The following is a future historian’s view of potential events that might occur today or in the near future. It is intended to give some insight into the potential uses, applications, and consequences of the use of AI in the marketing industry and beyond.

---

By mid-2025, 25 AI-generated songs made it on the Billboard Top 100 chart, surpassing The Beatles record by one song. In July of the same year, the majority of playlists generated by users on Soundcloud, Spotify, and iTunes included at least one AI-generated song.

In early 2026, AI-Rock launched in partnership with the top music platforms, consuming their music and user data (anonymously, of course) to drive the creation of the Adaptive Music Generation Engine (AMGE)*.

The AMGE utilized user data to create custom music for each user based on their personal listening habits, playlists, and the preferences of similar users in the central database.

In its first iteration, the program simply asked the user to specify their top 20 favorite songs in order to generate custom music in the genre, melody, harmony, rhythm, timbre, pitch, silence, and form that they would most prefer.

To further enhance user experience and music consumption, AI-Rock also accessed all public records of each user to assess their current life events, habits, and personal interests to create lyrics relevant to their current mood, socioeconomic status, religious beliefs, political beliefs, and other public-facing information.

Users could further enhance their results by completing a detailed personality assessment through the platform.

The final enhancement available involved opening all communication platforms and private data to the platform, allowing AI-Rock to assess personal relationships, each user’s current mood in real time, and both known and unknown shifts in a user’s personality as perceived by the application.

By 2027, a number of mental health organizations began using AI-Rock to treat anxiety, mood, and personality disordered. Their use of the application eventually led to the development of Therapeutic Musical Interventions for Depression and Stress (TMIDS), which was widely adopted as both a direct and preventive treatment for a number of mental disorders.

The following is a future historian’s view of potential events that might occur today or in the near future. It is intended to give some insight into the potential uses, applications, and consequences of the use of AI in the marketing industry and beyond.

By late-2023, over half of all online educational providers had begun to implement educational courses augmented by AI. The intention was to solve a nagging problem in the industry… low completion rates.

In the beginning of 2023, the completion rate was stuck at 15%, as it had been since the original fully-online educational platform, Jones International University, was founded in 1996.

As AI-customized content became increasing popular with the wide adoption of AI application in early 2023, many educational organizations began to implement customized coursework.

By mid-2023, an application called Intellicurriculum became a dominant player in the course-customization marketplace.

The concept was simple… train the Intellicurriculum AI, nicknamed Fiini (pronouned “Feeny”), to understand the interests of each student, then modify the course to include examples and concepts that feature those interests.

Early iterations of the application focused on user hobbies, typically sports whenever possible. For example, if a student named Bill enjoyed golf, each lesson would incorporate golf concepts and practices into what was being taught. When Bill wanted to learn about operational management, what better way to make a dry subject more interesting, than by including his favorite hobby. Here’s the content that Bill could expect to consume:

The Fiini AI eventually incorporated a wide set of factors to create customized content for each user, including customized video, audio, graphic, and written coursework.

As students continued to use the application, their performance and progress continued to become more efficient, increasing the completion rate of online courses from 15% to over 95% by the end of 2024.

One explanation for the rapid increase in completion rates was course length. Since learning efficiency increased substantially, the length of the courses decreased by orders of magnitude. Without the need to manually incorporate multiple learning styles with each course, the duration of each was slashed by 50-90%.

Further, course creation became much faster. Rather then spending the majority of their time conceptualizing ways to explain core concepts, educators simply created the concept itself. Intellicurriculum then did the “heavy lifting” of creating examples and formatting the lesson into the preferred learning style of the user.

By 2025, most courses, both in-person and online, were transferred to platforms utilizing Intellicurriculum AI.

The following is a future historian’s view of potential events that might occur today or in the near future. It is intended to give some insight into the potential uses, applications, and consequences of the use of AI in the marketing industry and beyond.

In 2024, the AI named book – converter was launched and consumes over 10,000 texts overnight. Each text became its own app that could be searched and utilized by the user however they needed

One of the books was called Ted’s woodworking. Rather than simply looking up useful plans for items that could be built the app first force the user to fill out a short questionnaire about their wants needs and expectations.

For example, a user could specify which pieces of wood they had available, the tools they had available, and their previous history in woodworking based on this information, the app would then propose hey series of projects that could be used to create items with the resources available.

The real benefit of the process was that it broke down the barriers between learning a lesson and taking action. Historically, when trying to get into woodworking, a novice maybe stops by the need for specific materials, specific tools, and a general understanding of woodworking or the skill in question.

The plans that were proposed based on the user resources were not simply step-by-step instructions, rather they were displayed in the preferred learning method of the user. While one user may get a detailed video tutorial created specifically based on their available resources, another user may instead get a PDF-style manual with the same instructions, the key to making the app useful for both the vendor and the user is that these materials would be automatically generated based on the information in the original book in the resources of the user.

Further instructions, in regards to the dimensions of the item being created, will adjust based on the amount of wood, time, and skills of the user

The following is a future historian’s view of potential events that might occur today or in the near future. It is intended to give some insight into the potential uses, applications, and consequences of the use of AI in the marketing industry and beyond.

---

In late 2023, Slack, the all-purpose communication hub used by over 100,000 businesses, added an AI query capability to their application. Previously, the rudimentary search function could only search based on keywords and user names, restricting its use to the information known by the user.

Essentially, the AI consumed all data within a company’s Slack channel, assessing the information, intent, mood, subject, and patterns of all user conversations and shared data, including documents, links, pictures, videos, and other media. For an additional fee, the AI could also access patterns of in-formation collected by all Slack channels managed by the application to make judgments based on conversations within a single network.

The new search function massively enhanced each user’s ability to find conversations based on in- tent, rather than simple terms. The reach of these searches was restricted by the level of each person in the company.

For example, a lower-level user could search based on general project information, such as, “who was the last person to work on the Weyland project.” This capability allowed any user, no matter how limited their knowledge of the subject they were searching to get immediately up to date on the status of projects and other company events.

However, for higher-level users in management positions, the capability was expanded to recognize patterns in user conversations and comments to judge potential actions. For example, “who in the company is unhappy with their manager and why.” Slack would then as- sess all conversations to look for patterns of negativity, dissatisfaction, and mood by as- sessing conversations rather than simply look- ing for specific terms.

It could also be used to predict the future actions of employees by accessing application-wide patterns in all companies that use the application. The most useful function was to assess the conversations of employees who left their positions and when. Using this data, any manager could ask the question, “which employees will leave the company within the next 3 months,” to find future holes within the organization. The information could then be used to help prevent the exit, or speed it up to avoid complications in the future.

The following is a future historian’s view of potential events that might occur today or in the near future. It is intended to give some insight into the potential uses, applications, and consequences of the use of AI in the marketing industry and beyond.

---

In mid-2024, a startup called FuturaFashion.ai launched a new custom fashion application that allowed users to upload or select photos in order to create custom clothing based on an aggregated style created by AI.

The photos could be of the user themselves, but more often it was pictures of other individuals.

The key to making new styles of clothing was not simply an aggregate of the pictures themselves, it also incorporated the style of the user by integrating with their most-used social media platform to determine patterns in the user’s current style and the style of pictures they engaged with.

This information was combined with the porportions, skin tone, hairstyle, environment, and profession of the user to create sets of custom clothing.

While the user could simply choose a single item, FuturaFashion would maintain a “virtual closet” that would update as further input of the user was collected.

The virtual closet also included a gallery in which photos of the user in each piece of clothing could be viewed.

The pictures included standard full length views of the user in each piece of clothing, but also included lifestyle pictures as well, featuring vacation photos, family photos, important events, and even private activities like book reading, yoga, cooking, and other situations that rarely warranted a photo in real life.

This allowed the user to truly picture themselves using the clothes without involving their imagination. The company also planned a future version of application that included videos of the user, but that was still in development as of the writing of this entry.

Once an item was chosen, it would be automatically 3D printed and delivered within 24 to 48 hours. FuturaFashion partnered with Ministry of Supply to produce their products on demand.

The following is a future historian’s view of potential events that might occur today or in the near future. It is intended to give some insight into the potential uses, applications, and consequences of the use of AI in the marketing industry and beyond.

---

By the end of 2023 Bing surpassed Google as the top search engine in the world. 

Utilizing its new ChatGPT function called Bing-AI (BAI), users were provided with custom taylored articles that succinctly answered their queries in the style in which they preferred.

Rather than choosing a link from thousands or millions of search results, BAI displayed a landing page with the resulting content in a style, length, and reading level consistent with the preferences of each user.

Preferences were determined by the browsing habits of the user and the way in which they asked questions. 

Initial results were determined by “old style” analytics such as Time on Page and Average Page Depth, but as soon as a user opted into BAI-Preferred ($7 per month for basic access up to $50 per month for prioritized access, speed, and reduced ads), the system would create content based on prescriptive, predictive, diagnostic, descriptive, and cognitive analytics.

The new analytical drivers built a unique query engine called a System of User-centric Online Search Logistics (SOUL for short). A user’s SOUL was essentially a learning and evolving AI itself, essentially becoming an avatar that would communicate with BAI to deliver increasingly taylored results.

When BAI was initially launched, the best sources of content related to the search could be found underneath the summarized result. While some people found this feature helpful, very few actually scrolled the page long enough to consider or click on those links.

Within six months of initial launch, the practice was abandoned. In its stead was placed additional customized content pieces based on what BAI predicted a user would ask next based on their SOUL.

As expected, BAI essentially became a commercialized and monetized version of ChatGPT. Initially, ads were displayed similar to old style search results, with advertisements integrated into text within the summarized piece and banners in the side column, header, and footer of the resulting page.

What was unexpected was the eventual abolition of traditonal advertisements altogether. Rather than rely on vendors to create advertisements and pay for their placement, BAI would simply create content that guided the user’s content consumption and browsing towards commercial solutions.

Since a user’s SOUL would essentially track all aspects of a user’s behavior, including their emotional, mental, and spiritual status (physical status couldn’t be determined until BAI-VR was launched in 2028), creating content that subtley shifted their minds towards products and services became automated.

Rather than bidding for placement, vendors would go through an intensive process of product qualification in order to determine their “ad” placement and pricing.

Microsoft had an ethical and financial imperative in ensuring that only the best products could be advertised on the network. Obviously, the subtle (some would call subliminal) creation of commercially guided content creation had the potential for misuse, which would be much more obvious if low quality, dangerous, or immoral products were being promoted.

For this reason, BAI would price advertising based on their ADLIFE score, which qualified a vendor based on the quality, reviews, longevity, customer service, and positive results of the product and company.

These metrics were determined by scraping the vendor’s website and online precense on social media networks and professional organizations, massively increasing the importance of vendor content creation, branding, product creation, and customer service.

By mid-2024, automated content creation techniques had improved to include customized videos, podcasts, courses, and infographics in search results. This was a pivotal event in the exponential growth of data creation, distribution, and consumption, which we now identify as the start of The Inflection Point, a moment in history that still has major ramifications in our lifestyles today.