Chapter 1. Why embed GenAI in applications

Marketplace hype and the pressure to get GenAI into apps often obscure the answer to common business leader questions: Why do we need GenAI? How do we bring GenAI into our business?

McKinsey’s answer is that bringing generative AI into business strategically can result in automating 70% of tasks that waste valuable employee time.¹ Boston Consulting Group explains that GenAI enables companies to create content and information tailored to a specific audience, such as chatbots that personalize customer experiences or targeted advertisements based on patterns in a specific customer's behavior.²

These are good answers to the question of why you should integrate GenAI into your business. For the “how,” here’s a simple answer: By embedding generative AI in your apps for the right use cases, you make tangible improvements in efficiency, innovation, and engagement that can significantly benefit your business. And the sooner you do it, the better—if you want to stay ahead of your competition.

The benefits of adding GenAI to apps

GenAI can enhance customer satisfaction and help you maintain a competitive advantage by making personalized recommendations or responding to questions using natural language in real-time. GenAI can also automate routine tasks like updating project management tools or generating visualizations in dashboards to increase efficiency and productivity. As a result, employees can focus on guiding an initiative to its successful completion or deriving insights that inform strategies from the dashboard.

GenAI also drives innovation by quickly presenting new ideas and solutions, offering insights and options that might not be immediately obvious to human thinkers. Moreover, when generative AI is embedded throughout operations, your company can scale efficiently. GenAI makes it possible to handle increased workloads without a proportional increase in staff, which is invaluable during workload fluctuations or business expansion into new markets.³

Where GenAI apps are making the most impact

There are a multitude of use cases for embedding generative AI into applications. This is because, when you deconstruct GenAI, it falls into one (or more) of four main patterns–content Q&A, content deconstruction and summarization, content transformed from other sources, and data Q&A. It’s possible to do all kinds of things with these patterns that can search reams of code, content, or data and produce working content or code, but like all technology, there are top GenAI use cases.

According to TechTarget and Enterprise Strategy Group, organizations across all industries that have already deployed GenAI are currently using it in an average of three areas. The top areas are marketing, software development, and research.⁴ According to a Deloitte survey, there is a fourth area, customer service operations.⁵

Generative AI for marketing

Companies use generative AI applications in marketing for a variety of purposes. 76% of marketers use it for basic content creation.⁶ GenAI is currently helping improve the design and copy of landing pages and supporting the creation of more engaging content for websites. With GenAI embedded in the tools they use every day, marketers can identify trends and customer behaviors more quickly. As a result, they can make smarter, data-driven decisions about ad targeting, consumer preference prediction, and audience segmentation.

Generative AI for research

Generative AI is ushering in a new era in research—whether it’s medical, academic, or product R&D. It is being used in applications to detect when it’s time to harvest, repair damaged artifacts by surfacing missing text, and even communicate with whales.⁷ A biotech pharmaceutical company has paired generative AI with automated synthetic development tools to design small-molecule therapeutics.⁸ There are platforms for academic and scientific researchers that use GenAI to curate a customized repository to assist with literature review. Spending countless time and effort on data collection is now off their plates, so they can focus on analysis.

Generative AI for customer service operations

GenAI embedded in CRM, help, and support systems is changing how companies engage with customers. It is helping organizations ensure their customers get the support they need, lightening the burden on agents and call centers, and meeting consumer’s increased expectations for real-time and consistent experiences across channels. One company has used a GPT API to create a platform that filters communications received by customer service, removes spam, and sends legitimate ones to customer service agents.⁹

GenAI in software development

GenAI is streamlining code generation, enhancing creativity, and accelerating time-to-value. For example, GitHub Copilot has reduced development time by up to 56%.¹⁰ By automating code generation and refactoring, GenAI shifts the focus of software engineering to higher-level design and architecture that tackle complex problems and drive innovation.

There is little doubt that GenAI-powered apps and software development are the future. They promise multiple benefits and enhance numerous use cases—some of which can’t be identified right now because GenAI also has the potential to invent all new use cases and benefits. So, it’s time to break down what it takes to build these apps. The rest of this ebook dives deep into the effect of GenAI and AI on software development–what and how GenAI apps are developed, how to use GenAI and low-code together, and what this means for the future.