As the popularity of AI tools such as ChatGPT and DALL-E grow, business executives have started looking at ways to leverage AI in their business operations. But while the hype around artificial intelligence (AI) is relatively recent, smart marketers have been adopting artificial intelligence in their marketing efforts for years.
From Amazon pioneering collaborative filtering to improve the customer experience in 1998 to Google implementing complex algorithms to provide users with relevant and valuable information, machine learning and AI tech have had a close association with marketing and sales from the beginning.
AI technology is a polarizing topic — some people think that it will completely revolutionize how organizations operate, while others are fearful that completely removing the human touch will do more harm than good.
The truth is likely somewhere in the middle; AI adoption is growing, but understanding the true capabilities of AI-powered solutions is essential to tempering expectations and making the most out of the technology.
In this article, we offer a comprehensive overview of artificial intelligence stats and how marketers can adopt AI in specific use cases. These statistics provide insight into current and future AI market trends and how the technology is set to transform the marketing industry in the coming years.
- Notable AI Marketing Statistics
- Market Overview of the AI Industry in 2023
- How Marketers Perceive Artificial Intelligence (AI)
- AI Use Cases in the Marketing Industry
- The Benefits of Using AI in Marketing
- The Challenges of Using AI in Marketing
- The Future of Marketing AI Technology in Advertising
- Final Thoughts
Notable AI Marketing Statistics
- 28% of top-performing companies use AI for marketing purposes. (Forbes)
- Only 15% of content marketers plan to use AI in the next year. (Content Marketing Institute)
- 64% of marketing businesses use AI technologies in their toolkits. (Salesforce)
- 40% of infrastructure and operations teams at large organizations plan to use AI-augmented automation to free IT departments from routine tasks (McKinsey).
- Using AI voice assistants can reduce call times by up to 70%. (Gartner)
- 84% of digital marketing professionals believe that using AI can provide clients with real-time, personalized experiences that drive sales and increase revenue. (Salesforce)
- Companies that implement AI marketing tools can see a 451% increase in qualified leads. (Salesforce)
Market Overview of the AI Industry in 2023
Artificial intelligence (AI) and machine learning (ML) are hot topics, and many businesses have begun incorporating AI into their normal operations, leading to accelerated artificial intelligence growth.
Here are some global artificial intelligence statistics that showcase how AI technology is poised to explode in the coming five years.
Global AI Market Growth
AI market revenue has increased dramatically since 2018 and is set to increase to $500 billion in 2024, according to market research firm IDC. This accelerating trend is mainly due to the adoption of AI in many end-user sectors, including the wearable AI market, which is expected to be worth $180 billion in 2025.
Another research firm, Precedence, suggests that this number will rise to $1.5 trillion in 2030, with an estimated compound annual growth rate of 38.1% from 2022 to 2030.
The largest market share for AI is currently software, and the need for AI platforms continues to increase. According to a 2022 report by Leftronic, AI software platforms will focus on tools and API frameworks and will continue to dominate the AI market. The report also predicts that AI software will encompass about 40% of all cognitive and AI expenditures for the next five years.
|wdt_ID||Market Overview of the AI Industry in 2023||Value|
|1||Global AI Market Growth|
|2||Year||Revenue (in billions USD)|
|6||Wearable AI Market (2025)||180|
Number of Machine Learning Platforms
Open AI, the developer of ChatGPT and DALL-E, is the most funded machine learning operations platform in 2022, with a market value of over $1 billion, according to Statista’s findings.
The second-most funded platform has a value of $600 million, and the top ten AI companies in the industry all have valuations of over $100 million.
|wdt_ID||Number of Machine Learning Platforms||Market Value (in USD)|
|2||Open AI||1 billion|
|3||Second-Most Funded Platform||600 million|
|4||Top 10 AI Companies||Valuation > 100 million|
AI Adoption in Global Organizations
According to the 2021 McKinsey report on the state of AI, service operations and product development make up the bulk of AI-based operations, with marketing and sales coming in third place.
However, according to a 2023 Precedence study, the advertising and media segment has gained the largest end-user market share of AI adopters, leading to a dominance of marketing in the global AI market.
The healthcare segment is poised to overtake marketing in AI adoption statistics due to the rising penetration of telehealth platforms, electronic health records, and virtual digital voice assistants.
A 2020 global survey of 570 companies by EY reveals that the companies best poised to respond to disruption and improve financial performance are those that invest heavily in digitization and AI acceleration.
These findings were consistent across sectors, including financial services, health, hospitality, and telecoms, showcasing how the transition to digital systems can benefit many organizations, regardless of sector or size.
|wdt_ID||AI Adoption in Global Organizations||Ranking|
|4||Advertising and Media||3|
|5||Healthcare||Poised to overtake|
AI Corporate Investment
AI investment saw a massive jump in the past five years, with corporate investments rising from approximately $10 billion in 2018 to $94 billion in 2022, as per Statista’s data study.
The reason for this huge jump in corporate interest is a shift in perception. According to a 2020 MIT Sloan Management report, approximately 87% of global organizations believe that using AI correctly will give them a competitive edge in the global economy, compared to 75% in 2019.
As AI increases in market size and sophistication, more companies will make the digital transition and invest more heavily in AI development and implementation across a variety of sectors.
|wdt_ID||AI Corporate Investment||Investment (in billions)|
|4||AI Investment Perception Shift|
|8||AI Expenditures by Category|
|10||AI Software Platforms||40%|
How Marketers Perceive Artificial Intelligence (AI)
Marketers are some of the most enthusiastic proponents of machine learning and artificial intelligence. According to a 2020 SalesForce State of Marketing report, approximately 84% of marketers say they use AI in a marketing and sales function, and 70% claim to have a fully-defined AI strategy for the future.
The same report found that many high-performing marketing teams average seven uses of AI services in their daily operations. Approximately 52% of these teams also plan to increase their AI adoption rate in the next year.
The 2018 Drift and Marketing Artificial Intelligence report revealed how marketers that have already implemented AI technologies feel about their expertise.
Approximately 17% said they were in the scaling phase of AI adoption, where they have started using artificial intelligence regularly as part of their mainstream technology use, and 19% said they had entered the humanizing phase, where human marketing teams and AI work almost seamlessly to deliver results.
The same report showed that nearly half of the surveyed marketers felt they were beginners at using AI terminology and services, while 37% considered themselves intermediate. Similarly, 40% of marketers felt relatively confident about their ability to evaluate marketing automation and AI services, while 24% felt they needed more training.
AI Use Cases in the Marketing Industry
Marketers anticipate that accelerating AI trends and improved AI capabilities will bring new opportunities to assist organizations in their sales and marketing function.
Even now, many digital marketing leaders have started using marketing automation, and data shows emerging technologies are already providing exciting returns on AI solutions. From better customer service to deep learning analytics, AI-powered applications can improve marketing efforts in a variety of ways.
The following 2022 breakdown from Statista shows some of the most common ways marketers have blended marketing automation and AI for routine tasks and more complex marketing strategies:
- Paid advertising (32%)
- Email message/offer personalization (32%)
- Product or content recommendations (22%)
- Email subject line personalization (22%)
- Predictive analytics (18%)
- Account identification (18%)
- Chatbots (16%)
- Campaign or ad deployment scheduling (16%)
- Segmentation (12%)
Enhanced Email Marketing
Email marketing is already one of the best marketing investments available, with an average ROI of $36 per dollar spent. It’s also one of the most popular targets for automation — a report by Leftronic shows that 87% of businesses that had implemented an AI strategy used it to boost email marketing.
According to Business Wire, implementing AI tools to automate email marketing can further improve its effectiveness. Email marketing revenue is 41% higher in companies that use AI and generate more revenue per subscriber when compared to organizations that have limited AI services in place.
AI use also led to higher subscriber engagement, with open and click-through rates being two points higher for AI senders than companies that relied solely on human marketers.
Many companies use artificial intelligence (AI) as a way to automate routine tasks, freeing up teams for more complex roles.
According to Ascend2 and Research Partners, email marketing and social media management remain the top areas where marketing artificial intelligence dominates, but paid ads, campaign tracking, SMS marketing, and push notifications have become popular targets for automation strategies and have an increasing AI usage percentage as well.
According to Forrester, 70% of enterprises plan to implement AI for automation purposes in their business processes within the next 12 months.
Marketers have used chatbots for several years as virtual assistants and to assist sales leaders in their sales function. According to Accenture, 43% of companies interviewed report that their competitors have already implemented chatbots as part of their digital transformation. Furthermore, 57% of organizations believe that chatbots can deliver a large ROI for minimal investment.
According to Juniper Research, chatbot adoption can result in cost savings of up to $11 billion per year in the banking, retail, and healthcare sectors, up from $6 billion in 2018. While many organizations use chatbots primarily in their IT departments, 20% have implemented chatbots and virtual assistants in their customer service departments and 16% in their sales departments.
Many marketers already use AI automation in social media to schedule posts and gather data for analytics, but artificial intelligence statistics show that AI can do so much more.
Digital innovation, such as using AI to personalize social feeds, changing the appearance of users using facial recognition, and sentiment analysis of customer posts, offers a new arsenal of tools to fully take advantage of the power of social media marketing. According to MarketsandMarkets, the AI market size in social media is set to grow to $2.2 billion in 2023, with a compound annual growth rate of 28.3%.
Advances in AI technology, such as natural language processing, deep learning, and natural language generation, have made creating SEO-friendly content easier than ever.
While we’re not at the point where artificial intelligence and natural language processing can write high-quality articles automatically, a few promising proofs show that AI technologies can enhance content marketing through:
- Automated keyword research
- Testing landing pages
- Optimizing and personalizing content
- Reviewing customer data and analytics to further hone targeted content
The Benefits of Using AI in Marketing
With growing interest in artificial intelligence (AI) for marketing automation, sales leaders and marketers have to carefully weigh up the advantages of implementation versus the challenges that may lead to increased costs and failed AI projects.
While 56% of B2C customers expect brands to tailor their customer journey and interactions, 47% say that current interactions do not align with their preferences. Marketing personalization remains a challenge, with 63% of digital marketing experts saying that they struggle with customer experience personalization, as per to Gartner.
Machine learning, data capture, and data analysis tools can all assist with creating hyper-focused, personalized experiences for all customers. According to IBM, 71% of customers want to communicate with brands in real time, which has led to the rise of chatbots, voice assistants, and other artificial intelligence solutions.
Many organizations have started implementing artificial intelligence to generate revenue. The top earner for these efforts is marketing and sales, followed closely by finance and supply-chain management. According to McKinsey AI marketing statistics, several companies attributed a 20% increase in revenue to AI. Approximately 10% of respondents said they saw a 10% increase in earnings, while 26% reported more modest returns.
Companies are constantly seeking to reduce costs, and one of the most promising ways is through AI. According to machine learning statistics from McKinsey, 13% of respondents said that costs declined by 10% to 20% after implementing machine learning solutions, while 2% of companies saw cost reductions of more than 20%.
Customers generate huge amounts of data during the customer journey, and many marketing channels are providing increasingly complex information streams. According to Salesforce, marketers foresee up to 50% more data from customers than in previous years, and making sense of this information requires novel solutions.
Increased Sales and Consumer Retention
While AI is incredibly useful in marketing, it’s also an invaluable tool for sales departments. Gartner reports that at least 30% of B2B companies use AI for a primary sales process. Many sales leaders estimate that their AI use will rise by 155% in the coming years, and 54% of respondents said they expected to adopt at least one new AI technology in the next year.
What is also exciting is how AI encourages further collaboration between marketing and sales. As stated by Salesforce, many marketers use automation to increase sales and customer retention and to create successful new product launches. Similarly, 21% of sales leads take advantage of collaborative AI applications with their marketing departments.
The Challenges of Using AI in Marketing
While the AI market size continues to grow, and AI statistics show increasing acceptance of the technology, several barriers prevent wider-scale adoption across the global AI market.
Risk and Governance Concerns
According to Statista, 35% of professionals using AI technology in their workplace are concerned about risk and governance issues arising from using these cutting-edge technologies.
From a customer data perspective, 74% of respondents from a 2022 Statista survey stated that they were concerned about privacy and tracking. Fewer than a quarter of respondents said they understood how brands use their personal data to target them with focused, hyper-relevant online ads.
As governments across the globe start implementing more restrictive privacy policies, marketers will need to be cautious about how they use artificial intelligence and marketing automation in data collection and analysis.
Education and Training
The number one barrier to full-scale adoption, according to the 2022 Drift State of Marketing AI report, is a lack of education and training. Over 70% of respondents felt this was the main barrier in their workplace, despite 40% feeling relatively confident in evaluating current marketing AI strategies.
Only 14% of respondents felt that their organization had any formal artificial intelligence (AI) or machine learning training, while 16% expressed reluctance and fear of AI as an additional barrier.
Difficulty Deploying and Using Artificial Intelligence
The 2022 McKinsey survey on AI adoption shows that many of the perceived barriers were organizational and resulted in difficulty deploying and using AI solutions. The more common barriers included:
- Lack of clear AI strategy
- Functional silos that constrain whole-organization AI implementation
- Lack of leader ownership of AI
- Lack of technical infrastructure for AI implementation
This implies that a large part of AI implementation in the organization depends on how far the company is in its digitization journey. Organizations that have followed AI industry statistics and have digitized core business processes are better suited to embed AI throughout their operations.
According to Statista, another potential hurdle to wide-scale artificial intelligence adoption is cost. Over 30% of marketing professionals identified machine learning and AI costs as challenging, while another 31% stated that current implementations were too difficult to use.
AI Replacing Jobs
A common concern voiced by AI detractors is that of artificial intelligence replacing human workers, especially in jobs that have many easily automatable tasks. The World Economic Forum estimates that globally, AI and other automation technologies could replace 85 million jobs in the next five years.
However, in companies that have adopted AI strategies, AI marketing statistics show the opposite is more often true. According to the McKinsey report, many of the most digitized companies say they expect the effect of AI on headcount to be minor or positive.
In fact, 31% of respondents in digitalized companies are optimistic that their workforce will grow significantly in the future, as opposed to 18% in less-automated companies. Combined with AI statistics from other McKinsey studies, this suggests that AI will not replace jobs but will transform the work people perform in their roles, especially in marketing and the retail industry.
The Future of Marketing AI Technology in Advertising
Organizations are starting to realize that AI and automation are here to stay and can offer competitive benefits for marketing and other operations. By looking at current AI marketing statistics, businesses can identify prospective trends, and early adoption may mean the difference between success and failure.
According to Gartner, 40% of large business infrastructure and operations teams are planning to implement automation solutions for many processes, including marketing. Many of these implementations will take advantage of “augmented intelligence” that fosters collaboration between humans and AI to improve cognitive performance and reduce the need for humans to perform routine tasks.
A report by Genpact suggests that now is the perfect time to start a transition to AI systems. The report estimates that businesses using AI will be 10 times more productive and have double the market share of organizations that don’t by as soon as 2025. The report recommends several steps to accelerate AI implementation, including:
- Prioritizing AI as part of the corporate strategy
- Creating a reliable data foundation at the core of the business
- Combining industry expertise with digital skills
- Embedding AI in routine business operations
- Continually scaling and refining AI implementation across the organization
The transition to automation using AI and machine learning has already begun and has had a massive impact on how companies run their businesses. AI and automation affect every aspect of marketing, from content writing to SEO tools and customer data analysis.
Voice assistants can reduce call times while improving customer experience, and automation tools for email and SMS marketing have become almost ubiquitous.
Marketers are well-placed to start adopting AI in their roles. Most understand the digital marketing landscape and have worked with algorithms daily. They are comfortable with rapid changes and can adapt quickly to take advantage of shifting digital landscapes.
One of the earliest examples of machine learning and algorithms was from Amazon, which used AI to identify shoppers’ likes and dislikes and recommend them products based on their preferences.
While AI presents unique challenges, these AI advertising statistics should show that it also provides exciting opportunities. The future of AI in advertising is guaranteed, and the only question is how marketers will take advantage of the opportunities it provides.