IDC report says generative AI will have a huge impact on the marketing industry by 2027

Generative AI is a type of artificial intelligence technology that broadly describes machine learning systems capable of generating text, images, code or other types of content, often in response to a prompt entered by a user. Generative AI models learn the patterns and structure of their input training data and then generate new data that has similar characteristics. For example, a generative AI model can create realistic images of faces, landscapes, or products that do not exist in reality, or write catchy slogans, headlines, or product descriptions based on a given topic or keyword.

According to a recent report by IDC, a leading global market intelligence, generative AI will have a profound impact on the marketing industry by 2027, as it will enable marketers to create more engaging, personalized, and diverse content for their target audiences, as well as optimize their campaigns and strategies based on data-driven insights. The report predicts that generative AI will account for 40% of all marketing content creation and optimization by 2027, up from less than 5% in 2023.

Some of the key benefits of generative AI for marketing include:

• Enhancing creativity and innovation: Generative AI can help marketers unleash their creativity and generate novel ideas for their campaigns, products, or services, by providing them with a variety of options and suggestions based on their inputs. For example, Generative AI companies in India use Generative AI tool to create a logo, a slogan, or a name for a new product, or to generate a storyboard, a script, or a video for a new ad campaign.
• Improving personalization and relevance: Generative AI can help marketers tailor their content and messages to the preferences, needs, and behaviors of their customers, by using data and analytics to understand their profiles, segments, and journeys. For example, a marketer can use a generative AI tool to create personalized emails, landing pages, or offers for each customer, or to generate dynamic content that adapts to the context and situation of the customer.
• Increasing efficiency and productivity: Generative AI can help marketers save time and resources by automating and optimizing their content creation and delivery processes, by using algorithms and models to generate, test, and refine their content. For example, a marketer can use a generative AI tool to create multiple versions of a headline, a banner, or a social media post, and then select the best one based on the performance metrics and feedback.
• Enhancing quality and consistency: Generative AI can help marketers improve the quality and consistency of their content and brand voice, by using standards and guidelines to ensure that their content is accurate, relevant, and coherent. For example, a marketer can use a generative AI tool to check and correct the grammar, spelling, tone, and style of their content, or to ensure that their content is compliant with the regulations and policies of their industry and region.

The report also highlights some of the challenges and risks of generative AI for marketing, such as:

• Ensuring ethics and trust: Generative AI can pose ethical and trust issues for marketers and customers, as it can create content that is misleading, deceptive, or harmful, or that infringes on the rights and privacy of others. For example, a generative AI tool can create fake or manipulated images, videos, or reviews that can damage the reputation or credibility of a brand, or that can violate the consent or identity of a person.
• Managing complexity and security: Generative AI can introduce complexity and security challenges for marketers and their organizations, as it requires advanced skills, tools, and infrastructure to develop, deploy, and maintain. For example, a generative AI tool can require a large amount of data, computing power, and storage to train and run, or it can be vulnerable to cyberattacks or malicious use by hackers or competitors.