What is the Democratization of Artificial Intelligence?
In the most simple words, the Democratization of AI means making AI available for everyone, including those who lack the knowledge and resources for the same. Why democratize AI, you may ask?
Well, technology is conquering one peak after another, and Artificial Intelligence (AI) is one of the most prominent pinnacles of 21st-century technology. The role of AI in solving real-world business problems is one of the most noteworthy impacts of software engineering in recent years. In fact, AI adoption has increasingly become crucial to every organization’s digital foundation.
Therefore, it won’t be long before AI becomes omnipresent, thanks to digital transformation initiatives. It is already making itself indispensable by enhancing business process efficiency and customer experience. So it’s high time this advanced technology is democratized and made available even to non-experts.
What does the democratization of AI mean for the world?
It is not difficult to imagine what will happen when AI is democratized. People will have more access to AI-based applications and AI tools. AI democratization will pave the way for more innovations that lessen the burden on humans and reduce the need for expert knowledge.
With the democratization of AI, organizations can rely on simplified AI solutions that handle the legwork rather than sifting through mountains of data to derive the information. One classic example is when AI solves problems that analysts and data scientists would have otherwise solved.
However, we are only at the cusp of AI democratization. So, rather than focusing on the big picture, let’s explore how this tech move will impact businesses in 2023.
AI Democratization: Changes to Expect in 2023
AI democratization is a given. But here’s what will happen next:
1. There will be an increased application of blended AI use cases. Emerging digital trends already predict that these use cases will pivot on robust and resilient operations that can scale vertically or horizontally.
2. Gartner predicts that in the next five years, decision intelligence and Edge AI will attain mainstream acceptance. This may result in transformational business innovations like:
- Operational AI systems
- ModelOps
- Smart robots
- Natural Language Processing (NLP)
- AI Engineering
- Autonomous vehicles
- Decision intelligence
- Computer Vision (CV)
- Intelligent applications
- AI cloud services
3. Business use cases will significantly influence the end goal of AI solutions. Hence, before choosing an AI solution, organizations will consider several factors depending on how far along they are in their digital transformation journey. In most cases, it will depend on how complex the task is compared to the decision risk.
4. In most cases, companies will not hesitate to invest in AI solutions with low task complexity and decision risk. Augmented AI will become an option when the decision risk and task complexity are higher. On the other hand, highly complex tasks will require human-in-the-loop intervention, with AI solutions as a decision-support tool. Nevertheless, it is still too early to determine the right approach.
Further, the 2022 Gartner AI Hype Cycle Report recommends companies to pay attention to some of the AI innovations that are expected to hit mainstream markets over the next few years. These include:
- Generative AI
- Deep learning
- Causal AI
- Composite AI
- Physics-informed AI
- Foundation models
When it comes to data-centric AI systems, innovations to look out for include:
- Knowledge graphs
- Data annotation
- Data labeling
- Synthetic data
4 Sub-trends of Democratized AI Likely to Emerge in 2023
Democratization of AI will likely give birth to these following subtrends, which will emerge more robustly than others.
1. Fully automated AI solutions
The most probable sub-trend to expect this year is AI solutions that will completely automate some of our daily tasks. We will likely witness AI automation in complex applications involving fewer risks, such as sending notifications and scheduling tasks.
2. Augmented AI
As intelligent applications become mainstream, user adoption of Augmented AI is expected to rise. Take, for example, business applications that rely on embedded or integrated AI solutions such as intelligent automation, guided recommendations, and data-driven insights. These solutions will be more prominent in improving productivity, enabling quicker decision-making, and delivering a personalized interface.
3. No-code AI
No-code AI is fast gaining traction because even engineers with little or no coding knowledge can handle it. Professionals can train or retrain existing AI models and fine-tune them for more relevancy and efficiency.
4. Human Involvement
AI works best when it co-exists with humans. The human-in-the-loop approach is a mutually beneficial partnership that simplifies even the most complex applications that require unusual pattern recognition, subjective decision-making, and cognitive judgment.
Thus, with the democratization of AI, we will witness many trends. But perhaps the most important one that will race ahead of others will be “composite AI.”
Also Read: Learn the ideal ways to keep AI claims in check by FTC
Evolution Of Composite AI in 2023: What to Expect?
What is Composite AI?
It is the method of using various AI techniques to achieve the best results. Also known as Multidisciplinary AI, it is the emerging trend for many use cases that are not machine-trainable due to the lack of adequate data in some fields.
This “data deficiency” happens when organizations hold back from sharing too much data in the public domain for sensitive business applications. In such scenarios, sufficient domain knowledge, together with human expertise, will be required to feed adequate context to the AI models. Further, the AI models will also have to be trained and retrained by humans consistently to achieve optimal performance.
Here’s where composite AI makes itself indispensable. Companies prefer the composite AI approach to tackle complex business problems holistically. This approach combines the capabilities of various AI models, such as:
- Machine learning
- Forecasting
- Optimization
- NLP
- Anomaly detection
- Traditional rules-based system
- Graph techniques
When done right, this combined power helps improve the AI system’s overall efficiency.
But that’s not all.
Composite AI has several advantages for organizations daring enough to use it. It:
- Allows users to gain insights from small datasets.
- Reduces the need for large data science teams.
- Facilitates human-like decision-making processes.
Closing Thoughts
In its first quarter, 2023 is already witnessing AI democratization in many forms as businesses embrace this high-end technology to cement their digital foundation. Composite AI will play a critical role in business optimization and automation. It will contribute to operational excellence, bigger advantages, and better revenue.
Yes, we have much to look forward to with AI democratization as we enter a fascinating era with this advanced technology.
The Opporture team is helping to create a more democratic and accessible future through AI democratization. Contact us today to learn more about our services and how we can help you succeed in AI.
