In the Digital Age, few technologies have had greater impact in the business world than cognitive technologies (aka artificial intelligence). The VentureBeat staff reports, “Artificial intelligence (AI) is a foundational catalyst for digital business, according to a new report by Gartner. The last 10 years represent a breakthrough period in AI’s development, spurred by the convergence of factors including the rise of big data, advancements in compute infrastructure, new machine learning techniques, the emergence of cloud computing, and the vibrant open-source ecosystem.”[1] And Oleksii Tsymbal, Chief Innovation Officer at MobiDev, adds, “Artificial Intelligence is rightfully among the technologies that are fundamentally changing the modern world.”[2] As a result, business leaders need to know understand the trends driving the future of artificial intelligence. Below are a dozen trends experts believe will drive the develop of artificial intelligence during the coming year.

Artificial Intelligence Trends

Trend 1. AI Ethics. AI is such a powerful tool that many people are concerned about how it can be misused. As a result, articles about ethical AI are increasing. Pohan Lin, Senior Web Marketing and Localizations Manager at Databricks, explains, “There’s a growing awareness surrounding the ethics of AI. And the topic is being discussed more and more at computer science conferences. Demand for ethical AI is rising. Today’s consumers are increasingly value-driven. And more and more organizations are questioning how we can make use of these technologies in the most ethical way possible.”[3]

Trend 2. The rise of no-code/low-code. Journalist Annie Button (@anniebutton1994) writes, “The idea of the average person engaging and using AI might have seemed like a far-fetched idea in the past. Computer programming and coding has long seemed just a bit too much on the technical side for most people. However, thanks to the development and prominence of no-code or low-code AI, more companies and industries can embrace AI applications. Low-code, which requires minimal coding, and no-code, which requires none, is helping to drive the cost of implementing AI down for businesses.”[4]

Trend 3. AI for cybersecurity. Journalist Jayanti Pandey asserts, “Cognitive Algorithms offer end-to-end security platforms and detect, assess, research, and remediate cyber security threats.”[5] She notes that these algorithms can help prevent cyber-attacks as well as detecting misleading data and disinformation.

Trend 4. Generative AI. The VentureBeat staff reports, “Generative AI is the use of AI to generate new artifacts and create groundbreaking products. To date, generative AI efforts have focused on creating media content such as photorealistic images of people and things, but it can also be used for code generation, creating synthetic tabular data and designing pharmaceuticals and materials with specific properties.”

Trend 5. Large Language Models (LLM). Freelance writer Disha Sinha explains, “Large Language Models are founded on the principles of machine learning wherein algorithms recognize, predict, and generate human languages based on very large text-based data sets. The models include Statistical Language Models, Neural Language Models, Speech Recognition, Machine Translation, Sentiment Analysis, and Text Suggestions.” These models have become so impressive they can carry out convincing conversations.

Trend 6. AI and robotics. Mark van Rijmenam, founder of Datafloq, writes, “Applications of artificial intelligence are used widely in robotics. Real-time updates enable AI-powered robots to detect obstacles and plan their journeys instantly.” Examples he discusses of how AI is used in robotics include: Transporting goods in hospitals, factories, and warehouses; maintenance of large machinery and offices; and, controlling inventory.

Trend 7. Neuromorphic computing. Tech journalist Sally Ward-Foxton reports, “Neuromorphic computing refers to chips that use one of several brain-inspired techniques to produce ultra-low–power devices for specific types of AI workloads. … As these technologies (and our understanding of neuroscience) continue to mature, we will see more brain-inspired chip companies, as well as further integration between neuromorphic computing and neuromorphic sensing, where there are certainly synergies to be exploited.”

Trend 8. Improving data to improve AI. Some experts believe that the best way to improve AI is to improve the data on which it trains. Afraz Jaffri, a Research Director at Gartner, explains, “The AI community has traditionally focused on improving outcomes from AI solutions by tweaking the AI models themselves, but data-centric AI shifts the focus toward enhancing and enriching the data used to train the algorithms.”[9]

Trend 9. Improved business processes. Sinha observes that AI and machine learning can be used to identify individuals involved in various business processes. She explains, “It goes deeper than the earlier version of process mining to determine what happens when people indulge in various ways with various things to create business process events.” AI can also be used in concert with other advanced technologies to improve automated business processes. Tech writer Bob Violino explains, “In addition to RPA, AI, and ML, intelligent automation strategies can also incorporate a mix of technologies such as natural language processing, chatbots, and others that complement each other.”[10]

Trend 10. Quality assurance and inspection. Button writes, “Companies in the manufacturing or logistics industries rely on their quality assurance and inspection teams to deliver the best possible products to customers. Artificial intelligence in inspection has come on leaps and bounds already in its short time since being implemented. … Using AI for inspection purposes is rapidly growing thanks to the increased competency of object detection in video frames.”

Trend 11. Expanding applications. Jaffri notes that new AI applications are being created in the areas of “engineering, decision intelligence, operational AI systems, ModelOps, AI cloud services, smart robots, natural language processing (NLP), autonomous vehicles, intelligent applications and computer vision.” He adds, “Decision intelligence and edge AI are both expected to reach mainstream adoption in two to five years and have transformational business benefits. Decision intelligence is a practical discipline used to improve decision making by explicitly understanding and engineering how decisions are made and how outcomes are evaluated, managed and improved via feedback.​” At Enterra Solutions®, we are advancing Autonomous Decision Science™ (ADS®), which we believe is the next step in the journey toward better decision intelligence.

Trend 12. AI unlocks the metaverse. There has been a spurt of activity surrounding the so-called metaverse. Most companies are still experimenting with this new venue; however, they are coming to realize that the key to mastering the metaverse is artificial intelligence. Tsymbal explains, “While the debate about the boundaries and regularities of the Metaverse continues, businessmen are already arranging and populating it. In fact, 2023 will be a defining period for many companies with regard to how they will create their world within the Metaverse. … Artificial intelligence is one of the key elements of [the] Metaverse.” He also notes that the metaverse isn’t simply for gaming or commerce. He explains, “The integration of AI systems and the Internet of Things (IoT), whose devices supply the necessary data, has made possible the creation of digital twins. Such virtual versions of environments or systems allow modeling their development under various scenarios. This makes it possible to predict their condition and behavior under the influence of different external factors.”

Concluding Thoughts

Advances in AI are being made so quickly that journalist Chris Stokel-Walker reports AI systems are being asked to predict the future of artificial intelligence.[11] That’s why van Rijmenam concludes, “The future of AI is so bright.” He adds, “There is no doubt about the transformational impact of artificial intelligence on the economy, legal system, political system, and regulatory system. … But we know new technology has always had unintended consequences. We will likely face challenges related to artificial intelligence’s unintended outcomes, but AI will significantly shape our future.” To ensure that AI benefits humankind, responsible individuals will need to build systems capable of countering the nefarious activities of bad actors bent on criminal and immoral actions. Whether the future of AI is as bright, as van Rijmenam hopes, or dark, as some experts predict, depends on how well AI is regulated, monitored, and developed.

Footnotes
[1] Staff, “Report: 5 key trends for AI’s future,” VentureBeat, 13 May 2022.
[2] Oleksii Tsymbal, “Artificial Intelligence Trends That Will Make a Big Difference in Business in 2023,” MobiDev Blog, 22 October 2022.
[3] Pohan Lin, “The 10 Latest Artificial Intelligence Trends That Your Business Needs to Embrace,” IEEE Computer Society, 15 July 2022.
[4] Annie Button, “The Latest Business Artificial Intelligence Trends,” CEO Today, 23 March 2022.
[5] Jayanti Pandey, “Top 10 Cognitive Computing Trends to Look Out for in 2023,” Analytics Insight, 21 October 2022.
[6] Disha Sinha, “Top 10 Artificial Intelligence Trends to Look Out for in 2023,” Analytics Insight, 9 August 2022.
[7] Mark van Rijmenam, “What is the Future of Artificial Intelligence?” Datafloq, 17 October 2022.
[8] Sally Ward-Foxton, “Top 5 Trends in AI and Machine Learning,” EE Times, 14 October 2022.
[9] Afraz Jaffri, “What’s New in Artificial Intelligence from the 2022 Gartner Hype Cycle,” Gartner, 15 September 2022.
[10] Bob Violino, “IT enters the era of intelligent automation,” CIO, 28 September 2022.
[11] Chris Stokel-Walker, “Artificial intelligence is being asked to predict the future of AI,” New Scientist, 17 October 2022.