with a comprehensive understanding of the projected impacts.
An application of this will be the use of machine vision AI to evaluate creative work, predicting its potential impact on targeted individuals. This represents a shift towards AI-augmented decision-making, where AI not only assists but actively contributes to the judgment process, enhancing the individual’s ability to make informed creative choices.
The transition to more AI-assisted decision-making will require new capabilities from individuals. This transition can be seen in the fact that 29% of respondents cite a need for retraining for the Judging function, emphasizing the importance of skill development in effectively leveraging AI for decision-making processes.
Judging in the AI Elevation Era (2028-2030)
It is the Judging function that sees the most significant impact in this era, with 36% of respondents believing Generative AI will replace this function for people working within marketing by 2030. This suggests that AI-driven decision-making will become the norm, with human intervention shifting towards supervising and augmenting the AI with new data-sets and/or tech integrations.
Approaching the edge of AGI, decision-making will be significantly influenced by AI. The technology is likely to move beyond mere suggestion to making the decision. Decision-makers will need to develop a keen sense of when to trust AI’s judgment and when to rely on their own experience and intuition. However, the decision will still be the individual’s responsibility. For major decisions, clients and internal stakeholders will still expect individuals to take responsibility for the ultimate decision.
The Path Forward
Throughout these eras, the role of AI in decision-making will evolve from a supportive tool providing insights to a sophisticated system capable of evaluating options and predicting outcomes. And, in some cases, making the decision. The challenge for executives will be to balance the efficiency and data-driven insights provided by AI with the nuanced understanding of human judgment. Talent development will focus on integrating AI into the decision-making process, while the technology will evolve from bespoke AI tools to Gen-AI closed-loop platforms
James Aylett, Chief Data Officer, Annalect – Interviewed June 2024
that offer a more dynamic and interactive decision-making environment.
The goal is to ensure that AI aids decision-makers without usurping the uniquely human ability to make judgments that take into consideration more than just data.
Actioning, a key executive function related to organizing tasks and executing projects, is significantly influenced by General AI and Machine Learning. This function has a high index score of 110.
Actioning in the AI Experimentation Era (2024-2026)
In the initial stages of AI’s integration within marketing management, machine learning and generative AI will be applied primarily to organize and optimize tasks, especially in roles associated with production and trading. AI’s ability to process vast amounts of data will enhance task organization, allowing for more efficient project execution. However, the complexity of some tasks will limit full AI automation during this period.
Clarissa Season, Chief Experience Officer, Annalect – Interviewed June 2024
The role of the individual will vary based on specific responsibilities but will universally require a systematic and procedural approach. Individuals in trading roles will manage the oversight of ML-based bid optimization, ensuring alignment with broader marketing strategies. Production roles will evolve, merging with Generating and Developing roles to oversee AI-driven production processes.
Actioning in the AI Acceleration Era (2026-2028)
There will be an accelerating increase in the integration of AI within marketing processes, particularly in task execution. Beyond the general administrative efficiency improvements of AI embedded more deeply into existing workflows, there will also be significant changes in specific marketing roles, particularly in production and trading.
Production roles have traditionally been differentiated from Generating roles. However, with the advent of generative AI, these roles will begin to converge, with production being managed on the same platform as generating and developing. For traders of programmatically served channels, Machine Learning-based bid optimization will likely be enhanced by generative AI to incorporate a wide range of unstructured data. The algorithms will develop intuition.
This is going to require a significant learning and development investment, with 45% predicting a need for retraining for Actioning functions, highlighting the growing importance of skill development to effectively implement AI-assisted marketing plans.
Actioning in the AI Elevation Era (2028-2030)
As we approach the threshold of artificial general intelligence (AGI), we’ll witness a paradigm shift in how tasks are actioned. AI will serve as an intelligence energy source that underpins all platforms, leading to a transformation in the role of individuals across agency roles. Trading roles will primarily oversee Machine Learning-based bid optimization, while production roles will larger have merged with the Generating and Developing executive functions. GenAI closed-loop’ platforms will autonomously activate based on performance data. The focus for individuals will shift from actioning to oversight, with a significant portion of tasks, including influencer engagement and brand partnerships, remaining as human-led activities due to their requirement sitting outside of a closed-loop automation platform.
Although the bulk of the changes to the Actioning function happen in the previous era, there is expected to be a continual requirement for training as we move into the Elevation era (33%) as advertisers and agencies use a range of new AI-enabled software and tools to automate and streamline administrative tasks.
This will allow them to focus on higher-value activities – as, even at this advanced era, 27% of respondents believe Generative AI will enhance the Actioning function, indicating that human input will remain vital for implementing marketing plans – mostly caused by the requirement to bring a whole range of different technologies and data capabilities together when building out complex activation activities.
The Path Forward
The evolution of the Actioning function will demand a fundamental shift in skills and mindset across the marketing landscape. As AI transitions from a supportive tool to an autonomous force, professionals must adapt their roles accordingly. Trading specialists will evolve into AI supervisors, overseeing complex ML-driven optimizations. Production roles will merge with Generating and Developing functions, creating a new hybrid skill set that combines creative oversight with technical proficiency.
The future workplace will be characterized by AI-driven, closed-loop platforms that autonomously activate and refine marketing strategies based on real-time performance data. However, the human touch will remain irreplaceable in areas requiring nuanced judgment, such as influencer engagement and brand partnerships. This new paradigm will require continuous learning and adaptation, with professionals focusing on high-value, strategic activities that fall outside the realm of AI automation.
Success in this AI-augmented future will hinge on developing a deep understanding of AI capabilities, cultivating strong oversight skills, and maintaining the flexibility to navigate between AI-driven processes and human-centric tasks. By embracing this transformation, marketing professionals can elevate their roles, driving innovation and strategic thinking in an increasingly AI-powered industry.
Future-Proofing a Marketing Organization
In PHD’s prior thought leadership initiative, Shift | A Marketing Rethink, the optimization of capabilities between client and agency organizations was examined to ascertain where each function is best situated. An interactive framework was developed, enabling individuals to pose a series of questions to pinpoint where a capability is most effectively placed.
For instance, capabilities involving the frequent handling of highly sensitive data, or those rapidly evolving in response to core business intelligence, are often optimally managed in-house. Conversely, for capabilities still developing, agency placement is preferable due to the enhanced learning from diverse client experiences and the specialized focus on the discipline itself.
Looking ahead to the next few years and the necessary adaptations for integrating artificial intelligence into marketing, we must evaluate the impact on the in-house versus outsourcing debate.
The critical perspective is to consider the unique benefits an agency can offer that an internal team cannot. This primarily involves access to a talent pool with advanced skills honed through exposure to various clients and a dedicated focus on the discipline.
It also involves understanding how the broader organizational design of the business is structured and maximizing the evolving roles of marketing executive functions as they are shaped and impacted by the AI revolution.
Summary
Within the broader agenda of the three distinct eras, specific adaptations will be necessary. Executive functions provide a lens for addressing these changes, offering a more focused approach than considering individual job roles since jobs encompass executive functions. The research revealed that while some functions, such as Generating and Actioning, will be significantly enhanced by AI, others will continue to rely heavily on the unique capabilities of human intuition, creativity, and emotional intelligence.
This will include the executive functions that will require development, with a specific focus on Defining (and Prompt Engineering), Developing (Executive Direction), Judging (Decision-making and Conviction), and Understanding (Intuition and Theory of Mind).
Furthermore, the dynamic between in-house and agency teams warrants consideration—how this interplay may need to evolve. Establishing a roadmap for development is crucial not only for the upcoming years but also as a foundation to brace for the next significant shift.
We stand on the precipice of a new dawn—the advent of Artificial General Intelligence (AGI). The following section, ‘The Clearing (Looking Towards the Horizon, and AGI),’ anticipates the changes that AGI will usher in. It will offer a guide to navigating the uncharted waters of a future where the lines between human and machine intelligence are not just blurred but merged.
