5 important trends for 2024

Generative AI tools will be primarily used in business applications in 2024. Advances in AI pose new cyber risks as well as opportunities for the environment and businesses. Guest writer Liz Centoni of Cisco identifies five trends that will shape the use of AI technology in 2024.

Artificial intelligence tools are evolving at an unprecedented pace. Advances in artificial intelligence, especially generative artificial intelligence (GenAI), are opening up new possibilities that will dramatically change our economy and ways of working and living. However, the Cisco AI Readiness Index shows that although 95% of German companies have or are developing an AI strategy, only 7% are best prepared to use AI tools.

1. APIs simplify the use of AI tools

Businesses have a growing need to leverage data, automation, and innovation quickly and easily. However, according to the Cisco AI Readiness Index, only 17% of German companies prioritize AI implementation budgets over other technology investments. One solution is to increase the use of APIs. Many more AI tools and services could be integrated across this abstraction level in the coming year. These “API abstractions” make it possible to integrate AI more cost-effectively into business processes without developers having to delve into the technical details of implementing AI or developing their own large language models (LLM).

By accessing a variety of AI functions via APIs, repetitive tasks can be automated and decisions can be made based on better data. APIs that enable customer-specific AI implementation will also be created in 2024. To do this, companies combine interfaces from different service providers and thus create AI solutions to meet their individual requirements. The integration also supports collaboration with external AI experts, startups, and research institutions. The first models of coordinated AI systems are currently visible – models that we will see more frequently in the coming year.

2. AI-powered cyberattacks require cooperation

In 2024, business, politics, NGOs and civil society will be increasingly at risk from AI-generated disinformation. According to Cisco's 2023 Cybersecurity Readiness Index, only 11% of German companies are resilient enough to resist cyberattacks – and only 29% have a good understanding of the various cyber threats posed by AI. Technology providers and governments will therefore work together in 2024 to improve solutions against AI-enabled threats such as deepfakes, AI social bots or cloned voice recordings and implement appropriate cybersecurity measures. Investments in risk detection and training of AI models containing large data sets will also increase. In order to detect threats early, companies must invest in advanced security technologies in 2024 and give data protection a higher priority.

3. Generative AI is making its way into the business world

To remain competitive, companies must implement AI over the next year. That's why the focus in 2024 will be on natural language interfaces (NLIs) for new products powered by GenAI. Half of the new products will have such interfaces integrated as standard. GenAI will also improve interactions between companies, provide interfaces and services for accessing data, and use it in many business applications. This primarily affects company tasks that analyze and visualize data, for example in project management, evaluating software quality or analyzing compliance areas, as well as human resources tasks.

Specialized AI models are still expected to become more important. This will see a shift towards smaller MBAs with more rigor, relevance, rigor and efficiency. For example, LLaMA-7B models can be used for linguistic tasks such as writing, code completion, or image classification with just a few snapshots (“few capture”). In addition, multimodality, which combines different types of data such as images, text, audio and digital data, will expand B2B use cases in areas such as business planning, medicine and financial services, ensuring ever-better results.

4. Improve energy efficiency when using AI tools

Smaller AI models designed for specific use cases will reduce energy costs when using AI tools compared to public systems as early as 2024. These special systems are trained on high-resolution datasets and complete specific tasks more efficiently. In contrast, deep learning models require processing large amounts of data to achieve results.

Moreover, the rapid implementation of power grids will contribute to improving energy efficiency. This refers to a combination of software-defined networking with DC microgrids. This will help companies measure energy consumption and emissions more accurately in 2024. Many functions in IT and smart buildings can be automated with IoT sensors and made more efficient through integrated energy management capabilities.

5. Ethics and frameworks are becoming more important for AI tools

The introduction of AI tools is a unique technological change that requires the power of innovation and trust. However, according to the Cisco AI Readiness Index, 76% of all companies worldwide lack comprehensive guidelines governing the use of AI. Given the risks of GenAI, there is broad consensus that such guidelines and voluntary self-regulation by AI providers are generally necessary.

It must also ensure that consumers retain access to and control over their data – in line with current EU data regulation. Companies themselves are required to do this. As AI tools become more important, publicly available data will not be sufficient to train AI models. High-quality audio data is expected to be exhausted before 2026, which means a move to private or synthetic data will soon be necessary. However, this carries the risk of unauthorized access and data protection breaches. Therefore, those responsible for deploying AI will commit to greater transparency and trust in the development, use, and results of AI systems.

Technology companies in particular will have to prepare to demonstrate a new level of openness in the coming year. For example, what governance processes control the internal development, application and use of AI tools. If they cannot prove trustworthy use of AI, the regulatory framework is expected to be narrower in 2024.

About the methodology of studies

the Cisco AI Readiness Index This report is based on a double-blind survey of 8,161 executives from private sector and IT companies in 30 countries in 2023. It was conducted by an independent third party that surveyed respondents from companies with 500 or more employees. The index assesses the extent of readiness to use artificial intelligence tools in six main areas: strategy, infrastructure, data management, governance, specialized personnel, and corporate culture. The opinions of 300 experts in Germany were surveyed.

the Cisco Cybersecurity Readiness Index 2023 It is also based on a double-blind survey of 6,700 executives in 27 countries who are responsible for cybersecurity in their companies. The research was conducted at the end of 2022 using online and telephone interviews. The opinions of 300 experts from Germany were also polled. (Saint Germain)

About the author: Liz Centoni is the Chief Strategy Officer and Executive Vice President/General Manager of Applications at cisco.

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