Enhancing your workflows and building out your experience with the correct generative AI touches boosts engagement rates by making every conversation in every channel as contextual as the customer needs at any scale your operations require. These experiences leverage and enhance your existing workflows and data, meaning no disruption on either side of the counter, and can be built using no-code tools that bring every relevant party into the flow design discussion.
That leads to faster agent programming and guardrails that ensure generative conversations always move in the right direction. On the customer's side, the tool looks like the chatbots they've already come to utilize, but on the backend, there's more potential to resolve issues and keep the customer engaged throughout the entire interaction, whatever brought them there in the first place.
What Is Generative AI for Business?
You're likely familiar with language-based generative AI systems, like ChatGPT, and image generation tools, such as Midjourney, two of the more prominent examples of generative AI. True to the name, technology under this category generates text, video, and other all-new content — anything from emails and movie scripts to full-blown videos with sound — by learning from huge troves of similar content humans have created.
Generative AI can be used to solve a number of internal problems and enhance a number of internal roles, leaning on the same strengths. In the technology realm, generative tools are used to help advise on procedural updates and make improvements to code, for example.
How the Impact of Generative AI Will Transform Business
In terms of business impact, the answer to, "What is generative AI?" is: "A little bit of everything." Generative AI's big hook is it can be reactive in ways technologies that came before it simply can't be. Think of the difference between dialing prompts into a touch-tone IVR in the '90s and speaking to a chatbot that's so real it seems human today, and you can immediately see the difference.
On some level, it all comes down to output. The key here is what's being put out — on-the-fly customer service conversations and immediate but deeply personalized account benefits, for instance. Generative AI enables businesses to bridge the gap and build out the experience all at once with a technology that sequentially improves by learning from its own mistakes and successes.
Even in this early stage in the technology's life, experts like McKinsey say it could boost the global economy by up to $4.4 trillion annually; Goldman Sachs says it could increase the global GDP by $7 trillion and boost productivity growth "by 1.5 percentage points over a 10-year period." Suffice it to say, there's a lot of potential tucked away in this emerging new business powerhouse.
Benefits of Generative AI for Business
What is generative AI, and what is its potential in your business environment? Let's look at the high-level points first.
Generative AI for Enterprise
Large businesses with existing customer- or agent-facing AI tools naturally have a lot of investment in the solutions they're currently using. Because it shores up existing tools and processes with new knowledge and learning capabilities, that gives the enterprise a distinct advantage with generative AI: They can build out what their large customer bases are already used to and take advantage of what they currently have, overcoming the inertia that sometimes slows large-scale tech adoption.
Generative AI for Midsized Business
At the mid-sized level, companies can lean on generative AI to create content and interactions at high quality, rapid scale, and in natural language. Scaling the experience while reducing costs is the kind of win-win growth any company can get behind, but especially one looking to differentiate — a key point for many mid-sized businesses.
Generative AI for Small Business
While small businesses run at a fraction of the operational complexity of an enterprise, there's something to be said for a solution that can introduce all-new capabilities — from chatbot responses onward — without disrupting what the company already does best. Since generative AI technology is typically hosted in the public cloud, smaller companies can pick, choose, and use what they want without over committing to or overinvesting in on-premises solutions to make it work.
Generative AI Use Cases for Business
Businesses can use AI for customer service, customer experience, and much more. Generative AI is especially promising for contact centers and call centers, where it can be used to build conversational AI applications, like AI chatbots.
1. Text Content Generation
Let's say a growing sales-based company needs to do more email volume. With a properly trained AI, emails can be prompted and then refined by humans, with the AI producing the content itself. The same idea goes for blog posts, social updates, and other content companies might have trouble producing at quality and scale.
2. Customer Service
Technologies like chatbots are powered by generative AI and are getting better at resolving complex but ultimately deflectable service issues — think: complex order inquiries and the like. These tools can be trained to speak with the sentiment and general tone a company wishes to provide and respond on the fly as though they were a regular agent, freeing humans to manage more complex issues in the contact center.
Product recommendations, ad targeting, and personalized messaging are just three examples of the personalized experiences businesses can more easily provide at scale with generative AI tools. A generative AI can pull from numerous disparate sources — browsing history, purchase history, and abandoned carts — and work within the rules you define to make sure every customer gets the experience they're after, even if the notion varies quite a bit from individual to individual.
Companies lacking the internal skill sets to speak every language within their customer base can use AI to round out their communications. For example, companies routinely use generative AI to translate landing pages, product pages, sales emails, and other content.
5. Customer Segmentation
Companies can use their segmentation findings to train generative AI solutions, which can be used to target content down to the individual level. As an example, a company serving three verticals might use business insights they've trained an AI with to tailor a prewritten blog post to multiple professional types in each field.
6. Feedback Enhancement
Generative AI technology can read data provided by other generative AI systems and provide feedback that makes effective coaching easier. In an environment like the contact center, an AI customer experience tool could monitor sentiment and use that data over time to inform on-the-fly pep sessions, the stats for which the customer can see on a dashboard — which the AI is already connected to.
Unlock the Power of Generative AI With Vonage
If you're ready to get started with AI-enhanced conversation workflows now, check out Vonage AI Studio.