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.

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.

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.

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.