Generative AI

4 Ways Generative AI Can Help Marketers Make an Impact




AI is coming for creative work—and that’s ok. In 2023, generative AI is at the top of every marketer’s mind as people experiment with tools like ChatGPT. We see them produce increasingly convincing copy with just a prompt and the push of a button, and we wonder how that will scale, what possibilities it brings to the table, and who it might replace.
People are expressing equal parts anxiety and excitement. Both are understandable. We don’t yet know the full implications of this technology, and it will only accelerate from here. According to Grand View Research, the global market for generative AI will expand from $8 billion in 2021 to almost $110 billion in 2030. Gartner predicts that by 2025, 30% of outbound messages from large organizations will be synthetically generated.
Like every technological revolution, generative AI will produce new kinds of work and new ways to win. The challenge is knowing how to adapt.

What is generative AI?

Text-based generative AI tools leverage natural language processing to produce fresh content. They don’t just analyze existing information to build analytical or predictive models like their cousins in big data. Instead, their algorithms assemble text according to the conventions of standard formats: scripts, blog posts, technical reports, essays for higher education, conversations with long-dead historical figures, and the list goes on. Think of them as extremely advanced versions of the predictive text that’s common on mobile devices and word processors.

Generative AI depends on self-supervised learning. The “GPT” in ChatGPT, the most prominent of these tools, stands for “generative pre-trained transformer.” That gives you an idea of how it works. Its underlying model trains on immense swathes of text drawn from web archives until it can generate reliable predictions for conventional language models.

It’s important to remember that ChatGPT doesn’t build responses by searching the internet in real time. Instead, it uses its predictive language model to emulate how humans typically discuss a topic. That’s an important distinction as you consider where it can provide value.

Four ways to apply generative AI in marketing

While the most obvious use case for generative AI tools might be customer-facing copy, there are internal applications as well. Within the marketing discipline, it has potential across content creation, CRM and CS, knowledge management, and strategy.

Your writers have a new co-author

Generative AI holds enormous potential for content marketing when it comes to both volume and adaptability. The first and most obvious application is saving time. While it isn’t up to most agencies’ standards for final, customer-facing copy, it’s certainly useful for providing inspiration or helping with edits and iterations.

Generative AI also sidesteps the tedium of producing high-volume text variations for PPC campaigns, A/B testing, or personalization across segmented audiences. Encourage your writers to start ideating through experimentation, iterating on creative prompts, and automating how they break their copy down into different formats and specifications.

A quantum leap for conversational marketing

Generative AI represents a watershed for conversational marketing and direct customer engagement. As conversational generalists, ChatGPT and other out-of-the-box generative AI tools aren’t typically equipped to go deep on product. But through APIs, dev teams can connect these tools to accurate, relevant company information, then present it in a customer-facing forum.

Companies like Got It AI are adapting existing language models like ChatGPT’s to create experiences tailored for conversational marketing and customer service. They work by connecting to your existing knowledge base to field customer inquiries. They also learn from past conversations to build better and smarter dialogue paths. While many businesses are jumping on the customer service possibilities, we see the potential for more intelligent and compelling first-touch engagement.

Accelerate learning experiences

Internal professional development and upskilling take time, effort, and investment. Generative AI can ease that burden by simplifying and distilling concepts down to a consumable scale. It’s important to remember that ChatGPT doesn’t search for up-to-date information on the real-time internet. It’s explicitly a predictive language tool—no more, no less. Don’t expect it to encapsulate the latest information or discussions on a topic.

Using extensions like Summarize, you can easily pull out the key information from lengthy web pages or articles. The results will need oversight and editing from subject matter experts, but the labour of condensing and summarization is already done. Rinse, repeat, and you have the foundations for a rapid-deployment knowledge base.

Inform strategy through summary

Strategists and thought leaders can also build actionable insights using generative AI tools. As long as your researcher has a strong grasp of reliable sources, they can quickly navigate from McKinsey to Gartner to PWC to any number of research firms and pull out key insights through generative AI summary tools.

To start, experiment with breadth and depth approaches:

  • Input comprehensive trend reports from several different research firms and have the tool summarize each. Aggregate those summaries, then look for common trends that stand out.
  • Find and input research on a single topic across different providers. Conduct a meta-analysis of their summaries to sift the signal from the noise

What does generative AI mean for marketing professionals?

Technological inflection points disrupt industries. Refuse to accept that reality at your peril. But that doesn’t mean we need to be fearful. Even within the generations that make up the current workforce, we’ve seen several new technologies rise to prominence—ubiquitous home computing, the internet, smartphones, big data. Remember that new technologies don’t eliminate jobs. They evolve them.

Keep two things in mind as you plan your next moves. First, these tools work best in close collaboration with humans. Writing for Harvard Business Review, authors and AI experts Thomas Davenport and Nitin Mittal share that using AI effectively requires human attention at both the beginning and the end of the process. You might begin to think of writers and subject matter experts as content coordinators or curators rather than creators. Second, conduct any implementation thoughtfully, strategically, and with a firm understanding of your goals and the technology’s capabilities. Ask yourself some key questions:

What does this technology simply augment? Where is it a true disruptor?

Which use cases will be most helpful for our business and our clients? How do we decide that?

What can we put in place to maintain compliance and trust?

Moving forward with generative AI

As the technology grows and providers react to business needs, use cases will become clearer. Models will improve their output and humanlike qualities. Their polish will elevate from first draft to final. At the same time, API availability and specialized models mean that business-specific iterations of this technology will get more granular. We already see that pattern at work with Jasper, a marketing-oriented generative AI platform.

Finally, after Microsoft acquired ChatGPT’s developer OpenAI, the tech giant recently announced their AI-powered Bing and Edge. Microsoft calls them “your co-pilot for the web,” claiming they will lead to better search, more complete answers from sources across the web, a new chat experience, and more. Not to be outdone, Google revealed Bard—one day before Microsoft’s announcement. In addition to more intelligent searches and fact-finding, Google highlights Bard’s potential for supporting developers by creating tools they can use to design innovative applications with AI.

Moves like these have taken generative AI from a purely predictive language tool into active, AI-driven research, discovery, and development. Results have been mixed, but the technology is well on its way to accurate, active engagement with real-world knowledge. Now is the moment to prepare your business for the generative AI marketing revolution. Start experimenting, get comfortable with the technology, and explore its benefits and vulnerabilities. Encourage your people to do the same. Reward thoughtful exploration and build process around wins. It’s never clear how new technology will evolve your business, but one thing is certain: ignoring it is not an option.