2024 Trends in AI

Amid global uncertainty, 2024 promises to be a transformative year for AI. The technology’s potential to cure diseases, accelerate drug discovery, reduce dosage errors in medicine and elevate customer service is gaining ground.

Additionally, generative AI tools are making it possible to create personalized AI applications, using proprietary data to deliver tailored experiences. This will boost efficiency and improve market competitiveness.


Generative AI

Traditional AI systems are deterministic, relying on predefined algorithms and structured data. Spam filters in email services, recommendation systems on e-commerce sites, and even the chess-playing programs used to challenge humans all operate according to well-defined rules. Generative AI, on the other hand, operates in a more fluid manner, creating new content based on its understanding of patterns and changes in input data.

Generative AI is proving to be a game-changer, with applications across industries. It has the potential to expedite product design, improve customer experiences, increase employee productivity, and more. But to fully realize its potential, it will require significant changes in the way businesses work.

For example, it will likely become a common practice for companies to use generative AI to automate legal templates and other repetitive tasks, freeing employees to focus on higher-value and more strategic endeavors. Generative AI could also accelerate business processes and enable better decision-making by enabling quicker synthesizing and analysis of structured and unstructured data.

However, generative AI’s growth raises questions around ownership and bias in the content it generates. Striking a balance between innovation and ethical guidelines will be key to its sustainable growth.

Enterprise AI Customization

Enterprise AI can be a powerful tool for enhancing efficiency and driving digital transformation. However, it comes with its own set of challenges and limitations that businesses must be aware of to maximize its potential.

Unlike generic AI tools that work well with general business needs but miss the finer points of complex industries, custom AI creates bespoke solutions tailored to a specific industry’s nuances. These tools are not only more effective, but also more cost-effective and easier to integrate.

This trend will continue to grow as the technology continues to evolve and become more affordable for businesses of all sizes. In addition, many millennial and Gen Z workers are ready to embrace the future of AI in their workplaces. A survey conducted by Jobs for the Future showed that 66% of respondents believe they will need new skills to work with AI in the future.

With the right guidance, you can become a part of this growing field. Comprehensive programs like AI & ML BlackBelt Plus by Analytics Vidhya will provide you with hands-on experience and help you understand the underlying concepts of this technology from a real-world vantage point. In addition, the program offers placement assistance with top-tier names in the industry, making it an ideal platform for you to start your journey into the world of artificial intelligence.

Artificial Intelligence as a Service (AIaaS)

For a business that wants to work with AI tools but doesn’t have the resources, budget, or expertise to build and maintain them in-house, AI as a service (AIaaS) is an option. AIaaS providers are specialists who offer access to AI and machine learning technology through flexible subscription models that allow businesses to scale up or down as their needs change.

This approach allows companies to use AI to automate repetitive tasks that don’t add value but still require human judgment, and it can help companies streamline their processes and improve their KPIs. It also provides a high level of transparency with pricing, since most AIaaS models use a pay-per-usage model. Some AIaaS platforms can even offer human-in-the-loop (HITL) to give process owners control over AI automation and provide feedback in edge cases.

Ultimately, AIaaS can help make your company more competitive by speeding up your operations and providing consistency in decision making. But it’s important to note that this won’t eliminate the need for skilled workers – in fact, AI will likely increase the demand for professionals with the right skillsets.

For example, an auto manufacturer may have countless KPIs around driver and passenger safety, but they’ll still need employees to ensure quality and efficiency in the manufacturing process. To support their AI systems, these employees will need to be able to understand and translate the data AI produces so that it can respond to specific scenarios.

Artificial Intelligence as a Platform (AIaP)

As the world becomes increasingly digitised, AI has become a critical infrastructure that connects every aspect of our lives. While the potential of this technology is enormous, there are also risks. Its widespread use must therefore be accompanied by an early set of guardrails that can be fortified with laws and global agreements.

The first of these early guardrails is ensuring that AI systems are deployed responsibly and do not harm people. This requires the involvement of employees and their representatives in the development and implementation of these systems to ensure that they are formulated with Decent Work in mind. It is essential that conflicts of objectives such as data usage and personal rights are resolved at an early stage in order to avoid conflicting solutions, e.g., AI-based surveillance tools that perform poorly across racial groups or lead to mistaken arrests.

As the Singapore ecosystem grows, there is a need to develop a strong pipeline of AI talent. Hence, in 2021, the Ministry of Education will enhance baseline digital competencies – including computational thinking and data skills – for students entering sectors ripe for AI adoption. Meanwhile, IMDA has developed an AI Governance Framework and Toolkit to help organisations deploy their AI responsibly. It is also developing COSMIC, a scalable and secure platform for the sharing of AI-enabled information amongst public agencies.

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