How generative AI is transforming marketing and businesses

Marketers should always consider the ethical implications of AI use, such as data privacy and transparency. This involves being clear with consumers about how their data is being used and ensuring that all AI-driven marketing practices comply with relevant laws and regulations. This means ensuring that the data used to train the AI is not only extensive but also accurate, relevant, and free from bias.

For example, Adobe Experience Platform is an open, real-time customer experience platform backed by Adobe Sensei Gen AI capabilities. It seamlessly consolidates data from diverse touchpoints, creating a unified Yakov Livshits customer profile for enhanced personalization. Another benefit of integrating different generative AI tools into a single platform is the ability to streamline the marketing campaign creation process.

Letting you focus on the Customer

Generative AI can fundamentally change how marketing departments operate, allowing teams to place more focus where it belongs — on the customer. This technology has been around for some time, but it has recently become more popular due to advances in machine learning and deep learning. Generative AI can create things such as music, images, videos, text—all without human intervention. Overreliance on AI-generated content is a risk, but not using it at all is equally risky. You’ll slow down production and burn out human marketers on content grunt work that AI can easily generate. Generative AI automates customer surveys to improve traditional data collection and analysis capabilities.

Generative AI models are trained on huge datasets, which enables them to create unique content every time. However, the datasets used to train these models may sometimes be biased, due to which the content created may not be satisfying. Ethical issues with the generated content are a concern for 67.4% of businesses in implementing generative AI.

Models attempting to learn from content and synthesize it

LLMs are increasingly being used at the core of conversational AI or chatbots. They potentially offer greater levels of understanding of conversation and context awareness than current conversational technologies. Facebook’s BlenderBot, for example,  which was designed for dialogue, can carry on long conversations with humans while maintaining context. Google’s BERT is used to understand search queries, and is also a component of the company’s DialogFlow chatbot engine. Deloitte has experimented extensively with Codex over the past several months, and has found it to increase productivity for experienced developers and to create some programming capabilities for those with no experience.

It is the marketer’s responsibility to procure, manage, and maintain this data. There are numerous ethical considerations in marketing, from data privacy to truthful advertising. Human oversight is necessary to ensure that AI-driven marketing adheres to ethical standards and regulations. If you are interested in other generative AI tools, you can read our article on top 35 generative AI tools by category. Use licensed or original content to respect legal restrictions and avoid copyright infringement. To uphold ethical standards, obtain the required consent for data usage and be open and honest with your audience about using AI in content development.

In this context, generative AI serves as an additional team member who can convey a fresh point of view or help marketers develop new ideas based on what they’ve already prepared. Since ChatGPT’s emerger, generative AI has been a no. 1 topic on everybody’s tongues. After all, we’re talking about the groundbreaking technology that has every potential to significantly impact various aspects of everyone’s lives, including — or should I say starting with — the way we work. Bobby Jania is the Senior Vice President of Marketing for Marketing Cloud, leading teams focused on messaging, positioning, and go-to-market strategy. That trusted first-party data is important for generative AI to work well, 63% of marketers told us.

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

It works by learning patterns from existing data and using that knowledge to create new content. Rapid advancements have left us with AI that can write engaging text and create realistic images. LivePerson is a platform providing several generative-AI-powered products, including two marketing tool suites. Yakov Livshits Combining the power of generative AI with your CRM data gives marketers the ability to create those kinds of digital experiences for their customers. Altogether, this results in more efficient marketing journeys that are better tailored to their audience across content generation, design, and targeting.

Customer Experience

To make it easier to increase revenue from both new and existing customers, we’re also enhancing our new customer acquisition goal and introducing a re-engagement goal for Performance Max campaigns. Simply add a preferred landing page from your website and Google AI will summarize the page. Then, it will generate relevant and effective keywords, headlines, descriptions, images and other assets for your campaign. Now, you can chat your way into better performance — ask Google AI for ideas, just like you might ask a colleague.

For AI to generate good results, humans are involved in the data gathering process. By now you know that AI powers most of the customer support you encounter, such as answering frequently asked questions or providing personalized recommendations through tools like chatbots and even those – gasp! The prompts can get pretty specific too – like telling it to write in the style of a famous author or create a persuasive sales email using hyperbole and a lot of puns.

Generative AI also raises numerous questions about what constitutes original and proprietary content. Since the created text and images are not exactly like any previous content, the providers of these systems argue that they belong to their prompt creators. But they are clearly derivative of the previous text and images used to train the models. Needless to say, these technologies will provide substantial work for intellectual property attorneys in the coming years. In a six-week pilot at Deloitte with 55 developers for 6 weeks, a majority of users rated the resulting code’s accuracy at 65% or better, with a majority of the code coming from Codex. Overall, the Deloitte experiment found a 20% improvement in code development speed for relevant projects.

It’s your business, your marketing and your results — all multiplied by Google AI. As always, we’ll be experimenting first, testing and listening to your feedback along the way. This new Search Generative Experience (SGE) can be found in Search Labs, a place to access Google Search experiments. At I/O, we showed how ads will appear above and below this new experience. Now, over the coming months, we’ll experiment with Search and Shopping ads that are directly integrated within the AI-powered snapshot and conversational mode. We’ll also experiment with new formats native to SGE that use generative AI to create relevant, high-quality ads that are customized to every step of the search journey.

Marketers are encouraged to explore and embrace this transformative technology to unlock unprecedented creativity, efficiency and personalization. Midjourney and DALL.E2 are excellent real-world examples of AI image generators. They can generate stunning, hyper-realistic visuals of humans, animals and real-world objects. Businesses have been leveraging the benefits of generative AI to a certain extent. However, as the industry continues to mature further, there is a lot of potential for many more developments. With the AI models working on the data used to train them, there are chances that the content produced is plagiarized.

Generative AI has raised considerable buzz lately, but with this hype comes a lot of misconceptions and confusion on how it can help marketers. With customer expectations rising and personalization now an expectation, marketers can use generative AI to help maintain customer loyalty and gain Yakov Livshits insights in a post-cookie world. Generative AI in marketing can give users the advantage of saving time and money. However, despite the existential dilemmas brought on by AI, it’s important to remember that generative AI tools are NOT advanced enough to replace human content creators.

• Business owners can use technology instead of employees if they run a small business and don’t have the staffing to get everything done.
• Understanding your customers is key, and one of the best ways to do that is through customer segmentation.
• But they are clearly derivative of the previous text and images used to train the models.
• If marketing teams fail to edit AI-generated content or ensure data privacy, a generative AI tool can do more harm than good.
• Draft and send personalized email campaigns to segmented customer lists, optimizing open and conversion rates.

These tools can help businesses improve customer engagement and retention, SEO, ad optimization, market research, and sales forecasting. It also allows marketers to drive user engagement, increase brand awareness, and foster connections with their target audience on social media. Those capabilities of generative AI can help you take amplified marketing to another level. You can maximize the value and reach of your original content with less time and effort. Make the technology do research grunt work while you do the fun and creative work of developing unique, engaging, authentic marketing content without needing to generate net-new material. Examples of AI content include essays, short-form content, books, lifelike images and art, and audio clips.