Looking back, 2024 has been a year of phenomenal advancements in AI. The advancements have already begun reshaping industries and redefining business possibilities. In light of a year of AI innovations, we’re taking a quick look back and recapping the 13 most significant ways that AI has impacted the business world so far.
Industry adoption of AI
AI adoption is picking up momentum across organizations large and small and in many industry sectors. But they are not uniform across different sized firms, according to the Bipartisan Policy Center. The largest (7.2%) and smallest firms (5.5%) tend to adopt AI at higher rates than do medium-sized firms.
While many companies began their AI journey by augmenting search capabilities and improving knowledge management and retrieval systems, several organizations started incorporating AI into their mainstream business processes this year. Here are a few highlights in the enterprise, public sector and social good arenas.
- AI in the enterprise: AI is being widely adopted by enterprises within most industries with the topmost goals of improving efficiency, reducing costs and driving innovation. Key areas where they are deploying AI-powered applications include customer service, marketing, finance and the supply chain management.
- AI in the public sector: Governments are leveraging AI to improve public services, such as healthcare, education and public safety. AI-powered tools are helping streamline government processes, reduce bureaucracy and improve decision-making.
- AI for social good: AI is being used to address social challenges, such as poverty, hunger and inequality. AI-powered tools are helping identify vulnerable populations, allocate resources effectively and develop targeted interventions.
These highlights demonstrate how AI is transforming organizations across sectors. To explore more, discover leading use cases for unlocking AI’s full potential with innovative solutions across eight industries.
AI innovations in applications
In 2024, advances in AI applications have spanned industries from manufacturing to medicine and supported innovation in everything from employee training to improved privacy to quantum computing. Here are some of the year’s highlights in AI application innovations.
- Generative AI: These models made significant strides, enabling the creation of realistic images, videos and text. The models support a range of applications in several fields, including marketing, design and entertainment.
- AI-powered healthcare: Healthcare was transformed by AI in multiple ways, including improved medical image analysis, drug discovery and personalized medicine. AI-powered tools are assisting in early disease detection, accelerating drug development and optimizing treatment plans.
- Autonomous vehicles: AI drove the development of autonomous vehicles, with companies like Tesla and Waymo making significant progress.
- AI for climate change: AI was used to address climate change by analyzing climate data, optimizing energy consumption and developing sustainable solutions.
These highlights demonstrate how AI is transforming organizations across sectors. To explore more, read our insights on the eight common blockers when transitioning AI from PoC to production.
AI innovation in hardware
While many business people tend to think of AI in terms of software, it’s also greatly impacted hardware innovation. Security Intelligence reported that big hardware changes have been necessary to accommodate power-hungry AI use cases. It stated, “The recent accommodation of AI in hardware is just the beginning, no doubt. We can look forward to AI-specific hardware trickling down beyond PCs and phones and into wearables, internet of things devices and more.”
In 2024, new AI-ready hardware has enabled advances in everything from employee training to improved privacy to quantum computing discoveries. Here are some of the year’s hardware innovation highlights.
- Specialized AI chips: Companies like NVIDIA, Google, Microsoft and Amazon Web Services (AWS) launched innovations in AI-specific hardware, developing powerful GPUs and TPUs designed to accelerate machine learning and deep learning tasks. The advancements enabled training and deployment of increasingly complex AI models.
- Edge AI hardware: Edge AI devices, such as cameras and sensors, became more affordable and accessible, enabling AI applications to be deployed closer to the data source, where they reduce latency and improve privacy.
- Quantum computing for AI: While still in its early stages, quantum computing proved that it holds the potential to revolutionize AI by solving complex problems that are problematic for classic computers. Researchers explored ways in which quantum computing can be leveraged for tasks like drug discovery and materials science.
AI innovation in developer tools
New AI-ready development tools are supporting a range of capabilities — from pre-trained AI models to open-source opportunities to low-code/no-code accessibility. According to Forbes, the integration of AI into software development is “a game-changer. It’s not just about automating tasks; it’s about enabling developers to think and work at a much higher level and focus on the strategic aspects of their projects.”
In 2024, new advances in AI developer tools supported innovation in everything from employee training to improved privacy to quantum computing discoveries. Here are some of the year’s highlights.
- User-friendly AI platforms: Companies like Google, Microsoft and AWS released user-friendly AI platforms that are allowing developers to build and deploy AI applications without extensive machine learning expertise. The platforms offer pre-trained AI models, APIs and tools for data preparation, model training and deployment.
- Open-source AI frameworks: Open-source frameworks, like TensorFlow and PyTorch, continued to evolve, providing researchers and developers with powerful tools for building and training AI models. The frameworks’ open-source nature is supporting new opportunities to achieve collaboration and innovation.
- Low-code/no-code AI tools: These tools empowered citizen developers to build AI applications without needing to write complex code. The tools democratized AI by making it accessible to a wider range of users.
AI has opened the door to new opportunities for developer tools. To explore more, read our insights on integrating AI with product development engineering processes.
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