Chapter 1. Why embed GenAI in applications
Table of Contents
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 value of GenAI in applications
GenAI has the potential to add $2.6 trillion to $4.4 trillion annually in value across 63 use cases that include interactions with customers, producing creative content for marketing and sales, and drafting computer code based on natural-language prompts. When 822 business leaders whose companies have added GenAI to apps were surveyed in 2024, the leaders reported, on average, a 16% revenue increase, 15% in cost savings, and a 23% improvement in productivity.
Sources: McKinsey & Co. and Computer World
The benefits of adding GenAI to apps
GenAI can enhance customer satisfaction and help you maintain a competitive advantage by making personalised recommendations or responding to questions using natural language in real-time. GenAI can also automate routine tasks like updating project management tools or generating visualisations 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.
Examples of generative AI apps
Every week, the RundownAI newsletter highlights the latest GenAI applications. Here’s a sample:
- Twain: A communication assistant that helps users write clear, convincing, and confident outreach messages that get answers
- Jasper AI: A GenAI writing tool designed for bloggers, marketers, and businesses
- Canyon: Searches for jobs using AI
- Elicit: Analyses, searches, and extracts research papers
- fynk: Creates, reviews, tracks, signs, and analyses contracts
- IntelSwift: Automates customer service with AI technology
- Open Interpreter 01 Lite: Controls work and home computers with a voice interface
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 summarisation, 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, organisations 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 behaviours 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 artefacts 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 customised 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 organisations ensure their customers get the support they need, lightening the burden on agents and call centres, 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
Brands that have embedded GenAI into their applications
Walmart
Walmart’s shopping app uses generative AI to offer a single place to search by use case, such as planning a party, so consumers don’t have to search for individual items.
Allstate
ABIE is a GenAI chatbot on the Allstate website. It can answer consumer questions about their products using natural language processing and understanding.
Coca-Cola
Coca-Cola is offering an immersive GenAI-powered consumer experience, Y3000, that enables users to generate futuristic images and videos through the Coca-Cola Y3000 AI Cam.
Estee Lauder
Estee Lauder’s GenAI chatbot conversationally consults its product database and information for data that its marketing teams use to quickly create new campaigns relevant to different locales.
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 guide 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.
Useful resources
Gartner® Emerging
Tech Impact Radar
Explore Gartner's in-depth analysis on Generative AI.
AI Adoption in Software
Development: Report Insights
How enterprises are navigating AI adoption and implementation.
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1 The economic potential of generative AI: The next productivity frontier, 2023. McKinsey & Company, 14 June.
2 Generative AI, 2023. Boston Consulting Group.
3 The economic potential of generative AI: The next productivity frontier, 2023. McKinsey & Company, 14 June.
4 Beyond the GenAI Hype: Real-world Investments, Use Cases, and Concerns, 2023. Tech Target and Enterprise Strategy Group.
5 Sarah K. White, 2 most popular AI use cases in the enterprise today, 2023. CIO, 19 Sept.
6 Scott Vaughan, GenAI for Content Marketing: Benefits, Best Practices, and Pitfalls to Avoid, 2024. Acceleration Economy, 8 Feb.
7 Molly Bell, How generative AI is expanding what is possible in research, 2024. EAB, 17 Jan.
8 Iambic’s Rapid Path to the Clinic Enabled by Its AI-Driven Drug Discovery Platform, Built in Collaboration with NVIDIA, 2024. Iambic, 18 March.
9 Sarah K. White, 12 most popular AI use cases in the enterprise today, 2023. CIO, 19 Sept.
10 Sida Peng, Eirini Kalliamvakou, Peter Cihon, Mert Demirer, The Impact of AI on Developer Productivity: Evidence from GitHub Copilot, 2023. Cornell University, 13 Feb.
Originally published on OutSystems.com
