Generative AI Marketing Trends 2024
Cahit Arf is a Turkish mathematician known in Algebra and Number Theory, inventor of the Arf Invariant, Arf Rings, and Hasse-Arf Theorem. He contributed to differential geometry and group theory by expanding his scope and mentoring generations of mathematicians around the globe. Cahit Arf asked a question in 1959 directly related to the second quarter of the 21st century and beyond.
“Can Machines Think, and How?
The question in 1959 is answered in today’s world. Technically, a machine can’t think, but it can imitate thinking by assigning a combination of numbers to every data point called a vector. Even if machines can’t think, their limitations and capacity for helping humans are the center of the trends in 2024.
Remember, this article was created to explain business trends and marketing reflection. Thus, you will see a long analysis that can change your vision for your future.
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Now, deep dive into the Generative AI Marketing and Business trends in 2024. Generative SEO is presented in my speeches throughout 2023, and they are all being added to our course now.
Welcome to the Year of Agents: 2024 Generative AI Marketing and Business Trends
Agents are specialized automation for certain tasks. An agent can use an API and its data to interpret with Generative Pre-trained Transformers and help traders trade, coders, code, designers design, writers write, or even judges judge and doctors treat. Agents can communicate with each other. Agents can replace each other for different conditions without human intervention.
OpenAI Launches Its Agent Store
OpenAI is launching its own GPTStore, which is an Agent Store. The entry cost for the creation of an agent is meager. This means that in 7 days, millions of agents will be created, and most of the GPTStore will be crapware rather than software. But still, the economy in the AgentStore will be huge, while most of the Software Designers in the UpWork will need to check what’s going on here.
You should take into account what an agent army can do. Let’s check some of the actual real-world existing companies, which have sold nearly over 1.5 Billion Dollars or raised hundreds of millions of dollars with simple AI and Robotics.
1. RoadBotics: One such company is RoadBotics, which emerged from Carnegie Mellon University’s Robotics Institute. RoadBotics uses AI and machine learning to assess road conditions and prioritize repairs. Their GIS-based platform, RoadWay, analyses stretches of highway to provide reliable condition ratings and imagery that assist in local budgeting and decision-making processes for road maintenance.
2. A2E Ltd.: Another notable initiative is from Robotiz3d Ltd, a joint venture spinoff formed by the University of Liverpool in partnership with A2E Ltd. This company uses AI and robotics to detect and repair road and infrastructure defects. Their technology, which autonomously detects and characterizes road defects like cracks and potholes, is particularly noteworthy for its potential to assess the severity of such defects and perform repairs to prevent them from worsening.
3. Vaisala: This company has developed RoadAI, a technology that assists in managing road network condition assessments and safety inspections. RoadAI can reliably and objectively analyze road conditions, make maintenance decisions, respond faster, and keep roads safer. Vaisala’s solution aims to enhance infrastructure management, operational efficiency, and roadway safety through AI in collaboration with industry experts and engineers.
4. Maintain-AI: This company provides an AI-powered road maintenance and inspection solution focusing on automated road inspections. Their technology, which includes advanced computer vision and AI road maintenance techniques, revolutionizes road defect detection, offering a cost-effective alternative to manual inspections. Maintain-AI’s platform can detect road defects quickly, improving the inspection process significantly. By using computer vision to identify and prioritize road defects, road maintenance professionals can allocate resources more efficiently, reducing both the time and costs associated with road maintenance
5. Virtualitics: the USAF has partnered with Virtualitics, a company specializing in AI techniques, to support the Mission-Capable (MC) rates. This metric measures the readiness and quality of an aircraft fleet. The AI solutions provided by Virtualitics enable technicians to proactively address issues during routine maintenance, thereby reducing unplanned downtime. Implementing predictive maintenance is seen as a game-changer in improving day-to-day and deployment decisions, which can lead to significant cost savings and enhanced mission effectiveness.
6. C3.ai: C3.ai’s predictive maintenance platform leverages AI to monitor assets across various industries. It identifies abnormal behaviors across systems and assets, provides prioritized alerts, and recommends prescriptive actions. The platform is designed for reliability engineers, maintenance managers, and executives, integrating workflow for proactive maintenance decision-making.
7. Dingo: Specializing in heavy industries, Dingo uses its Trakka platform to optimize asset health management. It combines data analytics, machine learning, and domain-specific expertise. The platform predicts failures and prescribes maintenance actions, improving equipment reliability and extending life.
8. ABB: ABB’s predictive maintenance solutions use AI algorithms to analyze real-time data from critical assets. The Ability™ Predictive Maintenance software identifies anomalies and forecasts failures, helping businesses to reduce downtime and maintenance costs.
9. Honeywell: Honeywell’s predictive maintenance solutions are aimed at industrial sectors like oil and gas, aerospace, and manufacturing. Their Connected Services use digital technology to improve operational efficiency, offering greater operational visibility and performance benchmarking.
10. PTC: PTC’s ThingWorx platform is an AR-enabled predictive maintenance solution. It uses IoT, analytics, and AR technology for asset monitoring and failure prediction. ThingWorx helps visualize asset health, improve maintenance planning, and reduce operational costs.
11. Uptake: Uptake provides AI and analytics solutions for predictive maintenance across manufacturing, energy, and transportation sectors. Their platform combines data science, machine learning, and industry expertise to deliver actionable insights, optimize maintenance schedules, and improve asset reliability.
12. General Electric (GE): GE Digital SmartSignal and its Digital Twin solution are central to GE’s predictive maintenance offerings. These solutions enable industrial companies to predict, diagnose, and prevent critical equipment downtime.
13. SAP: SAP’s predictive maintenance solutions are part of its intelligent asset management offerings. They utilize AI and machine learning to analyze sensor data, identify patterns, and forecast potential failures, integrating with other enterprise systems for optimized maintenance operations.
14. Siemens: Siemens offers a range of predictive maintenance solutions for various industries. Their acquisition of Senseye enhances their asset intelligence capabilities, using AI to detect anomalies, predict failures, and schedule maintenance strategically.
15. IBM: IBM Watson IoT uses AI and machine learning to analyze data for predictive maintenance. Their Predictive Maintenance and Quality solution helps predict instrument failures, adjust maintenance schedules, and mine maintenance logs for effective repair procedures.
There are more examples of companies that leverage AI with Predictive Analytics for maintenance and repairment optimization for efficient use of the resources.
If you use GPTs for creating simple apps, such as “Keyword Clustering” or “Named Entity Recognition,” you do not get the full potential here. You can create billions of dollars of value companies with the help of Organized Agent Armies. Look below carefully; a company recognizing the plants’ and their types raised 52 Million Dollars in May 2023.
AI helps with 3 Main Things
There are three main benefits of artificial intelligence for businesses.
- Prediction Precision: AI interprets and analyzes current data to forecast future trends and outcomes. This ability is precious for businesses in market analysis, consumer behavior prediction, and inventory management. By leveraging sophisticated algorithms and vast datasets, AI can identify patterns and correlations invisible to human analysts. This leads to more accurate predictions, enabling businesses to make well-informed decisions, anticipate market changes, and stay ahead of the competition.
- Generation Precision: AI’s capacity for generating high-quality, realistic outputs like images, music, films, voices, and texts such as poems, essays, and articles is revolutionizing content creation. This precision allows businesses to produce a wide range of digital content more efficiently and cost-effectively. AI-generated content can be tailored to specific audiences, enhancing engagement and personalization. For example, AI can generate targeted ad copy, personalized email content, or even create marketing campaigns, saving time and resources while improving effectiveness.
- Reaction Precision: AI systems continually improve through learning from feedback and adjusting their actions accordingly. This aspect of AI, known as machine learning, enables systems to become more accurate and efficient over time. In customer service, for instance, AI-powered chatbots learn from interactions to provide better, more relevant responses to inquiries. AI can analyze customer feedback in product development to suggest improvements or new features. This adaptive capability ensures that businesses remain dynamic and responsive to changing market demands and customer needs.
How to Create an Army of Agents?
There are early examples of no-code visual builders for connecting APIs to GPT models, downloading any language model from Huggingface, and using it inside the Agents. Since the market is early, I won’t name any technology for this purpose. But below, you can see an example of a use-case to build an Agent for Image Generation using Vision LLM with an HTTP Endpoint.
Many people generate images by using ChatGPT to generate image prompts, then go to Midjourney to create the image, and then go to another app to change the style of the image or its texture. How about one agent who does all of these? Or how about creating an image generation technology for all the images you take with your phone, which directly emails you them by making the changes you ask for? How about taking all the ranking images on Google Image search results and merging the standard components in these images with the theme in your title tag for visual relevance and uniqueness signals? I know this is the first time I talk about “ranking”, but AI is beyond SEO, and Business is the real SEO. Then we talk about Business AI.
You can see another Agent Construction example below.
All these examples are at the early stages of Agent Creation. Still, there is a reason that first, I shared the AI-relied Companies, which raised over 100 Million Dollars and announced over a half billion dollar annual revenue.
You can create these companies that raise hundreds of millions and announce billions of dollars of revenue and their advanced technologies as One Person with Agent Armies, seek funding, or go for the open market with your showcases.
But, if everyone starts to create these technologies so easily… What will separate you from others? Three things: Your Data, Your Model, and Your Marketing.
Why is Data Digital Oil today?
There are nearly over 60 different AI-based start-ups today for only fashion generative technologies. Fashion generative technologies generate images with new clothes on a certain person who might. Imagine you want to see how this cloth would fit on you, or you have a special design for yourself, but you want to see how it looks on you, and you can use these AI technologies to see it. However, the main problem is that most companies use only general public image generation models, as presented in CivitAI. When you enter this website, you will feel like you have already seen all these textures or image styles.
Due to this common image generation method, your data becomes more valuable than oil. More quality data means a better model for production, precision, or extraction based on AI.
Data is where a bad product is differentiated from a good one in AI. The same goes for search engines and information retrieval systems, too. Let’s say you have a specific search algorithm for quality understanding, which is stolen. The algorithm will only perform similarly if the algorithm thief or the imitator has the same data. Thus, you can understand that even if many Googlers pass into Microsoft or Apple, they still can’t create the same quality search engine result pages because they do not have the same level of rich data. The algorithm’s quality might decrease the amount of needed data, but data quality is always a must for the quality of AI products.
Why are Deep Learning and Machine Learning Models Important in Business?
ML and DL models create a real difference in the business; since Google, Microsoft, and Amazon know this need, they launched two main things.
- AI Studios will help AI and ML developers employ new models.
- AI Training Chip production companies to employ new heights for chip consumption.
To support this culture, NVIDIA even declared Language Model Developers’ Day.
Amazon launched its SageMaker Studio in December 2023. SageMaker allows developers to employ new ML and AI models to support their businesses for 3 main benefits of AI: generation, prediction, and reaction.
Google launched its Vertex AI Studio to support developers and help them train their custom models.
The competition between these giants for helping developers in the AI industry is always leading us to two things, and these are.
- Stock prices are affected by even the declaration of AI technologies or chips.
- Free model improvements are happening thanks to every chatbot user. Even Google Bard directly states that human reviewers process every conversation with Google Bard. These tech Giants again use any model, experiment, or improvement on data or uploaded data to improve their technologies. More users mean more models, data, and feedback for better algorithms. Check below to see the Human Reviewer warning from Google.
You can check the headline below to see all these reactions and moves tied to stock prices or personal gain. OpenAI buys AI Chips from Sam Altman’s company, meaning Sam Altman’s latest resignation and board member drama are tied to personal business affairs around chip production.
Similarly, Amazon Stocks increased 81% in 2023.
NVIDIA accelerated its chip production in the same way.
In 2024, NVIDIA plans to significantly ramp up its chip production, particularly for its H100 AI processor. They aim to deliver between 1.5 million and 2 million units of the H100 chip, a substantial increase from the 500,000 units anticipated in the previous year. This move is in response to the growing demand for AI processors, with NVIDIA’s chips already sold out well into 2024. However, the company is also facing challenges due to global supply chain disruptions
NVIDIA uses AI-generated images directly from their models in their blogs. To fully increase the stock market price advantage while helping with chip production, they launched their new technology for LLM development.
They even launched their courses and LLM Development software, which accepts developers with applications. NVIDIA even contacted me to make me try their software, and I know many SEO software companies have started using their system to improve their products.
NVIDIA started to create electronic books for the large language models as above.
Similarly, NVIDIA launched its LLM newsletter, which you see directly in my inbox. As a result of AI Chips, Generative AI courses, software, community, and influencers, NVDIa increased its revenue 3 times in 2023 and increased the stock value more than 2 times.
You can see the NVIDIA stock price changes during the 2023.
Digital Marketing Trends come from Business Trends, which rely on global companies and what they develop during the year. You need to understand the stock value changes and companies’ investments in business technologies to see the future of marketing trends.
In this context, having a customized generative model that relies on unique data is the most important thing to create the product difference. Because without having personalized data, you will end up using the same model as the competitor, and the output will be the same. Other important aspects remain response time, generation speed, user interface, pricing, and customer service. Still, these won’t be a separator between the winning and losing businesses in 2024 and beyond.
Every AI Chip producer focuses on gathering more developers to their platform while creating LLM and Model employment systems to gather their data and feedback while making the industry bigger and faster for the future demand for their AI chips.
Remember, Data, Model, and Marketing are the three columns of future businesses.
In my SEO Vibes Budapest 2023 SEO Speech and Sofia SERPConf 2023 speech, I mentioned the importance of LLM Optimization for SEO and how I use or train different language models for different purposes. I use a different LLM for HTML tables and a different one for comparison sentences. Imagine you have an Agent Army that you trained with your data. For example, once, I explored the data of a website that lost against its main competitor, a broad core algorithm update. Still, the search engine signaled these more permanent and negative results during the ranking tests and changes throughout the year. How about creating an agent to realize these ranking anomalies and create early alert systems with custom click curves? Can you create this tech and launch it on GPTStore?
After discussing Data and Models, let’s move into the marketing phase.
Digital Marketing Trends with Generative AI and Machine Learning
Marketing is where a business differentiates itself from other competitors and alternatives. Being the closest brand entity in the perception map for a specific solution and advantage requires creative and diverse repetition of a single but strong message that entails prestige, uniqueness, and intelligence. I graduated from Advertisement Design and Communications at Yeditepe University, and all of the Doctors in my educational lectures mentioned the prominence of “message.” Your product’ and its quality must be consistent with your message.
To explain the Generative AI-related marketing business trends, we will take the Coca-Cola Company as a strong example.
1. Generative AI Chatbot for Support
Coca-Cola launched its chatbot to help users with the help of Meta AI Studio. Answering customers and clients with the help of artificial intelligence and answering their needs instantly or generating leads with AI is helpful for customer loyalty while decreasing the costs of customer relations.
An example of a customer-focused generative AI Chatbot from CocaCola.
Holistic SEO launched a similar Generative AI Chatbot to help visitors and the Holistic SEO Community. A separate chatbot for Topical Authority course members, which answered over 30.000 questions in the last 9 months.
Generative AI Chatbot of Holistic SEO: https://www.holisticseo.digital/seo-chatbot
2. Image Generation for Gathering Leads
Coca-Cola uses art generation contests and social media to ignite visibility and virality among customers. It turned itself into an art item by helping customers use generative AI to help their marketing.
An example of Generative AI use for product placement with aesthetics.
Below you can see the contest of Coca Cola Generative Art.
3. Video Marketing with Reimagined Art
Digital marketing statistics involve reaching out to prospects based on marketer choices. Video marketing always has a heavy share among marketers. As shown below, Coca-Cola uses Reimagined Art to create viral social media content with aesthetics and a universal ambiance.
Some of the video marketing statistics to learn are below.
- Video is the most popular content format that web users consume. Source: Holistic SEO & Digital
- 87% of digital marketers say that video content increases website traffic. Source: Wyzol
- 80% of the video marketers say that the content improved their sales. Source: Wyzowl
- 20% of the visitors read the article, and 80% watch the video. Source: Entrepreneur
- 59% of decision-makers prefer video over text. Source: Forbes
- Users prefer watching videos 400% more than reading about a product. Source: Animoto
- 25% of users lose interest without video on their website. Source: Animoto
- Consumers watching videos convert 1.81 times more. Source: Animoto
- 81% of companies use videos as a marketing tool. Source: Experian
- Video content has a chance to generate 50 times more organic traffic. Source: SEOTeric
- Landing pages that use video get 86% more conversions. Source: Eyeview
- The average conversion rate for Landing Pages using video is 4.8%, compared to 2.9% for those who don’t. Source: Unbounce
4. Augmented Reality with Stable Diffusion
Coca-Cola worked with Timber and Ogilvy Mexico to create an immersive AR experience featuring up to 12 interactive stories. Each story involved a conflict resolved by sharing a Coke, reinforcing the brand’s association with happiness and harmony. The project involved detailed 3D development of characters and props, and the AR experiences were activated by customers globally, demonstrating the potential of AR in creating immersive and fun experiences.
Coca-Cola has effectively utilized augmented reality (AR) for marketing, creating engaging and interactive consumer experiences. One notable example is their collaboration with Ogilvy Mexico and VFX house Timber, where they developed an AR experience accessible through Coca-Cola’s app. In this experience, users can point their phone’s camera at a can of Coke to witness one of 12 animated stories come to life. These stories typically revolve around minor conflicts and conclude with characters resolving their differences by sharing a Coke and associating the brand with positive outcomes and social connections.
This news demonstrates Coca-Cola’s work with Ogilvy Mexico for interactive marketing with AR.
5. AI Creation with Crowd Sourcing
Coca-Cola Creations has been leveraging AI to create unique and immersive consumer experiences. One of their notable initiatives is the introducing of Coca-Cola® Y3000 Zero Sugar, a limited-edition flavor that was co-created using both human and artificial intelligence. This innovative approach involved understanding how fans envision the future through emotions, aspirations, colors, flavors, and more, blending these insights with AI to inspire the unique taste of Y3000.
Coca-Cola Creations also launched an AI-powered experience called “Destination Y3000” at the Las Vegas Sphere. This experience transformed the exterior of the Sphere with visually striking perspectives on what the year 3000 could look like, using AI-powered technology. This event projected visuals reflecting the latest Coca-Cola Creations drop onto the Sphere’s Exosphere, creating a futuristic cityscape inspired by the Y3000 AI Cam. This AI-powered camera allows fans to take photos of their surroundings and transform them into futuristic visuals. This vibrant visual tapestry also included images from a future-inspired capsule fashion collection designed in partnership with AMBUSH®, symbolizing the optimism enhanced by the power of technology.
An example of AI with Crowd-sourcing for Marketing.
6. Personalized AI Characters
Meta AI Studio helps users create customized characters as influencers or chat-friend. This is beyond a little marketing, but it is the art of animation, and novelist character creation touches real-life engagements.
Meta AI Studio introduces a universe of 28 unique AI characters, each with distinct personalities, mannerisms, and backstories. These characters are designed to feel like talking to familiar people, enhancing the user experience. To make these interactions more engaging, Meta has partnered with cultural icons and influencers who embody some of these AI characters, giving them profiles on Instagram and Facebook. This allows users to explore and interact with these AI characters, enhancing their digital experience.
Meta AI Studio with customized chat personalities.
In addition to these interactive features, Meta AI Studio focuses on building responsibly, ensuring the AI systems are designed for safe and responsible use. The custom AI models powering these text-based experiences, like Meta AI, are built on the foundation of Llama 2 and include safety measures tailored to specific features.
Coca-Cola partnered with Meta AI Studio to discuss this generative AI marketing methodology.
A Meta AI Chatbot Example is Albert Einstein. Imagine Albert Einstein’s GPT is merged with an Albert Einstein Hologram with Augmented Reality.
7. AI Influencers
Coca-Cola has not used AI influencers (influencers generated by AI) yet. But soon, every company will create its own AI Agents as influencers. Today, it is even possible to create AI Movies and AI characters, whether a chat friend, AI actor, or an AI influencer is only a few minutes away from us. Below is an AI influencer who creates a 7 figure business.
AI Influencer example is presented. Technically, this influencer does not have a gender; it is just AI-generated pixels.
Why Should You Start Creating Your Agent Armies?
You should start creating your Agent Armies for different solutions by incorporating them into each other as much as possible. One Agent can solve the issue of recognizing a plant, understanding and giving the side-effects of a drug, or giving you possible allergies that you can have according to your test results that come from a simple test kit from a pharmacy. Another agent can give you safer natural nutrients to replace a drug or possible diets to decrease allergic reactions.
Of course, according to the agent type, new regulations will be a subject. For example, Healthline started using Generative AI to answer health-related questions, which is directly competitive against Telehealth. Thus, the software is subject to many health consultancy-related legal regulations.
One person with Agent Army is equal to a company with 300 employees. You can assign one Agent Organization to one department, which communicates with another Agent Organization to solve complex problems. Only agent managers and engineers can easily manage Agent Orchestra. Entry-cost to the real business world never became more possible for creative, solution, and research minds.
What is a Brand Agent?
Brand-agent is a concept to explains how Brands can launch their agents to automate and scale their services with the help of GPT and API connections. Brand agents can charge their customers for different types of chatbot accesses utilized by custom LLMs and Datasets by the brand. For example, the Holistic SEO chatbot uses only our data to answer the SEO Questions with our model and dataset.
This brings us to the end of this long analysis of Generative AI for Business and Marketing trends in 2024.
There are 5 times more things to write here, but we will process all these improvements in 2024.
To explain the Generative AI SEO Trends in 2024, a separate article will be written, but my Budapest SEO Vibes speech and Saigon SEO Mastery Summit, Serpconf, already explained the future of SEO.
“Print websites that print money” and “Verbalize a Knowledge” are two quotes from my speeches during 2023 that would summarize everything for the future of Programmatic and Generative SEO. All these speeches will be added to the Topical Authority Course.
The End of SaaS and Beginning of Agents as Solutions
In 2024, SaaS will be a hard year if anyone can copy and re-produce your well-designed product in weeks. This will increase competitiveness, which requires understanding the Data-Model-Marketing components of the future of business. Focus on Business and AI as much as you focus on Search Engine Optimization to stay in the game and grow in life.
Love you all.
Stay with research, logic, and science.
Koray Tugberk GUBUR — Pioneer in Holistic SEO Mindset
7 January 2024, 7:59 on GMT +3
