2021 State of Marketing AI Report

A Letter from Paul Roetzer, Founder & CEO, Marketing AI Institute

Your life is AI-assisted, and your marketing will be too.

Artificial intelligence is forecasted to have trillions of dollars of annual impact on businesses and the economy, yet many marketers struggle to understand what it is and how to apply it to their marketing.

As the amount of consumer data exponentially increases, marketers’ ability to filter through the noise and turn information into actionable intelligence remains limited.

At the same time, much of the automation technology marketers rely on today is elementary, and, ironically, largely manual.

But, AI possesses the power to change everything.

Demis Hassabis, Co-Founder and CEO of Google DeepMind, defines AI as, “the science of making machines smart,” which in turn augments human knowledge and capabilities.

To take inspiration from Hassabis, I have come to define marketing AI as the science of making marketing smart.

With AI, marketers are able to reduce costs by intelligently automating data-driven and repetitive tasks, and accelerate revenue by improving their ability to make predictions at scale.

Traditional marketing technology is built on algorithms in which humans code sets of instructions that tell machines what to do. With AI, the machine has the potential to define its own algorithms, determine new paths, and unlock unlimited potential to transform marketing.

AI may seem like a futuristic concept, but you use it dozens, if not hundreds, of times everyday, most likely without knowing it. Major brands such Amazon, Facebook, Google, Microsoft, Apple, and Netflix are powered by AI technologies including: machine learning, deep learning, computer vision, speech and image recognition, natural language processing, and natural language generation.

While AI has been transforming other industries and redefining how we learn, communicate and live as consumers, we have not seen the same volume and velocity of AI innovations in marketing, until now.

Massive amounts of data, exponential growth in computing power, and the availability of AI from leading technology companies have combined with a flood of venture capital money to prime the marketing industry for disruption. Many time-intensive, data-driven tasks commonly performed by marketers are being augmented, and, in some cases, replaced, by AI.

The marketers who take action have the opportunity to create a significant and sustained competitive advantage for their businesses and themselves. AI enables marketers to:

• Accelerate revenue growth
• Create personalized consumer experiences at scale
• Drive costs down
• Generate greater ROI on campaigns
• Get more actionable insights from marketing data
• Predict consumer needs and behaviors with greater accuracy
• Reduce time spent on repetitive, data-driven tasks
• Shorten the sales cycle
• Unlock greater value from marketing technologies

The 2021 State of Marketing AI Report establishes industry benchmarks for understanding and adoption of artificial intelligence. It also offers a glimpse into a near-term future in which marketers and machines work together seamlessly to run personalized campaigns of unprecedented complexity, with unimaginable simplicity.

While AI-powered marketing technologies may never achieve the sci-fi vision of self-running, self-improving autonomous systems, a little bit of AI in marketing can go a long way to dramatically increasing productivity, efficiency, and performance.

Rather than fearing AI, marketers must embrace it. AI can be a competitive advantage. It can give marketers superpowers.

It is time to discover yours.

Paul Roetzer
Founder & CEO, Marketing AI Institute

Marketers see an intelligently automated future in marketing AI, but understanding and adoption are slow to take hold.

While the total numbers vary, every major report on artificial intelligence seemingly agrees that its annual financial impact will be in the trillions.

• McKinsey Global Institute estimates up to a $5.9 trillion annual impact of AI and other analytics on marketing and sales.
• PwC sees a truly global effect from AI, with an estimated 14 percent lift in global GDP possible by 2030, a total contribution of $15.7 trillion to the world economy, thanks to both increased productivity and increased consumption.
• In 2021 alone, Gartner projects AI augmentation will create $2.9 trillion of business value, and 6.2 billion hours of worker productivity globally.
• IDC states that efficiencies driven by AI in CRM could increase global revenues by $1.1 trillion this year, and ultimately lead to more than 800,000 net-new jobs, surpassing those lost to automation.
• The COVID-19 pandemic has accelerated AI-powered digital transformation across businesses. Additional research from McKinsey cites that 25 percent of almost 2,400 business leaders surveyed said they increased AI adoption due to the pandemic.

But, what does this all really mean for marketers?

• How will AI impact brands?
• How will marketing jobs evolve?
• What are the most valued marketing AI use cases?
• How many marketing tasks will be intelligently automated?
• What impact will marketing AI have on accelerating revenue growth and reducing costs?
• Are marketing teams ready for AI-powered digital transformation?

These are just a few of the questions we set out to answer with the 2021 State of Marketing AI Report.

Marketing AI Institute and Drift teamed up in fall 2020 to gain unparalleled insights into the awareness, understanding, and adoption of AI throughout the marketing industry.

Using Marketing AI Institute’s AI Score for Marketers^TM assessment, marketers had the opportunity to answer 13 survey questions, and rate the value of 49 sample marketing AI use cases. More than 400 marketers answered portions of the survey, and 235 completed all questions and use case ratings.

What we learned is that the marketing industry is on the cusp of the next frontier in digital transformation. Marketers believe that AI-powered solutions will intelligently automate dozens of common marketing tasks, and drive value through revenue acceleration and cost reduction.

But, we have not reached the tipping point, yet.

1. The majority of marketers know AI is very important or critical to their success this year.

When asked how important marketing AI is to their success over the next 12 months, the majority (52 percent) said it is very important (37 percent) or critically important (15 percent).

2. Marketers believe widespread intelligent automation of the industry is inevitable in the next five years.

The vast majority of marketers are just getting started with intelligent automation, which, in the survey, we presented as applying AI to improve the efficiency and/or performance of a task.

Today, more than 77 percent of marketers have less than a quarter of all marketing tasks intelligently automated to some degree, and 18 percent say they have not intelligently automated any tasks at all.

Yet, a similar majority (80 percent) believe more than a quarter of their marketing tasks will be intelligently automated in five years. A full 43 percent believe more than half of their tasks will be automated in that time.

3. Marketers are seeking to understand AI, and pilot smarter solutions.

Respondents were asked which stage of marketing AI transformation best describes their marketing teams, and could choose multiple options.

Most are in the Researching phase (65 percent), where they are becoming aware of AI. A majority are also in the Understanding phase (56 percent), where they were actively exploring use cases and technologies.

More than a third (34 percent) say they have entered the Piloting phase, which is defined by prioritizing, and starting to run, a limited number of quick-win pilot projects.

4. Some are seeing an impact from their marketing AI investments, specifically in revenue acceleration.

For marketers who are applying AI, accelerating revenue (41 percent) and getting more actionable insights from marketing data (40 percent) are the two most common outcomes that respondents say they are achieving.

Across all marketers surveyed, most (89 percent) said their marketing team’s highest priority includes accelerating revenue. Only eight percent adopt AI in marketing exclusively to reduce costs.

5. Half of marketers are still at the beginner stage of understanding AI terminology and capabilities.

Despite some of the data points that show AI understanding and adoption are on the rise, 50 percent of marketers classify their understanding of AI terminology and capabilities as beginner, while another 37 percent identify as intermediate.

6. Marketers lack confidence in evaluating AI-powered marketing technology.

The deficit in understanding and experience means that the majority of marketers lack confidence when evaluating and purchasing AI-powered products.

When asked to rank their confidence in evaluating marketing AI technologies, 40 percent chose medium, 24 percent selected low, and 5 percent said none.

Simply put, if marketers do not understand the underlying technology, and what it is capable of doing, they will struggle to identify smarter, AI-powered marketing solutions that can drive efficiency and performance.

7. Few marketers are successfully scaling marketing AI in their organizations.

Only 17 percent of marketers said they were in the Scaling phase of marketing AI transformation, which means wide-scale adoption of AI that is consistently producing efficiency and performance results.

It is encouraging to note that 19 percent are actively in the Humanizing phase, which is defined by, “Seamlessly integrating AI and human capabilities, and reinvesting the time and money saved from intelligent automation into listening, relationship building, creativity, culture, and communities.” We hope to see this number jump significantly in future studies.

8. Fear is not really a factor when it comes to barriers to adopting AI in marketing.

There is a common belief that fear of AI, and the unknowns it presents to the workforce, is an obstacle that must be overcome to achieve widespread adoption. Our research does not support this idea.

In fact, the majority (56 percent) of marketers believe AI will create more jobs than it eliminates over the next decade.

And when asked specifically about barriers to adoption of marketing AI, only 16 percent chose fear of AI as a contributing factor.

9. It is the lack of education and training that is holding marketers, and the marketing industry, back from adoption.

When asked about their barriers to AI adoption, marketers gave the most resounding answer of all.

It is a lack of education and training, as reported by 70 percent of respondents. To further this point, when asked if their organization has any AI-focused education and training, only 14 percent said yes.

Two other common barriers include lack of awareness (46 percent) and lack of resources (46 percent).

10. The future is marketer + machine. And the future is now.

The great irony of marketing automation is that it’s manual. Marketers write all the rules. They build the plans, produce the creative, run the promotions, personalize the experiences and analyze the performance. Traditional marketing is all human, all the time.

But, the landscape has changed. Leading marketers know that in order to deliver the website personalization and experiences modern buyers expect, marketing must become smarter. It must become marketer + machine.

Marketers do not believe AI will replace them. Rather, they see the potential to augment their knowledge and capabilities through the intelligent automation of data-driven, repetitive tasks.

We have entered the age of intelligent automation. The time is now for marketers to seek the knowledge and resources to understand, pilot, and scale AI in marketing.

The opportunities are endless for marketers with the will and vision to transform the industry, and their careers.

The 2021 State of Marketing AI Report collected responses to 13 questions about AI and its role in marketing. Additionally, data on 49 different marketing AI use cases across five categories of marketing (Planning, Production, Promotion, Personalization, and Performance) was collected using Marketing AI Institute’s AI Score for Marketers^TM assessment tool.

Respondents were not required to answer all questions or rate all use cases to submit their responses. A full 235 people answered all 13 survey questions and completed the full assessment to rate 49 AI use cases, with some questions receiving up to 425 responses.

The data presented in this report may reflect varying participation rates across different data points. Throughout the report, we clearly indicate the sample size of respondents for a particular answer set.

Respondents were gathered between October 8, 2020 and December 21, 2020. Respondents were marketed to by Marketing AI Institute and Drift via email, paid advertising, and social media.

Survey respondents represented a diverse set of roles, marketing disciplines, and company sizes.

Roles

57 percent identified their roles as Director-level or above. 

The highest percentage of respondents (22 percent) identified themselves as CEO/President, while the entire C-Suite comprised 38 percent of respondents.

Other top individual roles include: Chief Marketing Officer (12 percent), Senior Manager (10 percent), Director (10 percent), and Manager (10 percent).

Areas of Marketing

69 percent are involved in content marketing, the highest percentage of respondents. 

Respondents were asked about the areas of marketing in which they were involved at their organization, and could select multiple marketing categories.

The leading category was Content Marketing at 69 percent. The next most common area of marketing was Analytics at nearly 60 percent. Email marketing (58 percent) rounded out the top three most common areas of marketing.

Use case ratings throughout this report will reflect the fact that a majority of respondents do some work in content marketing, analytics, email marketing, social media marketing, and communications. Therefore, these use cases tend to be rated higher on average.

Industry

23 percent work in Professional Services, the highest percentage of respondents.

Professional Services was the industry most commonly identified by respondents, comprising 23 percent of respondents. Software (12 percent), Education (11 percent), and Media (7 percent) were other commonly cited industries.

B2B vs. B2C

78 percent work in B2B.

When asked if their company was business-to-business (B2B) or business-to-consumer (B2C), 42 percent indicated they were exclusively in B2B, while 36 percent said they were in both B2B and B2C. Only 18 percent indicated they were exclusively B2C.

Given the overlap, more than 78 percent work either fully or partially in B2B and 54 percent work in B2C.

Revenue

67 percent work at organizations with $10M or less in revenue.

Two-thirds of respondents work at companies with $10M in revenue or less. However, larger enterprises are represented as well, with 22 percent of all responses coming from marketers at companies with more than $50M in revenue.

Employees

63 percent work at organizations with less than 50 employees.

In line with revenue numbers, 63 percent of respondents work at organizations with less than 50 employees. At the other end of the spectrum, 21 percent work at companies with 250 or more employees. And, of note, 10 percent work at large enterprises with 5,000 or more employees.

Location

The largest concentration of respondents came from North America, with 38 percent in the United States, and 10 percent in Canada.

India (8 percent), Australia (6 percent), the United Kingdom (5 percent), and Germany (4 percent) were the only other countries with more than 2 percent of the total respondents. Marketers from a total of 43 countries completed the survey and assessment.

As part of the State of Marketing AI Report, respondents were asked to answer 13 questions about their AI knowledge and how their organization uses AI in marketing. The questions were either multiple choice with a single answer possible, or multiple choice with multiple answers possible.

Understanding of AI

50 percent of marketers classify themselves as AI beginners.

Q: How would you classify your understanding of AI terminology and capabilities?

When asked about how they would classify their understanding of AI terminology and capabilities, 50 percent of respondents classify themselves at the beginner level. A full 37 percent say they are at an intermediate level. Those with an advanced understanding of AI terminology and capabilities make up just 13 percent of marketers.

Marketing AI Knowledge and Capabilities

58 percent advance their knowledge and capabilities of AI in marketing through attending virtual/online events, the most common method.

Q: “What are you doing to advance your own AI knowledge and capabilities? Choose all that apply.”

Respondents were asked about what they were doing to advance their AI knowledge and capabilities. They could select multiple options.

Attending virtual/online events dominated the pack, with 58 percent of all respondents saying this is one activity they use to learn. A full 45 percent of respondents cited completing online courses as a top educational activity. And reading books (43 percent) rounded out the top three ways that respondents educate themselves about AI in marketing.

Role in Evaluating and Purchasing Marketing AI Technology

32 percent of respondents are decision makers with purchasing authority.

Q: “Which best describes your role in evaluating and purchasing marketing technology?”

The survey showed that 32 percent of respondents are decision makers with the authority and budget to purchase marketing technology in their organizations. An additional 25 percent are influencers who research and recommend solutions.

Marketing AI Confidence Level

69 percent rate their confidence level evaluating AI-powered technology as Medium, Low, or None.

Q: “How would you rank your confidence evaluating AI-powered marketing technology?”

When asked about their confidence in evaluating AI-powered marketing technology, 40 percent of respondents chose a medium confidence level. There was an almost even split between other respondents who claimed their confidence level was low (24 percent) and high (23 percent). Only 8 percent rated their confidence as very high.

AI’s Impact on Marketing Jobs

56 percent believe AI will create more marketing jobs than it eliminates.

Q: “What do you believe the net effect of AI will be on marketing jobs over the next decade?”

The majority of marketers are optimistic that AI will have a net positive effect on jobs, with 56 percent saying that more jobs will be created by AI. However, almost a quarter (23 percent) believed more jobs will be eliminated because of the technology, and 13 percent said they don’t know.

Stage of Marketing AI Transformation

34 percent are starting to pilot AI.

Q: “Which stage of marketing AI transformation best describes your marketing team? Choose all that apply.”

Respondents were asked which stage of marketing AI transformation best describes their marketing teams, and could choose multiple answers.

Respondents were most commonly in the Researching phase of marketing AI transformation, where they were becoming aware of what AI is and why it has the potential to transform marketing. A majority also indicated they were in the Understanding phase, where they were actively exploring use cases and technologies.

A full 34 percent said they were prioritizing or starting to run pilot projects, while only 17 percent were scaling their use of AI.

Importance of AI to Marketing

Q: “How important is AI to the success of your marketing over the next 12 months?”

52 percent say AI is very or critically important to the success of their marketing in the next 12 months.

Responses show that 37 percent of marketers believe AI is very important to the success of their marketing over the next 12 months, and another 15 percent say it is critically important. Only 4 percent say AI is not important at all.

Marketing AI Outcomes

41 percent are accelerating revenue growth with AI.

Q: “What outcomes is your marketing team achieving with AI today? Choose all that apply.”

Respondents were asked which outcomes their teams were achieving with marketing AI today. They could select multiple answers.

Most commonly, respondents were using AI in marketing to accelerate revenue growth and improve performance (41 percent). Almost as many (40 percent) are getting more actionable insights from marketing data using AI. Rounding out the top three most common outcomes, respondents are creating personalized consumer experiences at scale (38 percent).

Marketing Priorities

89 percent say revenue acceleration is a top marketing priority.

Q: “Which is a higher priority for your marketing team?”

When asked about their marketing team’s priorities, the highest proportion of respondents said they are trying to both accelerate revenue and reduce costs (46 percent). Almost as many say they are focused exclusively on accelerating revenue (43 percent). Comparatively, few are exclusively focused on reducing costs (8 percent).

Use of Intelligent Automation

77 percent believe they will be intelligently automating more than a quarter of their tasks in the next five years.

Q1: “What percentage of marketing tasks that your team performs are intelligently automated to some degree TODAY? (i.e. AI is applied to improve the efficiency and/or performance of the task.)”

Q2: What percentage of marketing tasks that your team performs do you believe will be intelligently automated to some degree in the NEXT FIVE YEARS? (i.e. AI will be applied to improve the efficiency and/or performance of the task.)”

Today, more than 77 percent of marketers have less than a quarter of all marketing tasks intelligently automated to some degree.

However, when looking out over the next five years, a similar majority of marketers (80 percent) believe they will be intelligently automating more than a quarter of their tasks.

In fact, 43 percent of marketers believe that more than half of all marketing tasks their team performs will be intelligently automated to some degree in the next five years.

Barriers to Marketing AI Adoption

70 percent say a lack of education and training is a top barrier to AI adoption.

Q: “Which of the following do you consider barriers to the adoption of AI in your marketing? Choose all that apply.”

Respondents were asked about their barriers to AI adoption in their marketing, and could choose multiple barriers.

The top barrier to AI adoption was a lack of education and training, with 70 percent of respondents citing it. Other major barriers included a lack of awareness (46 percent), lack of resources (46 percent), and lack of talent with the right skill sets (43 percent).

Notably, only 16 percent of respondents cited a fear of AI, and only 15 percent chose mistrust of AI as significant barriers to adoption.

Marketing AI Education and Training

82 percent do not have internal AI-focused education and training.

Q: “Does your organization offer any AI-focused education and training for the marketing team?”

When asked if their organizations offered AI-focused education and training for the marketing team, 66 percent of respondents said no, and another 16 percent indicated it was in development. Only 14 percent indicated that education and training existed.

In November 2016, we launched Marketing AI Institute and published our first spotlight in which we ask the same questions of every company. (See Drift’s spotlight here.)

The insights gained from this research led to the creation of a new framework to help visualize and organize the marketing AI technology landscape – the 5Ps of Marketing AI.

1. Planning: Building intelligent strategies
2. Production: Creating intelligent content
3. Personalization: Powering intelligent consumer experiences
4. Promotion: Managing intelligent cross-channel promotions
5. Performance: Turning data into intelligence

For this report, respondents were asked to rate 49 marketing AI use cases using the 5Ps of Marketing AI framework. Keep in mind, these are simply a collection of common use cases. There are hundreds, if not thousands, of potential use cases for AI in marketing; such as AI chatbots.

For each of the 5Ps, respondents were asked the same question, “Assuming AI technology could be applied, how valuable would it be for your team to intelligently automate each of the use cases below?”

For each use case, respondents were asked to consider the potential time and money saved, and the increased probability of achieving business goals. Then, respondents were instructed to rate each use case on a 1-5 scale:

• N/A = Your team does not perform the use case
• 1 = No value
• 2 = Minimal value
• 3 = Moderate value
• 4 = High value
• 5 = Transformative

The resulting ratings offer unparalleled insights into how much marketers value the potential intelligent automation of more than four dozen use cases.

Across all marketing AI use cases, the average rating was 3.53 out of 5.00. The top 10 individual use cases by score across all 5Ps were:

1. Recommend highly targeted content to users in real-time. (3.96)
2. Adapt audience targeting based on behavior and lookalike analysis. (3.92)
3. Measure return on investment (ROI) by channel, campaign, and overall. (3.91)
4. Discover insights into top-performing content and campaigns. (3.86)
5. Create data-driven content. (3.82)
6. Predict winning creative (e.g. digital ads, landing pages, CTAs) before launch without A/B testing. (3.81)
7. Forecast campaign results based on predictive analysis. (3.80)
8. Deliver individualized content experiences across channels. (3.80)
9. Choose keywords and topic clusters for content optimization. (3.78)
10. Optimize website content for search engines. (3.77)

Out of the top 10 marketing AI use cases, three were classified as dealing with content marketing. An additional three were classified as analytics use cases. The third most common category of use case was SEO, comprising two out of the top 10 use cases.

The five lowest-rated use cases included:

1. Predict customer churn. (3.19)
2. Formulate pricing strategies to maximize profitability. (3.15)
3. Transcribe audio (calls, meetings, podcasts, webinars) into text. (3.14)
4. Allocate and adjust marketing budgets. (3.14)
5. Find and merge duplicate contacts in your CRM. (2.91)

It is important to remember that use cases are subjective. The majority of respondents do at least some work in content marketing, analytics, email marketing, social media marketing, and communications, which may account for the use cases that get rated highest and lowest. A low-ranked use case may have the potential to unlock enormous value for individuals who work in areas of marketing different from the respondents in this report.

Marketing AI Use Cases by Category

As a part of the survey, respondents were given an overall AI Score based on the total value of their ratings, divided by 245, which is the total possible score if you rated every use case a 5 (i.e. 49 use cases with a score of up to 5 for each use case). This score is a reliable proxy for understanding AI’s potential at your organization across each of the 5Ps, as well as an individual’s overall need for AI in their marketing.

Across all respondents, the average total AI Score was 71 percent, indicating AI holds overall high potential for the marketing activities of those surveyed. We also broke down the AI Score for each individual use case category.

Planning

Building intelligent strategies.

The average AI Score across Planning use cases was 68 percent, slightly below the overall average. The average use case rating in this category was 3.41.

The top three use cases rated highly by respondents in the Planning section were:

• Choose keywords and topic clusters for content optimization (3.78)
• Analyze existing online content for gaps and opportunities (3.75)
• Score leads based on conversion probabilities (3.69)

The three lowest-rated use cases were:

• Formulate pricing strategies to maximize profitability (3.15)
• Allocate and adjust marketing budgets (3.14)
• Find and merge duplicate contacts in your CRM (2.91)

Production

Creating intelligent content.

The average AI Score across Production use cases was 71 percent, just a little below the overall average. The average use case rating in this category was 3.52.

The top three use cases rated highly by respondents in the Production section were:

• Create data-driven content (3.82)
• Optimize website content for search engines (3.77)
• Predict content performance before deployment (3.70)

The three lowest-rated use cases were:

• Tag website images with keywords and categories (3.42)
• Write creative briefs and blog post drafts (3.32)
• Transcribe audio (calls, meetings, podcasts, webinars) into text (3.14)

Personalization

Powering intelligent consumer experiences.

The average AI Score across Personalization use cases was 73 percent, above the overall average. The average use case rating in this category was 3.64.

The top three use cases rated highly by respondents in the Personalization section were:

• Recommend highly targeted content to users in real-time. (3.96)
• Determine offers that will motivate individuals to action. (3.74)
• Present individualized experiences on the web and/or in-app. (3.74)

The three lowest-rated use cases were:

• Customize email nurturing workflows and content. (3.59)
• Optimize email send time at an individual recipient level. (3.45)
• Engage users in conversations through bots that learn and evolve. (3.37)

Promotion

Managing intelligent cross-channel promotions.

The average AI Score across Promotion use cases was 73 percent. The average use case rating in this category was 3.65, which was the highest across categories.

The top-rated three use cases for Promotion were:

• Adapt audience targeting based on behavior and lookalike analysis. (3.92)
• Predict winning creative (e.g. digital ads, landing pages, CTAs) before launch without A/B testing. (3.81)
• Deliver individualized content experiences across channels. (3.80)

The three lowest-rated use cases were:

• Improve email deliverability. (3.52)
• Identify real-time social media and news trends for promotional opportunities. (3.47)
• Schedule social shares for optimal impressions and engagement. (3.44)

Performance

Turning data into intelligence.

The average AI Score across Performance use cases was 72 percent, higher than average. The average use case rating in this category was 3.61.

The top-rated three use cases for Performance were:

• Measure return on investment (ROI) by channel, campaign and overall. (3.91 average rating)
• Discover insights into top-performing content and campaigns. (3.86)
• Forecast campaign results based on predictive analysis. (3.80)

The lowest-rated use case in the category was: Monitor and evaluate brand mentions from media and influencers. (3.21)

The age of intelligent automation has begun in marketing – and most marketers know it. But the industry has a lot of work ahead.

Forward-thinking organizations are already using AI to accelerate revenue and reduce costs. In the process, they are building sustainable competitive advantages for their products and their people. Unfortunately, most marketers still lack adequate education, training, and confidence to understand, pilot, and scale AI technologies.

The State of Marketing AI today presents both a challenge and an opportunity.

It presents a challenge to AI-powered companies, vendors, and champions – a challenge to drive AI education and adoption with smarter solutions and approaches.

And it presents an opportunity to every marketer – an opportunity to evolve into a next-generation professional by embracing AI.

Together, we can transform the marketing industry. Together, we can move forward the State of Marketing AI.

Drift is the Revenue Acceleration Platform that uses Conversational Marketing and Conversational Sales to help companies grow revenue and increase customer lifetime value faster.

More than 50,000 businesses use Drift to align sales and marketing on a single platform to deliver a unified customer experience where people are free to have a conversation with a business at any time, on their terms.

Marketing AI Institute is an online education and event company that makes AI approachable and actionable to marketing leaders around the world.

The Institute owns and operates Marketing AI Conference (MAICON), a global event that attracted 300 marketing leaders from 12 countries in its inaugural year, and AI Academy for Marketers, an online education platform and community built to help marketers understand, pilot and scale AI.

Since its launch in 2016, Marketing AI Institute has educated tens of thousands of marketers on the present and future potential of artificial intelligence, and connected them with AI-powered technologies to drive marketing performance and transform their careers.

Today, our weekly newsletter subscriber list includes marketing leaders from major brands such as Accenture, Adidas, Adobe, Disney, Ford, IBM, KPMG, LEGO, LinkedIn, MasterCard, Mayo Clinic, Microsoft, Nasdaq, Nvidia, Oracle, and Samsung.

Marketing AI Institute’s founder and CEO is Paul Roetzer. Roezer is also the founder and CEO of PR 20/20, a marketing consulting and services firm. He is an international speaker who has given more than 100 presentations on AI, as well as authored The Marketing Agency Blueprint (Wiley, 2012) and The Marketing Performance Blueprint (Wiley, 2014). His next book, Marketing AI, is scheduled for release in spring 2022.