Getting AI-Ready for an AI Native Era

Imagine a world where AI is not just a tool, but a native part of our business landscape. In 2024, we’re not just imagining it; we’re living it.

Last year, we witnessed two major trends in the AI field. Technology wise, the concept of AI agents came to the public eye, and suddenly all the companies were talking about and leveraging AI agents. On the business front, we witnessed a gradual transition from the age of +AI to AI+ (the age of AI Native). Both of these two trends have posed questions to organizations entering 2024. How can we get AI Ready for this ever-evolving world?

In this article, we will look into these two trends, and examine the ways that organizations can get prepared for an AI Native world.

The Rise of AI Agents

As Bill Gates aptly put it in his blog last November, “AI agents will be the next arena after the large language model, which will completely change the way everyone interacts with computers within five years.”

While 2023 is regarded as the explosive year of Large Language Models, 2024 is regarded as the explosive year of large-scale implementation and democratization of Large Language Models, which is made possible by the advancement of autonomous AI agents.

With the emergence of AI agents, 2023 also signifies the onset of the Age of Artificial General Intelligence (AGI). This transition has transformed AI from a popular consumer gadget into an essential tool for B2B business. We have seen companies that focus on Large Language Models busy looking at computing power, training and refining models, while AI-applications companies are busy looking for scenarios for AI transformation or AI native applications.

In 2024, AI agents will be the next breakthrough point after LLM. We wrote before that LLM agents will unlock new possibilities and make the implementation of LLM in real life possible. AI agents make the practical applications of LLM in real-world scenarios possible because of its three capabilities: planning, memory and tool use. Because of these three distinctive capabilities, AI agents will have the ability to assist in solving intricate issues, capable of self-learning and autonomous decision-making, leading to groundbreaking LLM applications and services.

Transition from +AI TO AI+

The age of +AI denotes the initial phase where AI technologies were in their nascent stages, primarily serving as auxiliary tools that supplemented existing systems and processes. In this era, AI was often an add-on feature, enhancing traditional methods without fundamentally altering them.

For example, from AI-empowered tools to Co-pilot models, we have witnessed the rapid development of AI applications in +AI age, including AI-empowered voice recognition, face recognition, AI translation, etc. In addition, we have witnessed the emergence of the age of AI Co-pilot when Microsoft introduced its M365 Copilot products. In fact, many B2B enterprises in tech sectors have made a splash with their Co-Pilot products to optimize business efficiency and products, and we could foresee a future where Co-Pilot will become even more mainstream than regular chatbots.

On the other hand, “the age of AI+” signifies a more advanced and transformative phase in the AI journey. In the “AI+” era, AI moves beyond being just an add-on and becomes a core, integral component driving innovation and redefining systems. We have the opportunity to fundamentally reimagine how work gets done. This will mean the difference in leading our industries or getting left behind.

For example, in the advertising sector, we are witnessing the ads could be totally automated from creativity to production; in the health sector, we are seeing trends in patients going to hospitals and consulting with AI through the whole process. In the future, we are expecting that AI will become the foundation that re-constitutes the business world and model.

Today, more and more technology companies are beginning to deploy agents to prepare for the AI Native era. However, before companies consider whether the agents are native or not, the first question they might ask themselves is Are We AI Ready?

Getting AI Ready for an AI Native Era

According to Gabriela Vogel, Sr Director Analyst at Gartner. “By 2025, GenAI will be a workforce partner for 90% of companies worldwide.” However, few organizations have established principles or even a clear vision for AI. According to a Gartner survey in June 2023 of 606 CIOs, only 9% of organizations express that they have an AI vision statement in place, and more than one-third of respondents had no plans to create an AI vision statement.

In order to get AI Ready, we think the organization should follow the following four principles:

Make data AI-ready

Firstly, making data AI-ready is essential. LLMs, at their core, are vast statistical machines which are incredibly adept at learning from the data they’re fed. Therefore, the quality and relevance of the data directly impact the large language model outputs and performance.

According to Gartner, for data to be AI-ready, organizations must ensure that data is secure, enriched, fair, and accurate. This involves ensuring that the data collected and used by the business is clean, well-organized, and structured in a way that can be easily processed and analyzed by AI algorithms.

Getting a robust AI strategy requires a high-level of digitalization for organization. In other words, the more ready an organization’s data strategy is, the more ready its AI strategy is.

Compared with public data sets on the Internet, these professional knowledge data are often in the hands of the companies themselves and are “exclusive secret recipes.” The more professional data and the higher the quality, the greater the value. If an enterprise wants to deploy a large model well, it cannot do without the enterprise providing sufficient data of high quality to support secondary training and fine-tuning of the model.

Implement AI-ready security

Secondly, implementing AI-ready security is a critical consideration. As AI systems often handle sensitive data and can influence key business decisions, ensuring that these systems are secure against cyber threats is paramount. This includes protecting against data breaches, ensuring data integrity, and the ethical use of data.

Within the organization, CIOs should work with the executive team to create an acceptable use policy of public generative AI solutions.

Collaborate with a Dependable LLM Partner

Not all the organizations have the resources and capability to train and fine-tune LLM model themsleves. Thus, collaborating with a dependable Large Language Model (LLM) partner can provide significant advantages. This involves choosing a reliable and experienced AI service provider that can offer advanced AI solutions, insights, and support. Such a partnership not only accelerates the implementation of LLM, but also the AI transformation of the organization.

Build an AI-ready team

Finally, building an AI-ready team is an important aspect of transitioning to an AI Native Era. This involves training existing staff to work alongside AI systems and understand their capabilities and limitations. It may also include hiring new talent with specific AI skills and expertise, such as prompt engineer, fine-tune engineer and even LLM business partner. An AI-ready team is crucial for developing AI strategies, executing AI-driven projects, and maintaining AI systems effectively.

The need for an AI-savvy workforce has never been greater. Tech giants AWS took the lead and made the AI commitment last November to provide free AI skills training to 2 million people globally by 2025. In the future, more organizations will carry out initiatives to meet the high demands of AI-skilled talents.

How can WIZ.AI help Organizations get AI Ready for an AI Native Era

Companies in certain industries like banking, insurance and healthcare are already taking the leap to lead AI transformation and look for credible AI solution providers.

As a leading Generative-AI solution provider in Southeast Asia, WIZ.AI is dedicated to guiding companies through their AI transformation journey, propelling sustainable business growth, driving operational efficiency, and enhancing customer experience.

Our innovative WIZ platform, powered by AI Large Language Models, is designed to empower customer interactions and employee experiences, featuring human-like and personalized virtual agents, seamless human-bot synergy, and enterprise-ready generative AI applications, providing everything needed for scalable AI implementation.

We also adhere to the high standard of data security and compliance. Our platform is designed with unmatched enterprise-grade security, covering all AI work and solutions that provide you and your customers.

The AI-native era isn’t coming; it’s here. Let’s get AI-ready together. Ready to step into the AI-native era? Talk to our experts at WIZ.AI and start your journey today!