Business Storytelling with Generative AI
Business Storytelling with Generative AI
As humans, we have told stories for millennia using nothing but our imagination and creativity. With Gen AI, our capabilities have received a brand-new, third dimension.
A couple of decades ago, my father bought me a book. It was called the Panchatantra and comprised a collection of tales. Each of the tales culminated in a lesson: There was the tale of the monkey and the crocodile that stressed the importance of quick wit, the lion and the mice, which highlighted the need to be kind, and the doves who flew away with the hunter’s net, stressing on teamwork and collaboration. In hindsight, my dad could have just told me to be quick-witted, a team player, and kind. However, I doubt those statements would have stuck around the way the tales from the Panchatantra have.
Humans are storytellers (and listeners of tales) at a fundamental level. In his seminal book Sapiens, Yuval Noah Harari suggests that the ability to believe in shared myths and stories enabled Homo Sapiens to form complex social structures. These structures could support herds that were larger than anything our competitors, animals, and humans (other offshoots of the genus Homo: Neanderthals, Erectus, and more) could muster. Eventually, we were able to use our numbers to emerge as the planet’s dominant species.
Business Storytelling in the Modern World
Storytelling has always been around. From oral traditions and ceremonial performances to writing stories on clay tablets, papyrus, and parchment, we have always tried to preserve the best stories for future generations. These efforts peaked in the 15th Century with the invention of the Gutenberg press which allowed books to be published in bulk, democratizing access to knowledge. Another coup was in the institutional realization of storytelling's importance for driving messages home. The Roman government, for example, ensured it stayed relevant through daily announcements—known as Acta Diurna—which highlighted its efforts on the average citizen's behalf in prominent public spaces.
Fast forward to today, and business/institutional storytelling has taken on a life of its own. Whether it is Apple’s groundbreaking Super Bowl television commercial inspired by George Orwell’s “1984”, or Nike's “Just Do It” campaign, everyone from startups to trillion-dollar companies have learned that tying their services and products with an overarching storyline leads to greater profitability, brand recall, and customer loyalty.
As humans, we are hard-wired to love stories. This is why, beyond just sales and marketing, stories are the glue that hold organizations together, enabling them to drive internal communications, articulate leadership’s vision for the business, create a culture of learning, manage stakeholder expectations, and solve problems. There are plenty of examples: From General Electric’s “Work-Out” storytelling workshops where employees share best practices, to Patagonia amplifying its sustainability initiatives through campaigns like “Worn Wear” and “The Footprint Chronicles”, to Google’s “Project Aristotle” which leveraged storytelling to understand and implement the logic behind their most effective teams.
The Evolution of Business Storytelling with Generative AI
We are arguably at another “Gutenberg” moment in our civilization’s history. Generative AI has made it easier to ideate, conduct deep research, dig up historical references, preserve and disseminate knowledge, and align an organization’s narrative to deliver a consistent message to all stakeholders—employees, investors, and customers.
At this point, we are already familiar with Generative AI and its capabilities under different avatars (ChatGPT, Midjouney, etc.). Let’s take a look at some interesting ways in which these capabilities are being leveraged (along with applicable caveats) to redefine business storytelling in today’s world.
Story augmentation with rapid research
Stories are like staircases, built on top of each other. However, the quantity of information that we process in the digital age, can make it difficult to access what we need, when we need it. One of the most powerful uses of Generative AI, that I have discovered, is its ability to instantly present relevant information and data points in an easily consumable format. From generating statistical data and suggesting pop-culture references to recommending case studies that bring your stories to life and to its growing ability to add visual appeal to narratives, Generative AI is an essential assistant.
Personalization with audience segmentation
Segmentation is something usually associated with marketing—and it is an extremely important marketing tool—however, it extends beyond that and into other areas of business as well. Take customer satisfaction, for example. By understanding your customers, their habits, past consumption patterns, and preferences, you can predict the services, offerings, or products they are likely to want. You are at the receiving end of this, every time you opt to watch a new Netflix recommendation. Another spin on this is financial institutions using Gen AI to tailor credit cards to different customer segments, based on credit points, usage history, and risk factors.
Human experiences at scale
If you visit Bond Street in London, many stores will offer you dedicated assistants to help you shop. Despite all of their advantages, this touch of personalization is something eCommerce stores have struggled with replicating—until now. Today, with Gen AI-powered chatbots, forward-looking retailers are offering customers a shopping experience that closely mimics what high-end retail stores offer. Customers visiting the website can talk to dedicated chatbots in natural language and receive an ensemble of products that are closely aligned to their expectations.
We have taken the example of high end retail to illustrate our point, however, customer-centric narratives powered by Gen AI are finding their way to finance, healthcare, and most other verticals.
Knowledge management at speed
According to some estimates, 402.74 million terabytes of data are created every day. A lot of this is created at an enterprise level, meaning that homing in on specific data from this pile could be like finding a needle in a haystack. Companies that are sitting on massive repositories of private data are using Generative AI to solve this problem. Morgan Stanley for instance has a Gen AI Assistant that can quickly search through a repository of 100,000+ documents to find what’s needed. Other companies are also deploying Gen AI in similarly innovative ways to organize their knowledge bases, create single sources of truth to phase out the mundane, and enable their employees to create and drive data-backed, compliant narratives with customers, and other stakeholders.
A culture of collaborative storytelling
If you use Teams or Outlook, you would have noticed a string of new, Gen AI-led enhancements that Microsoft quietly rolled out. From suggesting responses and drafting follow-up emails to highlighting work hours and recommending the best times to meet, Gen AI is accelerating collaboration within organizations. Tools like spatial.io are using AI to enhance virtual collaboration between distributed teams through spatial audio and gestures. They also provide teams with a platform to brainstorm ideas and prototype products which are built onfeedback loops that often have Gen AI-powered customer sentiment analysis under the hood.
Combined with AR/VR, Gen AI-powered translation and localization tools (many of which are already in play) have the potential to enable large, globally distributed teams to come together in ways that are next-best/close to physical collaboration and contribute to the organization’s narrative.
Business storytelling will never be the same
Generative AI has inevitably transformed the effort that goes into building powerful stories, and the means and methods of communicating them. Organizations and their people can now use data and insights to drive highly personalized narratives that directly appeal to their customers. The scale and speed of storytelling has also changed, with Midjourney, Dall-E, and other visual GPTs democratizing multi-modal content, enabling the creation of videos, infographics, and other visual formats through text prompts.
There are caveats of course. The technology is still maturing— AI tends to hallucinate and at the moment, we can’t take anything that is Gen AI produced at face value. However, even as new waves of Gen AI-driven content proliferate in a market that has been struggling with reduced attention spans, individuals and organizations who can effectively leverage Gen AI to create, augment, and communicate their stories, will be placed to succeed. They will find themselves blitzing ahead of competition, and deepening their relationships with stakeholders through personalized narratives.
As humans, we have told stories for millennia using nothing but our imagination and creativity. With Gen AI, our capabilities have received a brand-new, third dimension.
I can’t wait to witness everything we will achieve with it.
