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Top  5 AI /ML Trends  In 2023

“AI continues to transform our world as companies look to win over consumers with intelligent experiences delivered in real time on smartphones, smart TVs, smart cars – smart everything.’

Over the last decade, Artificial Intelligence (AI) has become embedded in every aspect of our society and lives. From chatbots and virtual assistants like Siri and Alexa to automated industrial machinery and self-driving cars, it’s hard to ignore its impact. Today, the technology most commonly used to achieve AI is Machine Learning (ML) – advanced software algorithms designed to carry out one specific task, such as answering questions, translating languages or navigating a journey – and become increasingly good at it as they are exposed to more and more data.

Worldwide, spending by Governments and Business on AI technology will top $500 billion in 2023, according to IDC research. But how will it be used, and what impact will it have? Here, I outline what I believe will be the most important trends around the use of AI in business and society over the next 12 months.

1. Democratization Of AI

AI will only achieve its full potential if it’s available to everyone and every company and organization is able to benefit. Thankfully in 2023, this will be easier than ever. An ever-growing number of apps put AI functionality at the fingers of anyone, regardless of their level of technical skill. This can be as simple as predictive text suggestions reducing the amount of typing needed to search or write emails to apps that enable us to create sophisticated visualizations and reports with a click of a mouse.

If there isn’t an app that does what you need, then it’s increasingly simple to create your own, even if you don’t know how to code, thanks to the growing number of no-code and low-code platforms. These enable just about anyone to create, test and deploy AI-powered solutions using simple drag-and-drop or wizard-based interfaces. Examples include SwayAI, used to develop enterprise AI applications, and Akkio, which can create prediction and decision-making tools.

Ultimately, the democratization of AI will enable businesses and organizations to overcome the challenges posed by the AI skills gap created by the shortage of skilled and trained data scientists and AI software engineers. By empowering anybody to become “armchair” data scientists and engineers, the power and utility of AI will become within reach for us all.

2. Increasing AI Regulation

Increasing AI regulation puts spotlight on tools supporting ethical AI
The EU AI Act. The American Data Privacy and Protection Act. The Securing Open Source Software Act. The number of proposed regulations around artificial intelligence is rising rapidly, signaling that the days of companies self-policing their AI/ML projects (or not policing them at all) are coming to an end. Gartner predicts that by 2025 regulations will force companies to focus on AI ethics, transparency and privacy.

Companies must ensure that they have the Enterprise Model Management tools in place to meet new regulatory requirements, like “algorithm design evaluations” and “algorithm impact assessments.” That means being able to track and report on how models were created, trained, tested, deployed, monitored and managed. And if you don’t have an ethics council in place to oversee AI/ML, the time to establish one is now, before regulators come knocking on your door.

3. Responsible And Generative AI Capabilities

We can expect to see a few major AI trends in 2023, and two to watch are responsible AI and generative AI. Responsible or ethical AI has been a hot-button topic for some time, but we’ll see it move from concept to practice next year. Smarter technology and emerging legal frameworks around AI are also steps in the right direction. The AI Act, for example, is a proposed, first-of-its-kind European law set forth to govern the risk of AI use cases. Similar to GDPR for data usage, The AI Act could become a baseline standard for responsible AI and aims to become law next Spring. This will have an impact on companies using AI worldwide.

The second, Generative AI, will also make major strides over the next 12 months. Recent models can easily create realistic images and drawings from a description in natural language. Capabilities like this are now moving from cool functionality to actual business use cases. Dozens of companies offer you products that will draft essays, ad copy, or love letters. Instead of searching through stock photography, you can type a query and get a newly generated image. And this is just the beginning – we’re only scratching the surface of generative voice and video applications, so it will be interesting to see innovations and use cases come forth in the coming year.

4. Sustainable AI

In 2023 all companies will be under pressure to reduce their carbon footprint and minimize their impact on the environment. In this respect, the race to adopt and profit from AI can be both a blessing and a hindrance. AI algorithms – as well as all the infrastructure needed to support and deliver them, such as cloud networks and edge devices – require increasing amounts of power and resources. 

One study in 2019 found that training a single deep-learning model can result in the emission of 284,000 kilograms of CO2. At the same time, the technology has the potential to help companies understand how to build products, services, and infrastructure in a more energy-efficient way by identifying sources of waste and inefficiency. Ongoing efforts to implement more green and renewable energy-powered infrastructure are also a part of the drive toward delivering more  AI.

AI can be a driver of sustainability in other industries and areas of operation, too – for example, computer vision is used in conjunction with satellite imagery to identify deforestation and illegal logging activity in the rainforests, as well as illegal fishing activity, which impacts biodiversity in the oceans. In 2023, we can expect to see a continued drive towards deployment of AI initiatives aimed at tackling some of the most pressing problems facing our planet – rather than simply in pursuit of increased corporate profits.

5. Ethical And Explainable AI

The development of more ethical and explainable AI models is essential for a number of reasons. Most pressingly, though, it comes down to trust. AI requires data in order to learn, and often this means personal data. For many of the potentially most useful and powerful AI use cases, this might be very sensitive data like health or financial information. If we, the general public, don’t trust AI or understand how it makes decisions, we simply won’t feel safe handing over our information, and the whole thing falls apart.

In 2023 there will be efforts to overcome the “black box” problem of AI. Those responsible for putting AI systems in place will work harder to ensure that they are able to explain how decisions are made and what information was used to arrive at them. The role of AI ethics will become increasingly prominent, too, as organizations get to grips with eliminating bias and unfairness from their automated decision-making systems.  Biased data has been shown to lead to prejudice in automated outcomes that can potentially lead to discrimination and unfair treatment – which simply won’t be acceptable in a world where AI plays a part in decisions involving employment and access to justice or healthcare.

Final Thoughts

AI/ML will undoubtedly change how we operate in the world. And many of those changes are related to new forms of data collection and analysis.

As more novel data is collected (largely via IoT), new AI and ML initiatives will change how we utilize that data.

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Interested in Management, Design or Technology Consulting, contact anil.kg.26@gmail.com
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