Free DownloadWhat is generative AI? Everything you need to know
The potential of AI technology has been percolating in the background for years. But when ChatGPT, the AI chatbot, began grabbing headlines in early 2023, it put generative AI in the spotlight.
This guide is your go-to manual for generative AI, covering its benefits, limits, use cases, prospects and much more.
This rapidly evolving artificial intelligence field has the potential to help organizations quickly generate content, improve customer service and develop new products.
People use generative AI models to conduct searches, create art, compose essays and make conversation -- polite and otherwise. But how can businesses tap into these powerful tools to address real-world business needs?
Generative AI, as its name suggests, can produce images and text. This subset of artificial intelligence (AI) can also generate synthetic data. The technology builds on several developments, including generative adversarial networks and large language models that potentially include trillions of parameters.
Such advances let data scientists prep models using vast amounts of training data, offering the following seven generative AI benefits for business.
1. Create content on the fly
Rapid content creation ranks among the more obvious advantages of generative AI. It's also among the most immediately accessible, noted Arun Chandrasekaran, vice president, analyst, tech innovation at Gartner. The ability to generate content, such as marketing newsletters and blogs, provides tangible value today.
Gartner expects the media industry and corporate marketing to use generative AI for text, image, video and audio generation. Thirty percent of large organizations' outbound marketing messages will be synthetically generated by 2025, according to the market research firm. Only about 2% of organizations created such content in 2022.
2. Improve the customer experience
Customer interaction seems another likely early business application for generative AI. Businesses can benefit from employing chatbots that offer a more human-like response to customer inquiries. And those responses will have greater depth due to the scale of the underlying language models.
A business may deploy generative AI tools in self-service mode to handle customers' routine inquiries. But industry executives also see generative AI bots playing an agent-assist role in customer service, using natural language processing to listen to an agent's discussion with a customer and tapping relevant resources to support the interaction.
"Imagine a situation where ChatGPT is listening to a call and is now actively grabbing content from repositories to help the customer service agent provide better service," said Pablo Alejo, partner at consultancy West Monroe. "That radically shapes how they operate."
Generative AI will find its way into many business functions.
3. Boost personalization
Generative AI could help businesses step up their personalization game. Machine learning algorithms can analyze a user's purchasing history and online behavior to improve product recommendations or generate custom content. Salespeople, meanwhile, can create personalized presentations, and marketers can hone their campaigns.
Organizations might also benefit from improved personalization for employee training. Bill Bragg, CIO at enterprise AI SaaS provider SymphonyAI, suggested generative AI could serve as a teaching assistant to supplement human educators and provide content customized to the way a student learns.
4. Develop new products and accelerate design cycles
Businesses also stand to benefit from rapid ideation and the ability to create new products and services. Generative AI has the potential to accelerate development in industries such as pharmaceuticals where drug discovery can take a decade or more. Chandrasekaran cited the ability to launch products -- and shrink R&D timelines and budgets in the process -- as among the use cases offering the greatest potential.
Imagine a situation where ChatGPT is listening to a call and is now actively grabbing content from repositories to help the customer service agent provide better service.
Pablo AlejoPartner, West Monroe
At the same time, privacy issues, complex business processes and the nascent state of the generative AI ecosystem place product creation among the toughest use cases, Chandrasekaran said. Hyper-personalization also falls into that category, he added.
5. Improve task efficiency, from writing code to contract management
Machine learning models can suggest application code to increase developer productivity. ChatGPT, for instance, can help with website development, code in languages such as JavaScript, and debug code.
But generative AI could streamline other complex processes as well. Bragg pointed to the example of a software vendor's deal desk, a cross-functional group that manages the quote-and-proposal and contracting process. Currently, the task of co-terming contracts -- combining multiple contracts for products or services into a single vehicle -- might involve numerous conversations between a vendor's deal desk and a customer.
A deal desk using generative AI, however, could gather data on a customer's different licensing models, scattered across several business units, Bragg noted. An AI agent who has digested that data -- and learns from it -- can give the deal desk a head start when co-terming contracts.
Absorbing tedious chores could well become a hallmark of the technology's business applications. "Generative AI has the ability to abstract lots of low-level tasks away from business users, thereby freeing up valuable time for them and unlocking productivity," Chandrasekaran said.
6. Facilitate client services
Industries with a strong client-service focus, such as consulting, could benefit from generative AI. Alejo cited the technology's ability to absorb research data on a given subject, run it through a model and identify high-level patterns. With that insight, an advisory firm could kickstart the process of creating business strategies for clients.
AI tools will pop up "any place where knowledge management is crucial, where you have a corpus of information that can be accessed [and] where we can streamline the process of seeking information," Alejo said. Building on this initial use case, he noted, later advances will focus on generating insight from the information.
Chandrasekaran said interest in conversational AI-led enterprise search and knowledge management systems is surfacing in healthcare, financial services and legal. In such industries, he added, generative AI "has the potential to democratize institutional knowledge."
