2023 AI Trends – Part One 

The future of artificial intelligence (AI) is already here, and it’s growing rapidly. In fact, a recent Deloitte study reveals that more than half of all organizations plan to integrate AI and automation technologies in 2023. While there are concerns about the potential risks of these tools, forward-thinking companies are already embracing tech-savvy processes to stay ahead of the game. This is part one of a two-part series discussing what the future of AI looks like in the coming months and how we can expect to see these models being used in the business world. Check out Part One here.

Design for AI 

When it comes to creating a sustainable AI system, there are several crucial aspects that must be considered. These include:  

Business application 

It's essential to establish the intended purpose of AI implementation upfront to ensure clear comprehension of the system's value, manage expectations, and set realistic goals. 

Data 

Moving forward, we can expect that designing an AI system will transform how we handle data, from storage to utilization in system development and operation.  

Software and Hardware  

Both software and hardware need to play a crucial role in the design process by integrating existing systems within the enterprise to create a coordinated and efficient system. 

Governance 

Improvements in data strategy will be necessary moving forward as this information will be the driving factor in generating effective AI models.  

Privacy 

Evaluating the impact of AI on privacy requires separating general data concerns, such as inaccurate results or overreliance on patterns, from those that directly relate to personal information use. This distinction is crucial to determining the true effect of AI on privacy. 

Security 

It’s important to establish clear security guidelines. This means implementing strategies to safeguard personal data, including encryption and secure storage. It also requires protocols to handle potential breaches and cyber-attacks.   

The bottom line is that an effective approach to AI system design should encompass all stages, from inception to maintenance, while also enabling iterative development. 

Event- and Scenario- Driven AI  

Discovering valuable insights and making predictions for strategic decision-making can be made easier with AI-driven signal-gathering systems. These systems continuously analyze data streams to understand how certain events might impact different areas of your business. By doing so, they enable more effective scenario planning and modeling, allowing businesses to prepare for potential challenges. Using AI's scenario-based approach makes it possible to discover connections between events, going beyond simple pattern recognition to identify meaningful patterns. 

To have a system that can anticipate events, it needs an architecture that is able to analyze various types of data such as text, video, and images from a robust set of sources like social media, news feeds, and transactional systems. That data is then used to create models based on event sequences and triggers. The result is event-driven architecture that enables efficient gathering and analysis of various data points to predict future events. 

Synthetic Data 

Synthetic data is artificially generated data that mimics the structure of real-life data. It should also have the same mathematical and statistical properties as the real-world data that it is created to replicate. This type of data is used to train machine learning models when there is not enough real data, or the existing data does not meet specific needs. It allows users to remove contextual bias from data sets containing personal data, prevent privacy concerns, and ensure compliance with privacy laws and regulations. 

Synthetic data is transforming the world of AI in countless ways. From improving language systems and detecting fraud to training self-driving cars and advancing clinical research, the possibilities are seemingly endless. With the ability to create data for any scenario and cater to all technological and business needs, synthetic data is the key to unlocking innovation in every industry. 

Edge AI 

Edge AI is a powerful technology that combines edge computing and artificial intelligence. This innovative tool allows AI applications to be deployed directly in devices located in the physical world, such as manufacturing equipment, healthcare devices, self-driving cars, and IoT devices. With edge AI, you can benefit from quicker and more efficient data processing, as well as smart automation features.  

Edge AI technology enables you to: 

• Process real-time data in a blink to gain insights and reduce latency 
• Cut down on expenses and bandwidth requirements by avoiding data transfers to the cloud 
• Ensure maximum data security by processing data locally on the device, reducing the risk of lost data 
• Boost automation by training machines to perform automated tasks 

The benefits of Edge AI are already being utilized in various applications and use cases, such as computer vision, geospatial intelligence, object detection, drones, and health monitoring devices.  

Wrapping IT Up: 

Staying ahead of the curve and preparing your organization for success in the age of AI can seem overwhelming but we are here to help. At Cimatri, we are proud to be your go-to resource for leveraging the power of Artificial Intelligence (AI). Our passion is to assist association leaders in improving processes and delivering delightful member experiences. Contact us to learn how we can help you get started utilizing AI in an efficient and effective way.