Generative AI (Generated Artificial Intelligence or GAI), is an artificial intelligence (AI) technique which creates original content from images to music to virtual environments. While still under development, Generative AI could potentially revolutionise many industries and businesses.
The World Generative AI in Business Market size was valued at USD 1.2 billion in 2022 and is expected to grow at a CAGR of 33.5% during the forecast period of 2023-2032. It is predicted to reach USD 20.9 billion by 2032.
Generative AI models are typically trained on large datasets of existing content - for instance, books, articles and code may all serve as data input for training a generative text model. Once trained, such models can generate text similar to its source.
Generative AI models can be leveraged for various business uses, including:
- Content Creation: Generative AI can be leveraged to generate fresh blog posts, social media updates and marketing materials quickly and cost effectively - saving businesses both time and money while producing engaging and informative posts that resonate more deeply.
- Product Development: Generative AI can be utilized in product and service development by creating new designs or algorithms for software products or products themselves.
- Customer Service: Generative AI can be leveraged to enhance customer service, such as by developing chatbots that answer customers' inquiries or address issues more efficiently.
- Research and development: Generative AI can be leveraged to accelerate research and development by helping generate hypotheses or test ideas more quickly and accurately.
Although still at a very early stage of its development, generative AI markets are expanding quickly due to a number of factors including:
- Generative AI models require large quantities of training data in order to train effectively; thanks to an increase in both public and private data availability, developing and deploying these AI models has never been simpler!
- Decreasing Cost of Computing Power: Computing costs have steadily been decreasing over time, which makes generative AI models easier and more cost-effective to train and deploy.
- Consumer demand for personalized content and experiences: As consumer expectations for personalized experiences expand, Generative AI technology provides an effective means of creating these customized offerings at scale.
- ?The global generative AI market can be divided into regions, applications and technology types: North America, Europe, Asia Pacific, Latin America and Middle East/Africa are included within each segment while applications range from content creation, customer service delivery to product development to fraud detection/risk evaluation and more. Technology types encompass deep learning natural language processing computer vision.
- North America is currently the dominant market for generative AI technologies, followed by Europe and Asia Pacific. Content creation represents its main application segment while customer service and product development follow in importance. Deep learning technology dominates in this generative AI market segment.
Key Market Drivers in Generative AI Include:
- Data availability: An abundance of both public and private information makes creating and deploying AI models much simpler.
- As computing power costs decrease over time, training and deploying AI models has become more cost effective and affordable.
- Consumer demand for personalized content and experiences: As consumer demands for customized experiences become ever more pressing, AI technology offers an effective means of mass producing unique personalization on an unprecedented scale. Generative AI offers solutions which create tailored material at scale.
Generative AI offers businesses a host of lucrative market opportunities, such as:
- Generative AI can increase revenue for businesses by creating new products and services as well as optimizing existing ones, leading to an increase in revenues and decreasing costs for them. Furthermore, automating tasks using Generative AI may further lower expenses in your operations and ultimately save costs over time.
- Enhance customer satisfaction: Generative AI allows companies to deliver tailored experiences for customers, which in turn increases satisfaction levels among them.
The market for generative AI presents several unique obstacles, including:
- Generative AI models may be biased and cause unfair and discriminatory outcomes. On top of this, their generation may also create synthetic media like deepfakes which could be used for malicious intent.
- Ethics: Generative AI raises ethical considerations that threaten job displacement or misuse for malicious uses, including potential job displacement risks or its misuse for unlawful purposes.
The Future of Generative AI in Business
Generative AI holds immense promise for business applications. As these models evolve and become more cost-effective, more innovative applications for this technology may arise.
Generational AI could have an enormous impact on multiple industries:
- Generative AI can be leveraged for marketing and sales applications alike; such as creating personalized campaigns, targeting ads to specific demographics and producing engaging content. When applied in sales context, Generative AI is capable of qualifying leads, personalizing sales pitches to leads and automating the selling process - among many other applications.
- Generative AI can be utilized in product development to design new products, prototype them and test concepts before their actual implementation. Generative AI may also provide personalized customer support or automate existing processes by automating routine support procedures. Likewise for customer service Generative AI offers benefits in providing personalized support services while automating these services more effectively for automated processing.