Emerging trends in Artificial Intelligence (AI), digital transformation & the impact of AI on industries. 

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Industry insights

The power of AI's transformative impact is reshaping industries, economies, and the global workforce. The definition from PwC’s report highlights AI's capacity to sense, learn, and act autonomously, mimicking the cognitive processes of humans but on a much larger scale. As AI becomes integrated into everyday business and personal use, its potential to drive economic growth and productivity is immense.  

The World Economic Forum predicts that AI could add a massive $15 trillion to the global economy by 2030.  As humans and machines work more closely together and AI innovations move out of the research lab and into the mainstream, the transformative potential is staggering.  The biggest economic gains from AI will be in China (26% increase in GDP in 2030) and North America (14.5% increase), totalling $10.7 trillion and accounting for nearly 70% of the global economic impact.

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Emerging trends

The intersection of AI and digital transformation is reshaping industries, driving innovation and creating new business models. Organisations that adapt to these trends can increase their competitive edge, improve operational efficiency and deliver better value to customers. As these technologies continue to evolve, staying informed and agile will be critical to success.

IBM recently identified multimodal AI as a key AI trend for 2024. Multimodal AI (MM AI) - a machine learning (ML) model that can process and integrate information from multiple modalities, or types of data. These modalities can include text, images, audio, video and other forms of sensory input.  

Note: AI and ML are not the same - there is a big difference. AI is present in a variety of applications that mimic humans, while ML enhances the reasoning power of such applications. AI is simply a broader concept.

MM AI is a rapidly evolving field, with several key trends shaping its development and application. Notable trends include:

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Unified models

OpenAI’s GPT-4 (Vision), Google’s Gemini, and other unified models are designed to handle text, images and other data types within a single architecture. These models can understand and generate multimodal content seamlessly.

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Enhanced cross-modal interaction

Advanced attention mechanisms and transformers are being used to better align and fuse data from different formats, leading to more coherent and contextually accurate outputs.

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Real-time multimodal processing

Applications in autonomous driving and augmented reality, for example, require AI to process and integrate data from various sensors (cameras, LIDAR and more.) in real-time to make instantaneous decisions.

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Multimodal data augmentation

Researchers are generating synthetic data that combines various modalities (for example., text descriptions with corresponding images) to augment training datasets and improve model performance.

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Open source and collaboration

Initiatives like Hugging Face and Google AI are providing open-source AI tools, fostering a collaborative environment for researchers and developers to advance the field.

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The impact of AI in the financial, educational and robotics sectors

Finance 

Financial entities such as fraud.net  is a cloud-based platform that harnesses AI to provide proactive fraud detection and blocking in real-time, assist with customer onboarding, and workflow monitoring. The solution provides actionable insights in real-time. You can customise and configure rules and policies to suit your company’s needs.

Evident, an AI benchmarking and intelligence platform that assesses the AI maturity of 50 of the world's largest banks through a combination of extensive manual research, automated data collection from public sources, consultation with a network of AI experts, and ongoing dialogue with the featured banks, has listed the banks that are winning the AI race today.  

Leading the pack is JPMorgan Chase. According to Evident's AI index, the American investment bank continues to "radically outperform" the broader market in AI research, maintaining its position as the banking leader in AI innovation. 

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Education 

AI has divided the higher education sector into enthusiasts and sceptics, with the integration of AI into higher education offering promising outcomes such as personalised education, automation of administrative tasks and improved efficiency discussed at the Digital Universities Europe (DUE) event in 2023. The biggest challenge for higher education institutions in taking advantage of generative AI is knowing where to start and defining a strategy. 

In the digital era, investing in the right technology to support the entire student ecosystem has never been more important to support future intelligent experiences that enable greater student outcomes. Delegates at the DUE uncovered holistic digital transformation and data strategies to improve the student experience and teaching support.

The Sorbonne University has established itself as an influential player in the field of AI research on a global scale: in France, the Sorbonne University is the third most prolific institution in the field of AI, contributing 8% of national publications. This performance puts it in about 20th place in Europe. And if we restrict the analysis to institutions that have published at least 50 articles, the Sorbonne University ranks first in France, fourth in Europe and around 30th in the world.

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Robotics 

The broad definition of robotics is the engineering and computer science that builds machines to perform programmed tasks without further human intervention.  Robotics and artificial intelligence are two very different things.  However, both can co-exist.  

A senior contributor to Forbes talks about the growing influence of robots on the automotive industry. Recent developments have extended their capabilities far beyond the manufacturing floor for 3 main reasons:

1. Embedded or 'edge' computing has become much more powerful, allowing us to run more advanced AI and computer vision algorithms on the robot. The ability to use cameras helps keep costs down compared to other, more expensive sensors, and at the same time these computing systems have become much more energy efficient. 

2. Cellular connectivity such as LTE has become an important factor. While robots can navigate largely autonomously, there are rare scenarios where a human operator needs to help remotely. 

3. With the huge increase in e-scooters and e-bikes, which has created a much more cost-effective supply chain for micro-mobility components such as motors and battery systems.

In 2021, Amazon announced Astro, the home robot.   In 2024, there is cobot - the human-robot collaboration that has earned its place in the marketplace thanks to rapid advances in sensors, vision technologies and intelligent grippers that allow robots to respond to changes in their environment in real time, enabling them to work safely alongside human workers. Cobots offer a new tool for human workers, relieving and supporting them. They can assist with tasks that require heavy lifting, repetitive motions, or work in dangerous environments.

The range of collaborative applications offered by robot manufacturers continues to expand.

A recent market development is the increase of cobot welding applications, driven by a shortage of skilled welders. This demand shows that automation is not causing a labour shortage but rather offers a means to solve it. Collaborative robots will therefore complement – not replace – investments in traditional industrial robots which operate at much faster speeds and will therefore remain important for improving productivity in response to tight product margins.

New competitors are also entering the market with a specific focus on collaborative robots. Mobile manipulators, the combination of collaborative robot arms and mobile robots (AMRs), offer new use cases that could expand the demand for collaborative robots substantially.

Multitasking robots are inspired by some of the core techniques behind the current boom in generative AI, and roboticists are starting to build more general-purpose robots that can perform a wider range of tasks. We are now in the era of the Fourth Industrial Revolution or Industry 4.0, which is characterised by intelligent, adaptive technology. Automation is becoming increasingly automated, with machines communicating with each other and even sending data to remote locations. This connectivity and adaptability has revolutionised the capabilities of industrial robots, enabling them to perform multiple tasks seamlessly.

Overall, AI is reshaping industries and offering new tools for innovation and operational improvement. Its continued evolution, combined with open-source collaboration and strategic implementation, is crucial to unlocking its full potential across various sectors.

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Klart AI 

Klart AI plays a key role in helping businesses adopt artificial intelligence by offering seamless integration of AI technologies that are tailored to each company's specific needs. It provides AI models and services that address industry-specific challenges, helping organisations innovate, grow, and position themselves for long-term success.

Connect with Klart AI and claim your place in the realm of artificial intelligence and discover the full potential of AI in business, AI-powered innovation and AI for economic growth.

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