- Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
- To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
- This is part 12: Marketing.
Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
This is part 12: Marketing.
Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
This is part 12: Marketing.
Generative AI offers marketing a time to shine.
Companies have long had the data they need to create hyper-personalized experiences. But it’s been housed in disparate data sets across multiple departments, and marketing didn’t have the power to harness it—until now.
Generative AI fuels both high-octane content creation and real-time data analysis, giving marketing teams the nitro boost needed to deliver bespoke customer communications. This can both supercharge the organization’s brand and introduce new risks. In this environment, 76% of CMOs say generative AI will change the way marketing operates—and 76% also say the failure to quickly adopt generative AI will significantly hurt their ability to stay competitive.
While many marketing organizations are already using generative AI based on public large language models (LLMs) for content creation, few have tapped this game-changing capability for extreme customization by feeding the models their own data. But that will soon change, as more than half (51%) of CMOs say they have plans to build foundation models with proprietary data—the intellectual capital about customers that sits in marketing—before the end of 2024.
Generative AI offers a way to create content faster with more personalized messages, and it gives marketing executives more control over analytics, making it far easier to distill insights from customer data with speed and specificity at scale. It highlights patterns that tease out the details of customer preference, letting marketers finally go beyond targeted segmentation to serve up truly individualized offers and interactions.
The real-time insights it enables can also help marketers gauge whether personalized products, services, and experiences are hitting the mark—and shift gears quickly when the answer is no.
The IBM Institute for Business Value has identified three things every leader needs to know:
1. Marketing is the pacesetter for enterprise-wide generative AI.
2. Content creators are freed from feeding the beast.
3. With generative AI, hyper-personalization is no longer a pipe dream.
And three things every leader needs to do right now:
1. Position marketing as the model for generative AI-driven workforce transformation.
2. Prioritize creative ideation and high production value in marketing content.
3. Build 360-degree customer profiles using integrated data.
An updated version of this chapter with 2024 data is now available in the latest edition of the IBM Institute for Business Value's book, The CEO's Guide to Generative AI.
Additional content
Meet the authors
Anthony Marshall, Senior Research Director, Thought Leadership, IBM Institute for Business ValueCindy Anderson, Global Executive for Engagement and Eminence, IBM Institute for Business Value
Christian Bieck, Europe Leader & Global Research Leader, Insurance, IBM Institute for Business Value
Carolyn Heller Baird, Global Research Leader, Customer Experience and Design, IBM Institute for Business Value
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Originally published 05 December 2023
1. Transformation
+ Generative AI
What you need to know
Marketing is the pacesetter for enterprise-wide generative AI
When all the mundane and repetitive tasks are automated, how should humans spend their time? More than one in four (27%) executives expect marketing roles to be automated due to generative AI. While this may sound dire for marketing professionals, there’s a huge opportunity yet to be uncovered, according to Mark Read, CEO of WPP, the world’s largest advertising organization.
“We know what jobs [generative AI] will disrupt, but we don’t know what jobs AI will create. And I’m sure it’ll create many, many jobs. If I look at WPP, probably half the jobs inside the company didn’t exist 20 years ago. We didn’t have social media managers. We didn’t have programmatic media managers. We didn’t have search engine optimizers. I could go on.”
To realize its full value, generative AI models will need to access customer data across the full chain of engagement—from marketing to sales to service. That means marketing teams have an amazing opportunity for growth, but also need to broaden their view of data privacy and governance to manage brand risks—and safeguard customer trust. However, only 26% of CMOs say their marketing function is implementing generative AI in collaboration with both sales and customer service.
Rethinking the marketing operating model to enable more effective human-technology partnerships frees up humans to do higher-value work. Bolstering creativity and innovation, strategic thinking and decision-making, and product positioning and merchandising can help marketing teams upskill and accelerate through the learning curve. And once these teams hit their stride, CEOs can distill learnings into a road map that will help other functions integrate this technology more effectively across the enterprise.
What you need to do
Position marketing as the model for generative AI-driven workforce transformation
Challenge your CMO to redefine what marketers do. And what they don’t. Build lessons learned into transformation of other functions across the enterprise.
- Make the CMO the champion of the customer. Position marketing as the owner of the brand’s customer experience and lifecycle. Give it the responsibility and authority to influence the customer value chain across the enterprise. Recognize and address brand risks while leveraging new engagement opportunities offered by generative AI.
- Emphasize higher-value role creation. Work with the CMO to build marketing teams rooted in the skills needed for the generative AI era. As in customer service, apply lessons learned from marketing’s reinvention to other functions.
- Turn apprehension into excitement. Encourage your CMO to execute a purpose-driven, targeted, formal change management approach to help marketers understand and lean into new value propositions for their roles. Lead with openness, transparency, and authentic communication from both the top down and the bottom up.
2. Content
+ Generative AI
What you need to know
Content creators are freed from feeding the beast
Content production can be oppressive. As teams rush to meet never-ending deadlines, high-value, strategic work is often lost in the shuffle.
Generative AI promises to change all that. It can take on the lion’s share of content creation work, helping teams summarize messaging, brainstorm catchy taglines, and optimize assets for different audiences.
By 2025, three in four CMOs say their organization will use generative AI for content creation. And more than half say they will use it for content transcreation (51%), which goes beyond simple translation to ensure the tone and meaning of the original asset is appropriately localized for a specific geography or culture.
As generative AI plays a larger role in content creation, teams will be able to spend more time thinking strategically about how messaging can support both business objectives and customer needs—and experimenting with innovative marketing approaches. They can create dynamic journey maps based on what buyers are doing.
Rather than frantically filling the publishing pipeline, they can thoughtfully consider where high-value content should be created based on data inputs and determine which delivery methods will be most effective for each customer. These directives can also fuel product and merchandizing decisions across the organization.
What you need to do
Prioritize creative ideation and high production value in marketing content
Raise the bar for marketing materials by tying them to touchpoints and moments of truth along the customer journey. Boost productivity by streamlining content creation and diverting human energy toward higher-value work.
- Say goodbye to writer’s block. Show teams how generative AI can accelerate the content production process. Tap LLMs customized with your organization’s data to help brainstorm topics, headlines, social posts, and variations on messaging that will work for different audiences. Triple check to eliminate bias in any content created by generative AI–or humans.
- Close the gap between customer needs and marketing content. Determine where content is needed to prompt desired customer actions and outcomes and use generative AI to produce pieces that will alleviate specific pain points on the customer journey.
- Identify people doing tomorrow’s jobs today. Discover the new roles that generative AI enables by paying close attention to people on the front lines. Those who embrace generative AI from the start will have insights, leading practices, and lessons learned that will help you define the MarOps model of the future.
3. Hyper-personalization
+ Generative AI
What you need to know
With generative AI, hyper-personalization is no longer a pipe dream
Every customer is unique—but on a traditional marketing dashboard, they get diluted in a sea of aggregated data. The details needed to make personal connections are lost.
More than two in five (42%) CMOs say scaling hyper-personalization is a marketing priority—and 64% expect to use generative AI for content personalization in the next year or two. But organizations need a consolidated, granular view of customer behaviors and preferences to get there. This takes flawless data integration and management, which has long been marketing’s Achilles heel.
That’s why CMOs crave more authority over data collection and insights. When asked which aspects of marketing they want to control more, analytics topped the list.
Generative AI could synthesize the complexity of customer preferences and behaviors into actionable insights that marketers need. By analyzing customer data faster and more dynamically from a variety of sources, teams can see what works best for specific customers and tailor outreach efforts accordingly. From personalized content and experiences to bespoke chatbot support, generative AI can help teams address customer needs in real time.
The list of potential applications keeps growing, and CMOs are focused on building a strong foundation of analytical capabilities that will help them keep up with the pace of change. For example, 78% of CMOs expect to use generative AI to conduct data analysis and capture insights from digital/social channels by the end of 2024—up from 36% today. And 86% of CMOs say they plan to use generative AI to analyze customer insights by 2025.
What you need to do
Build 360-degree customer profiles using integrated data
Unified data will make all the difference in hyper-personalized marketing. Give CMOs autonomy over the marketing tech stack across all touchpoints, including sales and service.
- Build multidisciplinary marketing and IT teams. Align CMO and CIO priorities, incentivizing partnership between the two. Stand up the infrastructure, systems, and data integration required for true one-to-one marketing with generative AI.
- Get the full picture of your customers’ needs. Break down functional silos to consolidate data from marketing, sales, and customer service to capture a complete picture of customers’ individual journeys with your business.
- Supercharge open models with customer data. Position your customer data as your best brand differentiator and defense against misinformation. At the same time, leverage the speed and scalability of open and public models to personalize experiences and offerings—while securing sensitive data each step of the way.
The statistics informing the insights on this page are sourced from two proprietary surveys conducted by the IBM Institute for Business Value in collaboration with Oxford Economics. The first survey was asked to 110 US-based Chief Marketing Officers in September–October 2023 regarding the impact of generative AI on the marketing function. The second survey was asked to 300 US-based executives in May 2023 regarding the impact of generative AI on labor.
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An updated version of this chapter with 2024 data is now available in the latest edition of the IBM Institute for Business Value's book, The CEO's Guide to Generative AI.
Additional content
Meet the authors
Anthony Marshall, Senior Research Director, Thought Leadership, IBM Institute for Business ValueCindy Anderson, Global Executive for Engagement and Eminence, IBM Institute for Business Value
Christian Bieck, Europe Leader & Global Research Leader, Insurance, IBM Institute for Business Value
Carolyn Heller Baird, Global Research Leader, Customer Experience and Design, IBM Institute for Business Value
Download report translations
Originally published 05 December 2023
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