Getting AI-Ready for an AI Native Era
Imagine a world where AI becomes a native part of our business landscape. In 2024, we’re not just imagining it; we’re living it. Last year witnessed two major AI trends. Technology-wise, AI agents entered the public eye. Suddenly, all companies started talking about and leveraging AI agents.
On the business front, we witnessed a gradual transition from +AI to AI+ (the AI Native age). Both trends have posed questions to organizations entering 2024. How can we get AI Ready for this evolving world? This article examines these trends and explores ways organizations can prepare for an AI Native world.
The Rise of AI Agents
Bill Gates aptly stated in his November blog: “AI agents will be the next arena after large language models. They will completely change how everyone interacts with computers within five years.”
2023 was the explosive year of Large Language Models. 2024 marks the explosive year of large-scale implementation and democratization of LLMs. The advancement of autonomous AI agents makes this possible.
AI agents emerged in 2023, signifying the onset of Artificial General Intelligence (AGI). This transition transformed AI from a consumer gadget into an essential B2B business tool.
Companies focusing on Large Language Models busy themselves with computing power and model training. AI-application companies search for AI transformation scenarios and AI native applications.
In 2024, AI agents will breakthrough after LLM. LLM agents unlock new possibilities and make real-life LLM implementation possible. AI agents enable practical LLM applications through three capabilities: planning, memory, and tool use.
These distinctive capabilities give AI agents the ability to solve intricate issues. They can self-learn and make autonomous decisions, leading to groundbreaking LLM applications and services.
Transition from +AI to AI+
The +AI age denotes the initial phase where AI technologies were nascent. They primarily served as auxiliary tools that supplemented existing systems and processes. In this era, AI was often an add-on feature. It enhanced traditional methods without fundamentally altering them.
Examples range from AI-empowered tools to Co-pilot models. We witnessed rapid development of AI applications including voice recognition, face recognition, and AI translation. We also saw the emergence of the AI Co-pilot age when Microsoft introduced its M365 Copilot products.
Many B2B tech enterprises made a splash with Co-Pilot products to optimize business efficiency. We can foresee a future where Co-Pilot becomes more mainstream than regular chatbots.
“The AI+ age” signifies a more advanced and transformative phase. In the AI+ era, AI moves beyond being just an add-on. It 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 between leading our industries or getting left behind.
In advertising, ads can be totally automated from creativity to production. In healthcare, patients go to hospitals and consult with AI throughout the process. We expect AI will become the foundation that re-constitutes the business world and model.
Today, more technology companies deploy agents to prepare for the AI Native era. However, before companies consider whether agents are native, they should ask: 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 a clear AI vision.
A Gartner survey in June 2023 of 606 CIOs revealed startling results. Only 9% of organizations express having an AI vision statement in place. More than one-third had no plans to create an AI vision statement.
To get AI Ready, organizations should follow these four principles:
Make Data AI-Ready
Making data AI-ready is essential. LLMs are vast statistical machines incredibly adept at learning from data. Therefore, data quality and relevance directly impact large language model outputs and performance.
According to Gartner, organizations must ensure data is secure, enriched, fair, and accurate. This involves ensuring collected business data is clean, organized, and structured for easy AI processing and analysis.
A robust AI strategy requires high-level organizational digitalization. The more ready an organization’s data strategy is, the more ready its AI strategy becomes. Professional knowledge data often remains in companies’ hands as “exclusive secret recipes.” Higher quality and more professional data creates greater value.
Implement AI-Ready Security
Implementing AI-ready security is critical. AI systems often handle sensitive data and influence key business decisions. Ensuring these systems are secure against cyber threats is paramount.
This includes protecting against data breaches, ensuring data integrity, and ethical data use. CIOs should work with executive teams to create acceptable use policies for public generative AI solutions.
Collaborate with a Dependable LLM Partner
Not all organizations have resources and capability to train and fine-tune LLM models themselves. Collaborating with a dependable Large Language Model partner provides significant advantages.
This involves choosing a reliable and experienced AI service provider. Such providers offer advanced AI solutions, insights, and support. Partnership accelerates both LLM implementation and organizational AI transformation.
Build an AI-Ready Team
Building an AI-ready team is important for transitioning to an AI Native Era. This involves training existing staff to work alongside AI systems and understand their capabilities and limitations.
It may include hiring new talent with specific AI skills and expertise. Examples include prompt engineers, fine-tune engineers, and LLM business partners. 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 giant AWS took the lead and made an AI commitment last November. They will provide free AI skills training to 2 million people globally by 2025. More organizations will carry out initiatives to meet high demands for AI-skilled talents.
How WIZ.AI Helps Organizations Get AI Ready
Companies in banking, insurance, and healthcare are taking the leap to lead AI transformation. They actively look for credible AI solution providers.
As a leading Generative-AI solution provider in Southeast Asia, WIZ.AI guides companies through their AI transformation journey. We propel sustainable business growth, drive operational efficiency, and enhance customer experience.
Our innovative WIZ platform, powered by AI Large Language Models, empowers customer interactions and employee experiences. It features human-like and personalized virtual agents, seamless human-bot synergy, and enterprise-ready generative AI applications.
We also adhere to high standards of data security and compliance. Our platform is designed with unmatched enterprise-grade security. It covers all AI work and solutions that protect you and your customers.
The AI-native era isn’t coming; it’s here. Let’s get AI-ready together.
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