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The Generative AI Evolution: Emerging Trends and Applications Across Industries

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“It’ll be unthinkable not to have intelligence integrated into every product and service. It’ll just be an expected, obvious thing.” – Sam Altman, co-founder and CEO of OpenAI.

Generative AI (GenAI) has expanded the horizons of innovation and challenged us to rethink the potential of workflows, efficiency, and intelligence. Yet, its evolution is young and ongoing. The possibilities seem endless, with big players like Microsoft, OpenAI, Google, and Meta investing heavily in advancing GenAI.

But how does sentient evolution impact businesses? As Altman said, it would be unthinkable not to have smarter products and services during this reinvention, especially since it could generate trillions in value. McKinsey [1] identified 63 ways generative AI could be applied across 16 business functions, potentially unlocking $2.6 trillion to $4.4 trillion in annual financial benefits.

Let’s take a closer look at GenAI trends and use cases that will shape 2024 and beyond.

Emerging Trends Shaping the Future of GenAI

The past year has been a breakthrough for GenAI, especially with OpenAI’s ChatGPT, inviting real opportunities for the public to experiment. 2023 also saw the explosion of general-purpose AI applications, with enterprises gearing up for a cognitive shift.

GenAI applications initially started by recognizing patterns in customer demands, creating personalized marketing strategies, and summarizing lengthy text documents. As improved models arrived, the usage has expanded to aid in personalizing medical treatments, streamlining insurance underwriting, and enhancing inventory and supply chain management.

Notably, GenAI has made significant advancements in various fields despite being in its early stages, proving its potential. Here is a glimpse of what might come next:

  • The popularity of multimodal models

    While transformer models have been the backbone of recent GPT and DALL-E AI successes, we now witness the emergence of advanced neural architectures. These sophisticated structures optimize information processing in AI systems beyond traditional models.

  • Apple’s newly introduced MM1, a more advanced multimodal AI model, can process and generate both visual and text data. It’s also pre-trained to offer in-context predictions – allowing it to tally objects, adhere to customized formatting, identify sections of images, and execute OCR tasks. Moreover, it demonstrates practical understanding and vocabulary related to everyday items and the ability to conduct fundamental mathematical operations.

    Evidently, multimodal Generative AI holds immense potential for shaping the user experience across various sectors, from scientific research (think analyzing complex datasets with visual and textual components) to social sciences (enabling richer analysis of human interactions). Once realized, this can significantly impact industries. For example, in a modern insurance workplace, a multimodal approach could help improve training and development modules for customer service representatives. In this case, training modules could incorporate role-playing scenarios with branching narratives based on past customer responses, allowing trainees to practice their communication skills in a simulated environment.

    Similarly, in the healthcare sector, multimodal AI is poised to transform diagnosis, treatment and patient care. By merging text and visual data from EHRs, medical images, genetic profiles, and patient-reported outcomes — intuitive healthcare systems can forecast disease likelihoods, assist with interpreting medical images, and customize treatment plans. This will allow practitioners and professionals to augment the quality of care and improve outcomes in a timely order.

  • The rise of autonomous agents

    2024 will be the breakthrough year for autonomous agents. Gartner’s predictions affirms this — their report indicates that by 2028, about one-third of interactions with Generative AI services will be marked by heightened autonomy, propelled by the fusion of action models and autonomous agents.

  • Another report [2] revealed that 96% of global executives believe ecosystems built around AI agents will be a primary growth driver for their organizations in the next three years.

    It all started with AutoGPT’s arrival in 2023 and has been developing since, with others like Microsoft, UiPath, and OpenAI joining the autonomous AI revolution. These GenAI applications are trained to instantaneously generate and respond to prompts for tackling complex tasks without manual intervention. Unlike traditional chatbots, which wait for the next manual instruction, autonomous agents are proactive, constantly learning and adapting.

    This will be a game-changer for retail, banking, healthcare, and insurance industries, where quick interactions are the key to sustained success and better outcomes. For example, OpenAI, the maker of ChatGPT, is working on a category of autonomous AI agents that manage online tasks like booking flights or crafting travel plans without relying on APIs. Currently, ChatGPT can perform agent-like functions, but access to the appropriate third-party APIs is required.

    This will transform how travel enterprises operate, helping them to streamline operations and speed up customer service.

  • GenAI ventures into education

    While the resistance was strong at first, the educational sector is slowly opening up to the GenAI intervention — with labor shortages wreaking havoc [3] across the global sector. To reduce the burden on teachers, GenAI tools can be deployed to optimize course planning and curriculum delivery.

  • With its potential to synthesize large volumes of data, it is also suited to develop a customized syllabus and curate a list of potential reading materials for students — while also assisting with drawing detailed lesson plans based on historical data.

    Additionally, GenAI can be primed to improve student outcomes. For example, predictive systems can proactively identify at-risk students who require early interventions. Educators can use this information to personalize their approach for targeted students and even help them with customized course materials to improve their performance.

    It is also a critical tool in today’s environment for empowering students and ensuring they’re future-ready. A leading technology company recently partnered with eight UGC-funded universities to advance the integration of AI and enable the use of Generative AI through their OpenAI service. This technology will be accessible to professors, teachers, researchers, and students across the academic, research, and operational sectors of these institutions.

    Through this, the universities plan to revolutionize their teaching and learning modules and ensure that students are equipped with the required AI skills for their academic and professional journeys.

  • Emergence of personalized marketplace experiences

    Personalized marketplaces powered by Generative AI are projected to be a big hit in 2024. GenAI uses extensive customer data to draw insights into demographic information, previous buying history, behavior, and preferences. These insights can be used to personalize product recommendations on the go, answer customer queries in real-time, customize product descriptions, and deliver targeted communication over marketing channels — essentially creating a personalized marketplace.

  • For example, Amazon, a leading global e-commerce platform, is currently testing an AI tool that can respond to shoppers’ inquiries about products. Embedded within Amazon’s mobile application, this GenAI addition will promptly address users’ queries about a particular item by extracting insights from a range of product reviews and the item’s listing, providing answers within seconds of being asked.

    Gartner predicts that this shift will be driven by information overload. By 2025 [4], 80% of sales interactions will happen online, and customized marketplaces powered by GenAI are poised to become the go-to platform for digital transactions, offering buyers an integrated way to connect with the perfect solutions.

    If untapped, product leaders will risk missing out on potential customers — by not offering powerful and unique digital experiences, driven by GenAI and emerging technologies.

Into the AIverse: Three Rules to Stay Ahead

  • Change is inevitable:To fully leverage GenAI’s advantages, businesses need to adopt a flexible mindset and be responsive to change. This can be achieved by integrating GenAI into their organizational vision, increasing awareness and knowledge amongst employees, and hiring AI experts to assess their company’s possibilities and accelerate the implementation process.
  • Data is key:Your data is a strategic asset and is key to gaining valuable customer intelligence. To make the most of your GenAI transformation, enterprise leaders must break down information barriers within their organization and establish digital threads that connect data.
  • Embrace continuous learning:Evidently, GenAI is still in its evolutionary phase. Like GenAI models, enterprises must continuously learn and improve by paying closer attention to user feedback and product & service successes and failures.

No longer an option

Generative AI is no longer sci-fi. It’s real, with very tangible benefits and outcomes. As the ripples of this cognitive intelligence can be felt across industries, enterprises can no longer afford to be reactive adopters. It calls for immediate action to embrace this technological and cultural change to stay relevant, innovate smarter products, supercharge customer experiences, and simply stay ahead of the competition.

However, as GenAI continues to evolve, one thing is certain: the future promises exciting possibilities.


Rajeev Bhuvaneswaran

Vice President, Digital Transformation and Innovation Services









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