This article is Part 2 of our three-part series on the Best AI Training Courses for Digital Media Publishers. It focuses on AdOps Specialists, while Part 1 covers AI training courses for Content Creators.

Ad operations (AdOps) are the driving force behind digital media publishers' revenue. However, much of it also involves tedious, manual tasks requiring significant time and effort. According to one report, teams spend about seven hours each week performing manual, repetitive tasks.

Artificial Intelligence (AI) can transform AdOps.

AI use cases include providing enhanced audience insights, tracking real-time traffic, identifying and segmenting readers, managing subscription and paywall strategies, automating ad placement, recommending content, forecasting trends with predictive analytics, deciding pricing, detecting frauds, and more.

Generative AI takes this further with its ability to sift through large unstructured data sets, uncovering hidden patterns for improved targeting. It can even analyze a publisher’s ad performance data to generate ideas for what to do next.

With the global AI advertising market expected to reach $100 billion by 2027, AI in AdTech will see many advancements in 2024. While possibilities are endless, developing meaningful AI capabilities will require the efforts of experienced AdOps specialists and programmers. 

This blog lists a few resources for AdOps professionals and tech teams to upgrade their knowledge of AI and be prepared to leverage these technologies as they evolve.

What must AdOps pros look for in AI training? 

While the strategic judgment of AdOps specialists will remain central to building successful revenue models, AI tools can supercharge this. 

A good AI training/resource must enable AdOps teams to:

• Grasp what is happening around AI and how it matters
• Provide hands-on exposure to tools relevant to their work needs
• Match their skill level and their current understanding of AI
• Cover tools and skills that enable them to perform jobs faster and more efficiently
• Provide access to career paths by expanding on skills they already possess

Because AI models and their use in AdOps are evolving, few training courses are available. The ones listed below offer essential skills and insights about implementing AI in AdOps.

1. AI In Digital Marketing Course (Digital Marketing Institute)

This short, interactive course by the Digital Marketing Institute combines hands-on practical lessons, toolkits, and real-world examples to teach how to leverage AI to gain key insights from data, refine campaigns, and drive growth. 

It covers Generative AI and predictive analytics, using AI with data for decision-making, AI-driven campaign optimization, using AI to enhance digital strategy, and streamlining automation with AI.

The self-paced course is divided into 4 modules (total 5.5 hours) and is 100% online. It is priced around $535, which can be further discounted for groups. Upon completion, a certificate is provided. 

2. Personalized Recommendations at Scale (Up Limit)

This technical-oriented course provides a holistic overview of machine learning (ML) based modeling choices for developing and deploying multi-stage recommendation systems. 

It discusses algorithmic models that power such systems and includes case studies, lessons, and practical considerations from deployed systems powering over 400 million users. It also covers the nuances of online experimentation, AB test designs, and online metrics.

The course is available on Uplimit at $500. Alternatively, it can be accessed through Uplimit membership, which costs $1000 yearly.

3. aX Roundtable: AI in Programmatic Advertising

This webinar, hosted by AudienceX, provides insights on:

Applications of AI in Modern Programmatic Advertising:

• ​​AI-driven platforms for real-time bidding and ad placement decisions.
• Deep learning and computer vision for sophisticated tasks like fraud detection and ad content analysis.

Impact of AI on Ad Optimization and Efficiency:

• How to use AI to create targeted campaigns and dynamic ad personalization
• How to analyze massive data sets quickly, optimize bids, and personalize ads based on user behavior and context.

AI's Future Prospects in Advertising:

• How continual improvements in AI will lead to even more personalized and efficient advertising strategies.
• Potential for AI to manage more complex decision-making processes autonomously
  
  

The webinar also provides insights into the evolution and growth of AI in AdOps.

4. Adriel’s Blog On AI Reshaping the Future Of Advertising

AdOps platform Adriel, trusted by 6,300+ leading brands, shares interesting insights in their blog titled “The Future of Advertising is Here: How AI is Reshaping the Industry.”

Key takeaways:

• We are closing toward a more efficient ad industry powered by AI. This means more relevant ad experiences, better audience segmentation, conversion rates, and ROAS.
• It is now possible to put the entire advertising process on autopilot, allowing human focus to be directed toward strategic direction and decision-making.
• AI can analyze user behavior, preferences, and contextual information, empowering advertisers to deliver highly tailored and relevant ads to their target audience.
• AI-powered predictive analytics promises to revolutionize the ad space by forecasting trends.
• AI will automate much manual work, but human intervention will remain the key to creative and more strategic tasks.
• The blog also includes case studies on how McDonald's, Amazon, and SBT (a Brazilian broadcaster) have used AI in Digital Marketing and Advertising campaigns. 

5. Comprehensive Overview of DCO by Gourmet Ads

Gourmet Ads has been in the industry since 2008 and manages over 3,500 curated websites. In its blog on Dynamic Creative Optimization (DCO), the advertising platform explains how to maximize ad effectiveness and ROI by automating ad creation, streamlining workflows, and adapting campaigns based on real-time user data, such as location and behavior.

The blog discusses the role of AI and machine learning and how to effectively implement DCO through best practices, such as defining clear campaign goals, effective testing and iteration, and balancing automation with human oversight.

6. AI and Programmatic Advertising

This blog by AiThority covers artificial intelligence and programmatic advertising with insights from leading Adtech executives and CEOs.

Key takeaways:

• AI and Programmatic Synergy: AI and ML can significantly enhance programmatic advertising through hyper-targeted, personalized ad experiences, crucial in the cookieless era.
• Data Utilization: Leveraging first-party data, contextual targeting, and real-time ad optimization through AI-driven insights ensures effective paid media activation while respecting user privacy.
• Efficiency and Automation: AI automates ad placements, creative adjustments, and performance optimization, reducing manual efforts and increasing campaign efficiency and effectiveness.
• Enhanced Personalization: AI-powered contextual targeting and real-time adaptability lead to more relevant and engaging ads, improving user engagement and conversion rates.
• Ad Fraud Prevention: AI plays a pivotal role in detecting and preventing ad fraud, improving transparency and ROI in programmatic advertising.
• Strategic Testing and Learning: Continuous experimentation with different strategies, channels, and technologies is vital for adapting to the evolving digital advertising landscape.
• Human-AI Collaboration: Maintaining a balance between AI automation and human oversight ensures quality control, creativity, and adherence to brand standards in advertising campaigns.

Conclusion

AI is revolutionizing the AdOps industry, with the global AI advertising market expected to reach $100 billion by 2027.

As AI continues to advance, it is crucial for AdOps professionals to stay proactive in their learning and adapt to the evolving digital advertising landscape. The training courses and resources outlined in this article provide valuable insights and hands-on experience for AdOps specialists aiming to expand their knowledge of AI and its applications in their field. By grasping AI's potential, such as improved targeting, automation, fraud detection, and predictive analytics, AdOps teams can streamline workflows, enhance campaign performance, and ultimately drive revenue growth for digital media publishers.

To remain competitive in this rapidly changing environment, AdOps professionals must acquire the necessary skills to leverage these emerging technologies effectively.