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Artificial Intelligence (AI) Trends that Will Be Huge in 2023 and Beyond
AI development is now maturing and showing a lot of promise for businesses of all sizes. This blog covers key AI trends for business innovations, expert predictions about the future of AI.
“Artificial intelligence will have a more profound impact on humanity than fire, electricity and the internet.” These are the words of Sundar Pichai, the CEO of Alphabet. While the claim might seem far-fetched, there is no questioning the potential of AI. From providing personalized marketing to pregnancy management, the possibilities are endless.
In 2023, the new trends that AI will bring about is something that organizations across the world are curious about. In this article, we will look at AI trends for the next year and beyond. We might be witness to these trends and get to see the kind of impact that it will have on businesses and humans alike.
AI trends for 2023 and beyond:
There has been an increase in digital transformation across a variety of industries, a phenomenon that happened faster than expected, thanks to the pandemic. It is expected that there will be significant innovations in these technologies in the year 2023. Let us see what the next year brings us in the world of artificial intelligence.
1. Natural Language Processing
Without a doubt, NLP is one of the most used AI technologies. Its specialty is that it comprehends human talk and reduces the necessity to type or interact with a screen. AI-powered devices can turn human languages into computer codes which can efficiently run applications and programs.
OpenAI, recently released GPT-3, which is considered the most advanced NLP ever. GPT-3 consists of more than 175 billion parameters which are used for language processing. OpenAI is on the works for GPT-4, and it is speculated that it may contain 100 trillion parameters. With GPT-4, we are on the verge of creating machines that can engage with humans in a way that is as good as real.
2. Metaverse
It is a virtual world, just like the Internet, where people can work and interact with the help of immersive experiences. A total of $106 million was spent on virtual land in the metaverse. AI and ML will be the technologies that propel the metaverse forward. They will help enterprises create a virtual world where users will feel at home with virtual AI chatbots.
3. Greater focus on model governance
Businesses want to increase the bottom line, but they also want to be compliant with all regulations. It is a tussle between the two as one might not necessarily help the other. Thankfully, this is where responsible AI becomes an important factor in model (data) governance. It will bring in more transparency and visibility, while ensuring that in the thirst to increase revenue, businesses do not fail to follow guidelines.
Many AI models keep breaking down while running in production. Having a proper AI model governance will bring more accountability and traceability into the equation. With more companies embracing AI, implementing an AI model governance will be so pivotal to following guidelines and being compliant with all regulations.
4. More localized AI/ML models
Everyone knows that the strength of an AI/ML model is derived from the data that it is fed. With businesses relying on such models to grow, they need to be careful of the external factors which can affect the outcome that they desire. That’s exactly why businesses need to experiment with localized AI/ML models so that they have a clear understanding of the demographics that they are dealing with.
The first few versions of your AI/ML model might bring in a lot of success. But when you move further, it can become much harder as the use cases will keep differing. For example, your AI model might work perfectly well in North America, but they will fail when you are looking at markets in Europe. With localization, you will be able to adjust the differences and get accurate AI/ML models.
5. More jobs for governance
Bias in algorithms can come from a lack of model governance, and it will be a huge concern in 2023 and beyond. Making sure that AI/ML models don’t make bad decisions or develop biases is not a simple task. Amazon realized in 2015 that its algorithm for hiring employees was biased against women. Why did it happen? They realized that the algorithm was based on the resumes submitted over the past ten years, and since most of them were men, it was trained to be biased against women. Twitter also recently admitted that its algorithm favored right-wing politicians and news outlets.
The above examples are exactly why you will see a rise in positions such as Chief AI Officer, Chief AI Compliance Officer, and so on. Their job would be to see the failure of such potential issues. While instances such as these will be few and far between, it will certainly see a jump because of the rapid adoption of AI/ML.
6. Low-code or No-code AI
The number of skilled AI engineers doesn’t meet the demand in the market. Organizations require engineers who can develop the necessary tools and algorithms. Thanks to low-code and no-code solutions, this issue can be addressed just by providing intuitive interfaces that can be used to create complex systems.
Most of the low-code solutions have drag-and-drop modules which makes it easy to build applications. No-code/low-code AI systems can be used to create smart applications with the help of pre-created modules and adding specific data into them. By using NLP and language modeling technologies, voice-based instructions can be given to complete tasks.
Check out our recent blog on “Are Citizen Developers Getting the Output They Need from Low Code Platforms?” which highlight the benefits of citizen development, as well as show how new tools are changing the way that software is created.
7. AI in Cybersecurity
The average amount of reported ransomware transactions per month in 2021 was reported to be $102.3 million. With technology seeping in almost every aspect of our lives, the damage that cyber attacks cost us is even more sinister than we could possibly imagine. The World Economic Forum recently declared the criticality of cybercrimes. With each device that is added to the network, the risk only increases. Obviously there is no way to reduce the number of devices being added as it would mean that we are negatively dealing with this issue.
The networks are also becoming complex with each passing day. Here is where Artificial Intelligence and Machine Learning can play a big role in tackling this issue head on. AI/ML systems have the ability to identify patterns, predict trends and see for anomalies. It can look for suspicious activity by developing smart algorithms for it. The coming years will see a lot of focus on AI/ML to combat the dangers of cyberattacks. The market for AI/ML in cybersecurity is expected to reach $38.2 billion by 2026.
8. Better hiring practices
With Covid-19 putting a huge dent in hiring decisions, the coming months will see a spurt in requirement for skilled employees. AI/ML systems can help with making better hiring practices. AI can help drive participation from diverse backgrounds. Diversity will bring in a lot of positive changes to the workforce, and even enable innovation, thanks to a variety of perspectives that it will offer. Employers should make it a point to hire people from different disciplines and backgrounds, including philosophy, social sciences, arts, etc.
9. Workforce Augmentation
The fear that AI will replace human jobs is something that we have been hearing for quite some time. The truth is that companies will use AI/ML to gather data, analyze, and leverage the insights to make business decisions. In such a case, it becomes even more important for businesses, employees and AI machines to work in tandem.
If you look at most departments, they are already using AI and ML systems. Let it be sales, marketing or customer service, AI is already being leveraged. Has it reduced the dependence on human beings? Of course not. You will see that these AI/ML systems have only increased the effectiveness of each of the departments. In manufacturing industries, AI systems are used right from predicting sales to forecasting inventory. Technology companies are using AI/ML to increase the effectiveness of its software. Each industry has multiple use cases when it comes to AI.
10. Conversational AI chatbot
There has been no technology which has revolutionized the way in which conversational AI chatbot has affected customer support. Conversational chatbot solutions are AI-powered virtual assistants which do rule-based operations and also carry on natural conversation. From doing mundane tasks such as responding to queries, resetting passwords, etc., to understanding human queries, the dent it has created is immeasurable. By almost replacing customer support agents, it has reduced the operational costs of businesses by a huge margin.
A conversational AI chatbot can also devise a conversational marketing strategy, scale your support operations to as much as possible, and even use previous customer data to offer solutions. Data from Comm100 says that chatbots are able to take care of 68.9% of chats from start to finish.
11. Hyper Automation
Organizations will leverage AI and ML technologies to automate a number of processes which would entail large volumes of information and data. You will see an increase in the rate of automation in multiple industries using robotic process automation and intelligent business process management software.
The main objective of automation is to scale automation capabilities in an organization. Hyper Automation is an expansion of automation, it adds an extra layer of advanced technology to do much more with the technology. The Hyper Automation market is expected to reach $600 billion by 2022.
12. More focus on AI ethics
There has been a spurt in AI use cases across almost every industry that you could possibly imagine, in the last few years. Although the technologies are incredibly beneficial for mankind, the potential risks cannot be discounted. We will see a bigger focus on AI ethics in the coming few years as things could go awfully wrong if there is no deliberate intent to use these technologies only for the good.
Even a technology as useful as facial recognition can be used to create a police state. Companies which have integrated AI into their business processes will find the most success with it, as opposed to one that goes with the flow.
13. Quantum AI
It is the use of quantum computing for computation of machine learning algorithms to achieve results which is not possible on a traditional computer. Although there has been incredible progress in AI in the last few years, it is still limited by technological challenges. With quantum computing, the obstacles to achieve Artificial General Intelligence (AGI) can be eliminated. An AI that is powered by quantum computing can complete years of analysis in a short period of time.
Conclusion:
The above AI trends will soon make a dent in the business world. AI is a transformative technology that will only keep improving with time and help organizations achieve their business objectives by assisting in building innovative solutions for products and services. Gartner says that by 2022, organizations will have at least 35 AI or ML projects in place. This is the kind of impact that AI will have in the coming future. Businesses that do not embrace these technologies will have a tough time thriving in this cut-throat world.
If you are looking to empower your organization with the power of AI and ML, the team at Zuci has stalwarts at these technologies. They will propel your business forward by leveraging these for you. Get on a call with us to understand how we can transform your business with AI/ML.
I write about fintech, data, and everything around it | Assistant Marketing Manager @ Zuci Systems.
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