10 Important Emerging Technologies for 2025 and Beyond

Aerial drones: Defined as unmanned aerial systems controlled remotely or autonomously, drones are unlocking new business opportunities in low-altitude economies. They automate tasks such as infrastructure inspection, predictive maintenance, and even delivery services. Despite challenges like regulatory hurdles, the potential for enriched insights and enhanced experiences is enormous.

AI chips: AI chips are specialized processors designed to optimize AI workloads, including machine-learning training and inference. The market for these chips is rapidly growing, driven by the need for more efficient AI model processing at lower cost. These chips also enable advanced AI applications at the edge, pushing AI capabilities to consumer devices like smartphones and PCs.

Sustainability management technology: These are software platforms that collect and analyze sustainability metrics, helping organizations meet regulatory requirements and enhance their environmental strategies. These tools will be critical in achieving compliance and driving sustainability goals.

Synthetic data: Synthetic data refers to artificially generated data that mimics real-world data but without the privacy and security risks. It supports AI and analytics by providing abundant, high-quality datasets for model training and testing. This technology is especially relevant for organizations looking to overcome data availability challenges while maintaining compliance with privacy regulations.

Blockchain: Blockchain technology has become a trusted foundation for multiparty processes, data integrity, and even new financial infrastructures. Although adoption remains limited outside specific industries, and the pace is grindingly slow, blockchain’s potential for secure, decentralized data management is becoming clearer.

Decentralized digital identity (DDID): DDID represents a new approach to identity management, allowing users to control their own digital identities through blockchain-based credentials. This technology promises to enhance privacy and security in digital interactions, making it a cornerstone for future trust frameworks.

Explainable AI (XAI): As AI systems become more integrated into business processes, the need for transparency and trust grows. Explainable AI provides insights into how AI models make decisions, helping mitigate risks of bias and regulatory challenges. This technology is crucial for increasing AI adoption across industries.

Sensory AI: Sensory AI integrates AI with human sensory inputs like vision, hearing, and touch to create more natural and effective human-machine interactions. Applications range from enhanced customer experiences to adaptive operations in manufacturing and logistics. While still maturing, sensory AI holds promise for significantly improving situational awareness and decision-making.

6G: The next generation of cellular networks, 6G is expected to revolutionize connectivity with promises of ubiquitous coverage, integrated AI capabilities, and enhanced security. Like 5G, however, its deployment will be gradual, with meaningful impacts likely not materializing until the 2030s.

Quantum computing platforms: Quantum computing remains in its infancy, with current platforms still struggling to outpace traditional supercomputers, but advancements in quantum algorithms and hardware may eventually unlock new possibilities in fields like cryptography, materials science, and AI. For now, quantum computing remains an area of speculative investment.