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AI In Marketing: Why GenAI Should Be in All 2024 Marketing Plans?

Have you ever engaged yourself in Avatars and virtual influencers? Have you come across AI-generated videos or AI-generated content?

Yes, there you are!

Welcome, to the world of AI in Marketing!

Reap the content, client, and ops benefits of AI in marketing! It’s a Whole New World Out There.


  • What Is AI Marketing?
  • Top 10 Ways To Incorporate AI In Your Marketing Strategy
  • Examples of AI In Marketing- Use Cases
  • Vendor Companies- AI In Marketing
  • Top 20 AI Tools In Marketing
  • Exclusive Commentary
  • How Marketers Can Use AI to Increase Sales and Improve Consumer Experience?
  • What Are The Kinds Of Marketing AI?
  • AI In Marketing Pros
  • AI In Marketing Cons
  • Why Generative AI Should Be in All 2024 Marketing Plans?
  • Future of AI Marketing
  • FAQ’s
  • Conclusion

What Is AI Marketing? 

Three aspects of marketing and sales could be affected by the rise of AI, especially gen AI: customer experience (CX), growth, and productivity.

AI marketing uses data models, algorithms, and machine learning to generate customer insights that marketers may utilize to optimize spending, customize content, and personalize the customer journey. Chatbots, picture recognition, personal assistants (Google Assistant, Amazon Alexa, Microsoft’s Cortana, and Apple’s Siri), recommendation engines, search-based advertising, and dynamic pricing on ecommerce sites are AI marketing solutions.

McKinsey research found that 90 percent of commercial leaders expect to utilize gen AI solutions “often” over the next two years.

In customer experience (CX), for instance, a customer’s identity, past purchases, and behavior might inform hyper-personalized information and offers. By providing salespeople with the correct analytics and consumer insights to capture demand, AI may expedite growth by jumpingstarting top-line performance. Furthermore, AI has the potential to improve sales performance and effectiveness by automating and offloading several repetitive sales tasks. This will allow salespeople to spend more time engaging with clients and potential customers, which in turn will reduce the cost of service. Customization is major in all these endeavors. B2C can now leverage personalization through customized marketing and sales services, made possible by AI paired with company-specific data and context, which enables consumer insights at the most granular level. Success in business-to-business marketing requires going above and beyond account-based marketing and making heavy use of hyper-personalization.


Top 10 Ways To Incorporate AI In Your Marketing Strategy

McKinsey research indicates that players who invest in AI are seeing a revenue uplift of 3 to 15 % and a sales ROI uplift of 10 to 20 %.

1. Data Analysis: Automating the collection and analysis of large volumes of marketing data from different campaigns and programs, eliminating the need for manual sorting.

2. Content Generation: AI generates both short and long-form content for marketing purposes, including video captions, email subject lines, web copy, blogs, and more. Natural Language Processing (NLP): Utilising AI to generate human-like language for content creation, customer service bots, personalized experiences, and more.

3. Media Buying: Predicting a business’s most effective advertisement and media placements, maximizing the return on investment (ROI) of marketing strategies while reaching the target audience.

4. Real-time Personalisation: Modifying a customer’s experience with marketing assets, such as web pages, social media posts, or emails, to align with their past preferences and encourage specific actions, such as clicking a link, signing up, or purchasing.

5. Natural Language Processing (NLP): Utilising AI to generate human-like language for content creation, customer service bots, personalized experiences, and more.

6. Automated Decision-Making: Assisting businesses in deciding which marketing or business growth strategies to employ based on historical or external data inputs.

7. Predictive Analytics: Predictive analytics powered by AI helps marketers forecast future trends and customer behaviors. By analyzing historical data, AI can identify patterns and predict outcomes, enabling businesses to make informed decisions about product launches, inventory management, and marketing strategies.

8. Optimizing Ad Campaigns: AI enhances the effectiveness of advertising campaigns through programmatic advertising, which uses AI to buy ad space automatically, targeting the right audience at the right time with the right message. AI analyzes data in real-time to adjust bids, choose the best platforms, and optimize ad placements, leading to better performance and cost efficiency.

9. Voice and Visual Search: AI-powered voice and visual search technologies are changing how consumers find products. With voice search becoming more prevalent due to smart speakers and virtual assistants, marketers need to optimize their content for voice queries. Similarly, visual search allows users to search using images instead of text, necessitating the optimization of visual content to be discoverable in such searches.

10. ChatBots: CMOs should be realistic about promoting AI’s current capabilities despite its great potential. Despite the hype, AI can only execute specialized tasks and cannot oversee a marketing organization. Its powers are growing swiftly, but it already assists marketers and is even essential for some marketing initiatives. AI will transform marketing, even if it takes decades. The marketing function and its support teams, especially IT, should prioritize AI development and risk mitigation. Marketers should start planning today to maximize AI’s current and future possibilities.

Examples of AI In Marketing- Use Cases

 Customer satisfaction is expected to grow by 25% in 2023 within organizations that use AI according to Gartner research.


PayPal used to periodically check for active users and classify inactive accounts as churned.This strategy is flawed because customers who become active soon after the checks are run are less likely to be won back by the following one. The model used historical churn data and important data points to predict early churn. With this data, marketing teams may act faster and with more focused, personalized content. So, PayPal lowered churn and cut the time needed to study a subset of users from 6 hours to 30 minutes.


Netflix CEO Ted Sarandos was forthright about using user data to make content production decisions when the business started original programming. Netflix produces content the same way as House of Cards and Orange is the New Black, over a decade ago. Because Netflix makes nearly all of its money from subscribers, making exclusive content to increase signups maybe its best marketing strategy.


Social media conversations are unpredictable and can conclude fast. It detects micro-trends from billions of internet discussions in real-time. Cross-referencing them with Mastercard’s interests like travel and entertainment ensures it targets relevant trends. After finding a good fit before peaking, it tells the marketing team, who determine whether to engage. If they engage, they can use their backlog of content and strategically use social media and targeted marketing. Mastercard and a national airline promoted a local tourist destination. The campaign increased click-through and engagement rates by 37% and 43%, respectively, while lowering cost per click and engagement by 29% and 32%.

Vendor Companies- AI In Marketing

Top 20 AI Tools In Marketing

Understand the sorts of AI marketing tools needed and the potential overlap with your martech stack before choosing one. Clear user stories and the AI solution’s ability to interface with existing technologies and gain stakeholder adoption can aid your inquiry. Finally, compare AI solution providers’ main competencies.

  1. Jasper AI (for copywriting)
  2. Lexica Art (for blog thumbnails)
  3. Surfer SEO (for SEO content writing)
  4. Notion AI (for productivity)
  5. Content at Scale (for generating SEO blog posts)
  6. Originality AI (for AI content detection)
  7. (content writing for teams)
  8. Undetectable AI (for rewriting AI content)
  9. FullStory (for digital experiences)
  10. Zapier (for automating tasks)
  11. Hemingway app (for content editing)
  12. Chatfuel (for chatbots)
  13. Grammarly (for content editing)
  14. (for digital advertising)
  15. Headlime (for landing pages)
  16. (conversation management)
  17. Browse AI (for scarping web pages)
  18. Algolia (for search and recommendation APIs)
  19. PhotoRoom (for removing image backgrounds)
  20.’s AI Sales Email Assistant (for email replies)

Exclusive Commentary

We had exclusive commentary from one of our AiThority guest in his byline from VP, AI Integrations & Emerging Tech at Merkle

1. Improve Customer Experience and Customer Satisfaction

Many brands are keenly focused on delivering a better customer experience, but the reality is that it is hard and time-consuming to deliver the right message at the right time at scale across channels.

Artificial intelligence’s exceptional abilities in data analysis and pattern recognition will revolutionize personalized marketing. By employing AI, brands will be able to analyze consumer behavior, preferences, and purchase history, allowing for tailored marketing strategies for each individual. This level of hyper-personalization will go beyond mere product recommendations and extend to personalized advertising, content, and even customer service interactions.

2. Employee Productivity

In the design process, AI will help create content like text, video, and images quickly with text-to-image capabilities. Further, marketing tools will have native features to create variants and speed up A/B testing.  AI assistants will complement, support, take the guesswork out, and provide suggested paths to utilize.

3. Operational Efficiencies

AI will streamline various marketing processes, from automated customer segmentation to predictive analytics for demand forecasting. This will lead to not only more targeted marketing campaigns but also substantial cost savings and improved ROI. Marketing assistants with chat-type natural language prompting will be everywhere to support marketers and make available their time for more advanced tasks.

How Marketers Can Use AI to Increase Sales and Improve Consumer Experience?

  1. Setting goals and expectations is the first step to using AI in marketing. Assess past campaigns’ successes and failures and suggest how AI might improve future results. After stakeholders agree, choosing an AI system and setting meaningful KPIs will be easier.
  2. Data scientists and engineers with AI, machine learning, and deep learning backgrounds are rarely on marketing teams, yet they are needed for AI marketing success. Organizations can engage data scientists and engineers or pay a third-party partner to train and manage their AI marketing tool to address this issue. Both approaches offer pros and cons, mostly according to an organization’s investment level.’
  3. AI marketing solutions struggle to leverage client data for training and implementation without infringing privacy restrictions. Organizations must protect consumer privacy and security during training or face steep fines.
  4. Training data must be accurate and relevant for an AI marketing tool to succeed. AI solutions educated on data that doesn’t accurately reflect customer intentions won’t deliver relevant customer behavior insights or strategic recommendations. Enterprises may ensure their AI solutions help them reach marketing program goals by addressing data quality.
  5. Organizations choosing an AI solution have several platforms and capabilities. If they followed the previous four steps—setting goals, hiring the proper people, and assuring data quality and accuracy—the last step—picking the correct tool—should be easy.

What Are The Kinds Of Marketing AI?

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The Four Kinds of Marketing AI. Categorizing potential applications according to their intelligence level and whether they are isolated or are integrated into broader platforms can help companies plan the rollout of their marketing AI. These two dimensions combine to create four types of AI. 1: Less advanced, isolated AI. This category comprises stand-alone task-automation apps, such as basic consumer service chatbots—for example, Facebook Messenger bots—and email automation systems. 2: Less advanced, integrated AI. This category comprises integrated task-automation apps, such as inbound customer call routing and CRM-linked marketing automation systems. 3: More advanced, isolated AI. This category comprises stand-alone machine-learning apps, such as Olay’s Skin Advisor, Behr’s color-discovery app, and Vee24’s chatbot. 4: More advanced, integrated AI. This category comprises integrated machine-learning apps, such as predictive sales-lead scoring in CRM, CRM-based sales coaching, E-commerce product recommendations, and programmatic digital ad buying. Simple stand-alone apps are a good place to begin because they’re easier to set up, but their benefits are limited. Once companies acquire AI skills and amass data, they can add apps that are more advanced and are part of other platforms, working their way up to integrated machine learning, which has the potential to create the most value.


AI In Marketing Pros 

  • Faster, smarter decision-making: Marketing teams using cutting-edge AI solutions may monitor their marketing activities in real-time and alter their strategies. AI marketing solutions use ML algorithms to construct AI marketing strategies, evaluate data faster than humans, and recommend actions based on sentiment analysis from past customer data.
  • AI marketing technologies can help marketers find meaningful insights from campaign data in real-time, improving marketing ROI. The same techniques can also determine the best media buy channels and ad placement depending on customer behavior. Modern AI marketing tools assist stakeholders maximize campaign ROI.
  • Digital campaigns generate more data than people can handle, making marketing success measurement challenging. Marketers can use AI-enhanced dashboards to track the success of their tactics and identify areas for improvement.
  • AI technologies automate typical CRM processes like customer data preparation, helping marketing teams improve their CRM systems. They can also identify at-risk customers, decrease human error, and tailor customer messages.
  • Customers’ data can provide more valuable insights: Many marketers struggle to plan campaigns with the amount of data accessible. AI can predict customer data using rapid, effective ML algorithms to analyze massive amounts in seconds. It predicts customer behavior, suggests personalized content and finds trends in massive data sets for marketers.

AI In Marketing Cons

  • AI-training solutions: AI needs extensive training to learn new tasks, just like humans. For instance, you must spend time and money training an AI system to engage customers. An application like this requires a lot of customer preference data and possibly data scientists trained in this type of training.
  • Monitoring data quality and accuracy: AI solutions are only as good as their training data. Any tool, no matter how powerful, will produce poor results and unproductive decisions if its training data is inaccurate and representative.
  • AI is educated on confidential customer data, so privacy laws must be respected. Companies using AI for marketing must comply with consumer data regulations or risk fines and reputational damage.
  • Facilitating staff AI marketing uptake is difficult. While ROI and efficiency are easy to assess, showing how AI affects customer experience and brand reputation requires the correct tools. Digital marketing teams should educate corporate stakeholders about AI marketing initiatives and train and enable employees to use them.
  • Initial AI marketing deployment best practices are still evolving because the tool is new. Digital marketers must evaluate AI marketing methods’ long-term implications as well as their short-term rewards. Marketers can help build best practices and assure AI inclusion by sharing expertise and remaining current.

Why Generative AI Should Be in All 2024 Marketing Plans?

We had exclusive guest post insights from Richard. 

Today, 55% say they need to add new skills and knowledge at least monthly.

As businesses develop their budgets and reassess their objectives for 2024, marketing departments must build GenAI into their marketing plans. I often say effective digital transformation is 90% people and 10% tech, meaning brand leaders must also invest in complementary, ongoing employee GenAI training programs that span strategy, planning, implementation, measurement, reporting and evaluation.

The day when GenAI-fueled marketing is simply the ‘everyday’, is coming into sharp focus. And, when it comes to marketers, their digital skills will need to be razor sharp, able to move beyond isolated tactical executions to create more strategic solutions, where GenAI is fueling individual professional development and business growth.

In time GenAI will become a key strategic instrument for making, augmenting, optimizing, accelerating, iterating and innovating marketing in ways we are only beginning to think of and visualize today. As marketers uncover these opportunities, GenAI’s potential to be the golden thread that drives forward strategic marketing outcomes will only grow. From a buzzword in 2023 to a key strategic pillar in 2024, GenAI considerations are essential to your marketing plans for the coming year and beyond.

Future of AI in Marketing

The marketing industry stands to gain the most from artificial intelligence, according to a 2018 McKinsey study of 400+ advanced use cases.

We encourage chief marketing officers to be realistic about the present capabilities of marketing AI, despite its huge potential. Despite all the talk, AI is still only capable of performing very specific tasks; it cannot manage a full marketing operation. Its capabilities are expanding quickly, but it is already providing significant benefits to marketers and is even critical for some marketing efforts. Even if it may take decades, we are certain that AI will revolutionize marketing in the end. Building AI capabilities and resolving any dangers should be a long-term focus for the marketing function and the teams that support it, especially IT. To make the most of AI’s present and future capabilities, marketers should begin formulating a plan today.

Our progress shows that these attributions to the marketing industry are nothing new and that AI advancements are still needed to meet the long-awaited need for increased personalization, cross-channel integration, and dynamic customer engagement. Marketers still seek better ways to interact with consumers. Industry progress remains unequal, with only larger, more advanced organizations having the skills and means to integrate basic AI infrastructure into their marketing efforts.

Marketing and AI development are needed to find the proper prospects. In the future years, AI marketing will present new opportunities and problems. Marketers could see interesting advances in the next decade, and from what we know and utilize today, both industries could undergo a revolution.


  • What is predictive analytics in marketing?

Predictive analytics uses historical data, machine learning, and statistical algorithms to predict future outcomes, such as customer behavior, allowing marketers to make data-driven decisions.

  • Can AI personalize marketing campaigns?

Yes, AI can personalize marketing campaigns by analyzing individual customer data to deliver tailored content, product recommendations, and offers that align with each customer’s preferences and behavior.

  • What role do chatbots play in marketing?

Chatbots play a role in marketing by providing i****** customer service, engaging with customers in real-time, collecting data, and guiding customers through the sales funnel, all while improving user experience.

  • How does AI enhance content creation?

AI enhances content creation by generating personalized content, optimizing headlines and topics for SEO, and even creating initial drafts for articles or social media posts using natural language processing.

  • What is programmatic advertising?

Programmatic advertising is the automated buying and selling of online advertising space using AI algorithms to target specific audiences with precision, improving the efficiency and effectiveness of ad campaigns.

  • How does AI aid in sentiment analysis?

AI aids in sentiment analysis by analyzing social media posts, reviews, and other online content to gauge public sentiment towards a brand or product, helping marketers understand and respond to customer feelings and attitudes.

  • What are recommendation engines?

Recommendation engines are AI systems that analyze user data to suggest products, services, or content that users are likely to be interested in, enhancing customer experience and boosting sales.

  • How can AI optimize email marketing?

AI optimizes email marketing by personalizing email content, segmenting email lists, predicting the best times to send emails, and analyzing campaign performance to continually improve results.

  • How can small businesses benefit from AI in marketing?

Small businesses can benefit from AI in marketing by using affordable AI tools to automate tasks, gain insights from data, personalize customer interactions, and compete more effectively with larger companies.

  • Is AI in marketing expensive?

While some AI tools can be costly, there are many affordable options available. The cost of AI in marketing varies depending on the specific tools and the scale of implementation, but the ROI can justify the investment through increased efficiency and effectiveness.


Rapid advancements in artificial intelligence make it difficult to foresee how this game-changing technology will influence advertising and commerce in the years to come. Using gen AI to optimize their operations, leading players in the area are capitalizing on advancements in personalization and internal sales excellence.

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