Advancements in artificial intelligence, especially generative AI, are transforming industries and reshaping how businesses operate, thus necessitating readiness, adoption, and ethical usage as they integrate AI into various sectors.
Cisco’s Executive Vice President Liz Centoni, predicts in her article 7 technology trends in 2024 around AI that will unfold the future of this exciting new technology, so let’s see what she had to say in her article below:
Cisco’s blog article discusses the impactful acceleration of AI and outlines seven tech trends anticipated for 2024, emphasizing AI’s integral role across these trends.
The Cisco AI Readiness Index shows that while 95% of respondents have an AI strategy, only 14% are fully prepared to integrate AI into their operations.
Generative AI (GenAI) is expected to quickly expand in the business world, with features like natural language interfaces (NLIs) predicted to become standard in products by the end of 2024.
Customized large language models (LLMs) and B2B applications will see growth, providing APIs for better data access and analysis. There will be a push towards smaller, specialized LLMs like the LLaMA-7B model for high accuracy and niche domains.
Ethical AI Use and Governance
There will be a movement toward responsible and ethical AI use with comprehensive policies to mitigate risks, such as IP infringement and data protection.
Organizations are encouraged to develop comprehensive AI policies to address ethical concerns, including issues like IP infringement and data privacy. Publicly available high-quality language data might be depleted by 2026, so the shift towards private or synthetic data is highlighted.
Threats from AI-Generated Disinformation
The year 2024 will see increased threats from AI-generated disinformation necessitating enhanced threat detection, and cooperation between the private sector and governments.
New inclusive AI solutions will help guard against things like deepfakes and social media bots by training models on large datasets to improve accuracy. There will also be increased focus on transparency and accountability through authentication and provenance mechanisms.
Businesses specifically need to prioritize advanced threat detection, data protection, regular vulnerability assessments, keeping systems updated, and thorough infrastructure audits. Consumers also must remain vigilant to protect identities, savings, and credit.
Post-quantum cryptography (PQC) will be adopted in anticipation of future quantum attacks, while quantum networking will gain importance in data security and processing.
Quantum networking utilizes quantum phenomena to transmit data. As an alternative or complement to PQC, quantum key distribution (QKD) over these networks will provide heightened security.
Significant research and investment into quantum networking will come from government and financial services which have high data security and processing requirements. Overall, PQC and quantum networking will see notable progress, addressing the threats quantum computing poses to encryption and data security.
AI-Driven Customization through APIs
Businesses will increasingly rely on API abstraction to leverage AI’s capabilities without the complexity of developing their own platforms, promoting innovation and customization.
APIs will provide seamless bridges to pre-built AI tools, services, and systems with little setup needed. This API-driven approach will allow automation of repetitive tasks, deeper data insights, and enhanced decision making.
There will also be a race towards API-driven customization as organizations mix and match APIs to create tailored AI solutions for their specific needs.
The flexibility to combine APIs from diverse providers will enable easy collaboration with external AI experts and startups, fueling innovation. Custom “model garden” ecosystems with curated APIs are already emerging and will expand rapidly.
Energy Use in AI
Energy networking emerges as a category focusing on sustainable energy, aiming to enhance energy efficiency through software-defined networking and energy management.
Sustainable energy and energy networking will become important, with emphasis on smaller AI models that reduce energy costs and new energy networking approaches to improve efficiency and emissions monitoring.
Shift Left in Software Development
“Shift left” in software development will lead to better collaboration, converged platforms, and AI assistance, optimizing programming experience and software quality.
Programmers will utilize platforms and collaboration, plus some AI assistance, to centralize toolkits for streamlined workflows so they can concentrate on quality digital experiences. Consolidated solutions like CNAPP, CSPM, and CWPP will help combat tool sprawl and disconnected systems.
However, some will still struggle with fragmented tools, causing security gaps and supply chain issues. Innovators will employ AI to accelerate delivery and automate tedious tasks like testing.
Collaboration apps and AI sidekicks will aid teams in tackling intricacies around security, observability, and infrastructure based on AI-generated recommendations.
Overall, programming in 2024 will be assisted by AI for efficiency gains but still rely on people for strategic direction and oversight.
Trust is a critical and non-negotiable aspect of AI systems and tools, highlighting the need for clear frameworks, education, and collaboration focused on ethical AI use.
The Cisco AI Readiness Index is presented as a resource, and the article concludes with a call to embrace AI with confidence, underscored by the importance of trust in technology.