Let’s explore the additional five technology trends predicted by leading technology executives that will shape the business landscape in 2024:
- Quantum Progress with a Focus on Post-Quantum Cryptography (PQC):
Liz Centoni, EVP Chief Strategy Officer & GM, Applications at Cisco, forecasts the adoption of post-quantum cryptography (PQC) in 2024, even before standardization. PQC, a software-based approach, will collaborate with conventional systems to safeguard data from future quantum attacks. Quantum networking, leveraging phenomena like entanglement and superposition, will enable scalable quantum solutions, with Quantum Key Distribution (QKD) emerging as an alternative or complement to PQC for enhanced security. Government and financial sectors are expected to invest significantly in quantum networking for data security and processing.
- Human Skills Essential for AI Integration:
Sashen Naidu, VP of CX Services at NTT Ltd, emphasizes the essential role of human skills in the uptake of AI. Despite a push for AI integration into customer experiences, the human element remains critical for success. The mounting skills shortages will drive a focus on reskilling and upskilling initiatives, making AI and big data analytics fundamental skills for most industries. Companies will invest in teaching experiences to bridge skills gaps and meet organizational needs.
- Continued Rise of Social Engineering Attacks:
Zeki Turedi from Crowdstrike predicts the persistence of identity-based attacks as the primary weapon for threat actors in 2024. Social engineering, phishing, and compromised identities will continue to be exploited by adversaries. Organizations will intensify efforts to educate employees on recognizing deception, making identity protection a critical focus. Tackling this weak spot becomes paramount to thwart adversaries successfully.
- AI Advancements and Increased Energy Usage:
Liz Centoni of Cisco notes that AI advancements will drive higher energy usage, prompting companies to choose smaller AI models tailored to specific use cases. These dedicated systems, trained on smaller datasets, will reduce energy consumption compared to general systems using deep learning models. The emergence of energy networking, combining software-defined networking and direct-current microgrids, will contribute to energy efficiency, offering visibility and optimization of power usage, distribution, transmission, and storage.
Businesses Creating Guardrails to Mitigate AI Risks:
Art Hu, SVP & CIO at Lenovo, highlights the growing awareness among companies about the risks and nature of AI. To mitigate these risks, businesses will take targeted actions, implementing new patterns like Retrieval Augmented Generation. Techniques such as ensuring quality training data, maintaining human involvement in training and inference for sensitive scenarios, and robust governance policies will balance the augmented intelligence provided by Generative AI. Clear AI policies and education for teams will be crucial for executing tangible AI plans responsibly and ethically.