Today, Generative Artificial Intelligence (GenAI) is redefining the horizons of what businesses can achieve with technology. From creating innovative designs to formulating marketing strategies, GenAI is at the heart of digital transformation. According to Gartner predictions, by 2025, generative AI will produce 10% of all data (now less than 1%) and 20% of all test data for consumer-facing use cases. Furthermore, 50% of new medicine discovery and development initiatives will use generative AI by 2025. Additionally, 30% of manufacturers are expected to use the technology to improve the efficiency of their product development by 2027. The market for GenAI is expected to grow significantly, from USD 14 billion in 2020 to nearly USD 900 billion in 2023 and more than USD 1.3 trillion in 2032. This is due to an explosion of generative AI tools in recent years such as Google’s Bard, OpenAI’s ChatGPT and Midjourney from Midjourney, Inc. However, their implementation comes with a number of challenges that require innovative solutions.
GenAI challenges
One of the main challenges is insufficient data. The quality of the answers given by the GenAI is deeply related to the quantity and quality of the available data. Companies often face the challenge of gathering enough relevant, reliable and diversified data to train robust models.
Another significant problem is the associated bias and ethical dilemmas, as well as the importance of responsible data use. GenAI can perpetuate or even exacerbate biases present in training data. This poses serious ethical dilemmas and reputational risks for companies.
In addition, the high costs associated with data acquisition, computing infrastructure and specialised talent can be prohibitive for many companies.
And let’s not forget about the impact on the ESG efforts – the carbon footprint of the computational process in both the training and inference phase of the models. Interpretability and control are also crucial concerns. The «black box» nature (i.e. functional relationships between inputs and outputs are described, but it is difficult to know their inner workings) of some generative models can make it difficult to interpret their decisions, which in turn affects the ability to maintain control over automated systems.
Further compounding these challenges, companies often find the adoption and integration of new technologies lagging behind due to the skill gaps within business and technology teams. Upskilling and reskilling are vital to bridge this gap and enable teams to effectively utilize and implement GenAI solutions.
Industry applications
Despite these challenges, GenAI is catalysing a revolution in multiple industry sectors, providing solutions to complex problems. Next, we will focus on some industry sectors based on a Mckinsey report.
Banking and Insurance Industries
In Banking, the evolution of GenAI has allowed processes to be automated, such as: credit approvals with chatbots, delegating the process in a generative way, as well as having a better credit evaluation through risk measurement by analyzing the governed sources (tables). Additionally, in collection processes you can identify delinquent clients to offer payment options as appropriate collection strategies.
Insurers play a crucial role and that is why they have taken advantage of GenAI from different perspectives focused on improving the business. The main advantages are the use of GenAI to summarize texts and conversations where it is possible to customize domains for policy documents, generate answers to questions automatically. Additionally, other approaches are the classification of texts corresponding to complaints, customer opinions, etc. Extraction of medical diagnosis information as a priority in risk assessment and improvements in operational efficiencies through automation in the use of GenAI.
Marketing and advertising application
GenAI is revolutionizing the marketing and advertising industry, enabling companies to forge deeper connections with their audiences through personalized content and campaigns, as exemplified by Coca-Cola’s Christmas initiative. This technology extends beyond content creation, providing real-time, personalized customer interactions through chatbots and virtual assistants, enhancing user engagement significantly. Additionally, GenAI aids in generating high-quality, consistent written and visual content, ensuring that brand messaging is coherent and visually appealing across various platforms.
Moreover, GenAI’s predictive analytics are reshaping marketing strategies by anticipating customer behaviors and trends, allowing for more tailored and proactive approaches. The personalization capabilities of GenAI enable content customization at an unprecedented scale, increasing engagement and conversion rates. It also plays a crucial role in market research, SEO optimization, and ad targeting, optimizing marketing efforts and maximizing ROI. As such, GenAI is not just transforming customer interaction but also driving innovation in product development, market strategy, and overall business growth, establishing itself as an invaluable asset in the dynamic field of sales and marketing.
Health and R&D
The global GenAI in the healthcare market was valued at $1.07 billion in 2022 and is estimated to reach around $21.74 billion in 2032, growing at a healthy compound annual growth rate of 35.1% between 2023 and 2032. This growth is driven by GenAI’s ability to expedite drug discovery and enhance medical diagnostics through its sophisticated analysis of extensive datasets, identifying potential therapeutic compounds and discerning disease patterns in medical imagery. In material science, GenAI demonstrates its prowess by generating crucial materials data, such as creating detailed Crystallographic Information Files and assisting in complex differential equation solutions, crucial for numerical modeling. This enhances accuracy and efficiency in research, particularly in simulations involving spintronic devices and dendrite growth analysis. Moreover, GenAI’s applications extend into other R&D sectors like environmental science for climate modeling, engineering for optimized system designs, and agriculture for improved crop yield predictions and resource management. Overall, GenAI is emerging as an indispensable tool across various industries, driving innovation and advancement in research and development.
Entertainment and art
Generative AI is significantly influencing the entertainment and gaming industries, revolutionizing content creation and enhancing user experiences. In entertainment, GenAI aids in scriptwriting, dialogue creation, and plot generation, speeding up the creative process. It personalizes user experiences, tailoring music and movie recommendations to individual preferences. Notably, AI programs like AIVA, Harmonai, and Soundful assist musicians in composition and accompaniment generation. The film and TV industry benefits from AI in visual effects enhancement and scene creation, with the Museum of Modern Art (MoMA) incorporating AI-generated artwork into its permanent collection, showcasing its artistic impact.
The gaming industry, valued at $922 million in 2022, is expected to reach $7.105 billion by 2032, with a CAGR of 23.3%. GenAI in gaming automates level and world creation, enriches NPC behavior, and adjusts game difficulty based on player skill. Tools like plask.ai, radicalmotion, deepmotion, and kinetix enhance animations, while armorlab, ponzu, kaedim3d, blockadelabs, and spline.design streamline the creation of textures and 3D models. GenAI also enables real-time dialogue generation and complex story crafting in narrative games. However, advancements like deep-fakes and voice synthesis present ethical challenges. The trajectory suggests a growing influence of GenAI in providing rich, personalized entertainment and gaming experiences.
The ascendancy of GenAI across diverse sectors, from healthcare and material science to marketing, advertising, and entertainment, underscores a transformative era in industry innovation and customer engagement. While the broad application and potential of GenAI fuel high expectations, it’s crucial to navigate this landscape with a balanced perspective. The substantial market growth projections and the profound impacts already visible in content creation, personalized marketing, and R&D innovation reflect a promising future. Yet, alongside this optimism, the industry must address the accompanying challenges (data sufficiency, ethical considerations, security and the integration of new technologies) prudently. As GenAI continues to shape the future of industries, the collective goal should be to harness its potential responsibly and innovatively, ensuring sustainable growth and value creation in this AI-driven epoch.
Author: Santiago Pineda Montoya, representative of Stratio BD – generative AI for enterprise – as an Official Expert of GENAIA
Co-author: Federico Caro, Official Expert of GENAIA