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AI for marketers

Accelerate your marketing lifecycle

Raise the bar on creativity, productivity, and performance with generative AI assistance across your content lifecycle and experience delivery

 

AI-powered marketing lifecycle

Set every campaign up for success with everything from intelligent creative ideation to automated experience generation, orchestrated with the help of cutting-edge AI.

  • Simplified brief creation and campaign planning

    Based on your campaign focus, AI will help you research trends in the market, SEO opportunities, historical data, and more. The output is a brief and plan, including all the details your creative teams need.

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  • Streamlined asset discovery and creation

    AI helps creative and digital teams intelligently source image options from asset libraries based on your brand, creative brief, and insights into the expected performance so on-brand assets can be created quickly for launch across all digital touchpoints.

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  • Accelerated launch of personalized experiences

    Leverage integrated AI to get recommendations for page layouts, based on current templates, audience segments, components, and design systems.

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  • Proactive AI-powered recommendations

    Unlock AI-suggested page variants and optimization opportunities before you launch, including SEO, A/B testing, personalization, and more to maximize performance from day one.

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Innovating for the future

"We have the strategy, roadmap, and team to deliver on the promise of generative AI, and a marketer-first ethos will remain at the heart of all our innovation. I can’t wait to see what brands will do with it."

Dave O’Flanagan, Sitecore CEO

Unlock your marketing potential

Turn your content creation process into an AI-assisted symphony of digital experiences that captivate and drive results. Using your brand assets, past campaigns, trends, and more, Sitecore can help you efficiently deliver marketing programs that drive results.   From generating comprehensive briefs to suggesting detailed deliverables, Sitecore helps ensure every aspect of your campaign is crafted for success. 

See it in action
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Marketers around the world are investing in AI and a tech stack that supports AI

According to a recent survey, generative AI is seen as a pivotal, game-changing advancement for brand marketers searching for solutions that can deliver rapid-fire personalization to customers expecting intuitive, engaging digital experiences.

79%

of respondents list AI among their top martech investment priorities.

85%

are planning to move at least some of their marketing tech stack to composable software for flexibility, speed, and cost efficiency.

More AI resources

Dive deeper into artificial intelligence

The Microsoft AI showcase

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AI in marketing

Read the article

Frequently asked questions

  • What is generative AI?

    Generative artificial intelligence (gen AI) is a type of artificial intelligence (AI technology) that often uses generative adversarial networks (GANs) to create realistic and original content. Generative AI using GANs involves the use of two neural networks, known as the generator and the discriminator, which work together in a competitive manner.

    The generator network is tasked with creating new data, such as new content , images, or music, based on patterns it has learned from a given dataset during the training phase. The discriminator network acts as a judge and tries to differentiate between the generated data and real data from the training set. As the training progresses, both the generator and discriminator become more skilled. The generator learns to produce data that increasingly resembles the real training data, while the discriminator becomes better at distinguishing real data from the generated samples.

  • What is an example of generative AI?

    Popular examples of generative AI technology include OpenAI’s ChatGPT, including GPT-3 and GPT-4, and Google’s Bard, an AI chatbot based on the LaMDA family of large language models (LLMs). Other AI solutions include Microsoft Copilot, DALL-E, Midjourney, DeepMind, the open-source provider HuggingFace, and open-source deep learning framework Apache MXNet.

  • How can generative AI be applied?

    Generative AI has applications including image synthesis, video generation, text generation, prompt engineering, and music composition. Generative AI models and AI applications have shown remarkable potential, and use cases are being explored across healthcare and medical imaging, software development, data augmentation, content creation, image generation, and technology startups.
  • What are the advantages of generative AI?

    Like other AI technologies, generative AI can increase productivity through automation and streamlining workflows. It can enable the faster creation of new content and assist with the optimization of existing content; it can also facilitate deep learning and the analysis of data sets that are both large and complex, which is especially helpful in fields like healthcare.   
  • What are the disadvantages of generative AI?

    Generative AI is a tool, and as such has limitations. Like other AI tools, generative AI is only as good as the data it is trained on and there is enormous potential for bias in the training data; this can and has led to biased and discriminatory outputs. Generative AI is like other AI systems in that it is resource intensive and can be cost prohibitive.

    There are also ethical considerations. Generative AI can be used to create deepfakes and other unethical content, and AI-generated content may infringe on the intellectual property and/or copyright of other works if the AI had access to the copyrighted material and produced a substantially similar output.

  • What is the difference between predictive and generative AI?

    The foundation models of the two are the same: both use machine learning models. While generative AI turns machine learning inputs into content, predictive AI uses machine learning to predict outcomes.
  • How does Sitecore ensure responsible governance of its gen AI technologies?

    Sitecore is deeply committed to the responsible and safe use of gen AI technologies. To uphold this commitment, we conduct thorough AI Impact Assessments which involve comprehensive risk and impact analyses for all products integrating AI. These assessments meticulously evaluate potential risks and impacts of AI integration, enabling us to devise and implement effective mitigation strategies for any identified concerns.

    We also have a cross-functional AI Governance Board to oversee responsible AI use within our organization. For an insight into our AI governance framework, please see here.
  • How is generative AI used for digital marketing?

    Generative AI enables marketers to automate content creation, personalize messaging, and optimize campaigns for better engagement and conversion. In digital marketing, generative AI refers to the use of AI algorithms to create, optimize, and personalize marketing content and campaigns.
  • How can generative AI enhance content and improve customer experience?

    By generating personalized content at scale, generative AI ensures relevant and engaging experiences for customers, driving satisfaction and loyalty. Generative AI analyzes vast amounts of data to understand customer preferences and behavior, allowing businesses to personalize experiences and anticipate needs.
  • What types of AI models are used for Generative AI?

    Generative AI employs various models such as GPT (Generative Pre-trained Transformer), LSTM (Long Short-Term Memory), and variational autoencoders to generate content. Sitecore’s product strategy embraces the power of composable to shape the digital future.

  • What's the difference between generative AI and adaptive AI?

    Generative AI creates new content from scratch, while adaptive AI adjusts existing content based on user feedback and interactions.

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