Technology disruption is nothing new. Even AI has been around for decades, enabling progress in areas like voice assistants and digital twins long before autonomous vehicles and ChatGPT hit the mainstream news. The difference for the past two years has been just how quickly the latest AI innovations are transforming industries and redefining business possibilities.
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While the AI landscape will continue to grow next year, paving the way for even more advanced and intelligent applications, companies and innovators must stay ahead by continuously adapting and leveraging AI in new, strategic ways. Here are the top five areas we see AI evolving in the coming year.
Prediction: AI and data analytics will increasingly move to edge computing, allowing companies to respond faster when immediate action is required.
Edge computing changed the nature of applications by processing data closer to its source rather than relying on distant cloud servers, drastically reducing latency and enhancing responsiveness. This shift enabled developers to create more responsive and efficient applications.
In 2025, AI will shift significantly toward edge computing, fundamentally transforming how data is processed and utilized. This evolution stems from the need for AI systems to operate faster and more efficiently, and it’s made possible by the increased computational power of edge devices.
Moving AI to edge computing minimizes the delay in data transmission, improves performance and ensures greater reliability. It will also deflect some of the energy intensity of AI processing from data centers to individual devices. Additionally, this synergy enhances data security and privacy, as sensitive information can be analyzed and acted upon locally rather than being transmitted to centralized data centers.
This integration of AI with edge computing is poised to drive innovation and efficiency across many industries. For example, businesses can reduce bandwidth costs and improve network performance by only sending essential information to the cloud. These advancements empower companies to create more adaptive and responsive operations, providing a competitive edge in a fast-evolving technological landscape. Additionally, processing data closer to the source enables rapid decision-making, which is crucial for real-time applications such as healthcare, autonomous vehicles, and IoT ecosystems such as manufacturing and utilities.
Adding AI to edge computing allows developers to harness the full potential of AI technologies while overcoming the limitations of traditional cloud-based models, leading to innovative solutions that were previously unattainable.
Prediction: How we interact with AI will become more natural, and prompt engineering will become second nature.
The professional landscape will change as AI-augmented work becomes a standard part of daily life. How workers interact with artificial intelligence will evolve to be more intuitive and seamless, making it a natural extension of human professional capabilities.
This shift is due to natural language processing and machine learning advancements, which allow AI systems to understand and respond to inputs with unprecedented accuracy and nuance. Prompt engineering, once a specialized skill, will become second nature, empowering more employees to harness the full potential of AI tools and applications. As these technologies embed themselves deeper into our workflows, they promise to enhance productivity and redefine the very nature of collaboration and innovation in the workplace.
How might this look in an enterprise environment? Human Resources teams may use generative AI prompts to request AI-generated project results. For example, an employee could ask for a performance review template for a specific role, including sections for goals, achievements and areas for development. Or perhaps the employee could request an analysis of an employee feedback survey, identifying critical areas for improvement in their department. These now-automated tasks could be completed in a fraction of the time using generative AI prompt-assisted requests.
Prediction: AI solutions will expand to include much more unstructured data to yield more reliable and precise insights for enterprises and consumers alike.
Unstructured data like images, streaming audio/video and social streams are the fastest-growing data types, so AI will inherently and quickly adapt to tackle such inputs in the coming year. By analyzing these forms of data, companies will gain new and more nuanced insights and be better equipped to launch new innovative services and solutions that deliver unprecedented reliability and precision outcomes.
As businesses become more data-centric, incorporating unstructured data into AI solutions will undoubtedly become essential. Solutions capitalizing on these data types lead to better decision-making and actionable intelligence that can lead to new revenue streams, providing a competitive edge.
For example, drones equipped with high-definition cameras and advanced AI capabilities will revolutionize disaster response, particularly in assessing storm damage. These aerial devices offer real-time, high-resolution video that can swiftly capture the extent of destruction across vast areas, a task typically hampered by ground accessibility issues post-storm. By applying AI to that footage, a number of actionable insights can enable faster, more effective disaster response.
In just one example, providing insurers with precise data can significantly expedite the validation of insurance claims, enabling faster financial relief for those affected. Such rapid assessments can also aid community leaders in streamlining recovery plans for impacted areas, allowing them to rebuild and restore normalcy more efficiently.
Prediction: As the AI skills gap widens, hyper-personalized learning will empower more people to meet changing workplace needs and even deliver more personal healthcare that improves patient outcomes.
In the coming year, we expect a surge in AI-powered hyper-personalized online learning, driven by the urgent need to bridge the growing global skills gap. Personalized learning leverages artificial intelligence to tailor educational experiences to individual learners’ needs, preferences and pace, enhancing engagement and retention.
This approach accelerates skill acquisition and ensures that learning is relevant and aligned with career goals. The global eLearning market will grow to $1 trillion by 2032, reflecting the increasing demand for accessible and adaptable learning solutions. By harnessing the power of AI, educational platforms can offer highly customized content, enabling learners to develop the precise skills they need to thrive in a rapidly evolving job market.
By extending this same model to healthcare, AI-infused data will empower nurses to contribute in areas where previously only doctors could, accelerating care and improving patient outcomes. AI will also continue reshaping how people experience personalized healthcare. With the capacity to analyze vast amounts of data rapidly, AI can identify subtle patterns in patient histories, symptom progression, genetic information, lifestyle factors and even known allergies that human practitioners might overlook. This capability allows for more accurate diagnoses, tailored treatment plans and customized preventive strategies to meet each individual’s unique needs.
Integrating AI into healthcare will improve medical outcomes and empower patients to take control of their health journeys. This shift will lead to a more efficient, patient-centered approach to medicine for better population health.
Prediction: AI analysis of visuals and voice makes insights more profound.
The AI revolution will spotlight language and visual analytics in the coming year, making them indispensable business tools across industries. One of the key advancements will be AI’s ability to determine sentiment in voice, providing companies with invaluable insights into customer emotions and intentions. This capability allows organizations to enhance the customer experience, tailor services to specific emotional needs and improve overall customer satisfaction.
Additionally, AI will begin to analyze visuals to offer improved insights that enable real-time operations monitoring, predict maintenance needs and ensure safety compliance. This capability will be valuable for industries like electricity, water, oil and gas that use video to monitor assets and infrastructure and are continually searching for ways to optimize efficiency, reduce downtime and significantly cut costs.
AI in 2025 will offer even more new ways to reshape industries, improve lives, and address global challenges like healthcare access, the digital divide and sustainability. Although AI’s specific evolution may be uncertain, it’s clear that the technology has the power to drive innovation further and create a better world.
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