Tech Experts Offer 7 Predictions for AI in 2023

AI continues to fuel a hotbed of activity from automating mundane tasks to enhancing decision making, and progress in this area looks to heat up even more in 2023.

According to Gartner’s AI Hype Cycle report which urges companies to, “pay early attention to innovations expected to hit mainstream adoption in two to five years, including composite AI, decision intelligence and edge AI.”

Despite the shift to a data-centric approach, AI models still need attention to ensure the outputs continue to help us to take better actions. Innovations here include physics-informed AI, composite AI, causal AI, generative AI, foundation models and deep learning. Innovations in data-centric AI include synthetic data, knowledge graphs, data labeling and annotation.

Decision intelligence and edge AI are both expected to reach mainstream adoption in two to five years and have transformational business benefits, according to Gartner. Innovations here include AI engineering, decision intelligence, operational AI systems, ModelOps, AI cloud services, smart robots, natural language processing (NLP), autonomous vehicles, intelligent applications and computer vision.

Digital ethics are a nearer-term trend (two to five years) likely to have a high business impact. Digital ethics comprise the systems of values and moral principles for the conduct of electronic interactions among people, organizations, and things. These issues, especially as they relate to privacy and bias, remain of concern to many.

Here, IT leaders share their perspectives on where AI is headed and what can be expected to change in 2023.

  • AI and data democratization: Artificial intelligence is becoming an increasingly popular investment among organizations, especially as a way to improve productivity during a time of increased “performance paranoia” and consolidation of teams—creating a need for AI-powered automation across multiple departments. Yet many of these teams across functions like HR and Sales might not even realize they’re a target buyer for AI, and our researchers show that marketers continue to overlook HR and sales directors in favor of IT teams, who are already familiar with the AI solutions they should invest in. In 2023, AI and data will be democratized, requiring all teams to know which data is usable and how AI-powered technology can make their jobs easier. —Ajay Sathyanath, CTO, Madison Logic
  • The AI industry will offer more tools that can be operated directly by business users: Companies have been hiring more and more data scientists and MLEs but net AI adoption in production has not increased at the same rate. While a lot of research and trials are being executed, companies are not benefiting from production AI solutions that can be scaled and managed easily as the business climate evolves. In the coming year, AI will start to become more democratized such that less technical people can directly leverage tools that abstract all the machine learning complexity. Knowledge workers and citizen “data scientists” without formal training in advanced statistics and/or mathematics will be extracting high-value insights from data using these self-service tools allowing them to perform advanced analytics and solve specific business problems at the speed of the business.—Ryan Welsh, founder and CEO of Kyndi
  • Responsible AI solutions—that address trust, risk, ethics, security, transparency—will gradually begin to become more mainstream: Solutions that target personalized insights—whether it is related to aspects such as credit risk, underwriting or simply recommendation engines for dynamic pricing or influencing buying decisions.—Nicolas Sekkaki, Kyndryl’s GM of applications, data and ai
  • Quantum computing emerges: An exciting trend in AI is quantum computing, which has been around for around 7 years but will have applications in the next 25 years or so. They're even more powerful than supercomputers in solving complex problems. Today's computers started development in the 1940s, but look at us now! Quantum computers will do the same for the future.—Erudit’s Chief Science Officer & Co-founder, Ricardo Michel Reyes
  • Offload low value tasks with AI: Repetitive tasks can easily drain productivity and keep you on your screen all day. Offloading a task like answering FAQs to an AI-powered help desk can create 25% more productive time in the work day. In 2023, SaaS companies will look more to AI to handle such tasks, allowing their workforce time for more fulfilling tasks and more human-to-human interaction.—Capacity CRO Tim Yeadon
  • Synthetic Data is the key to addressing generative AI ethical concerns: Generative AI has dominated headlines, and the hype surrounding the technology continues to grow. Data remains the most critical aspect in building generative AI systems, but using real-world data poses ethical and privacy concerns, including human data to train ID verification models. Development teams will increasingly use synthetic data when creating generative AI models, as it's artificial data created in simulated worlds and thus eliminates many biases and privacy concerns associated with datasets collected from the real world. AI adoption is steadily rising, with over 55% of organizations indicating AI as a core function in 2021, up from 50% in 2020. As innovation only continues to increase in the space, it will be imperative for organizations to invest in the tools and technologies that help mitigate bias imbalances and ensure generative AI models are built in a more ethical and privacy-compliant way.—Yashar Behzadi, CEO and founder of Synthesis AI
  • Big models for AI are driving innovations in specialized infrastructure and solutions: Over the past few years, AI and deep learning have become mainstream and reached the same maturity level as data analytics. Big models, from OpenAI’s DALL-E 2 image generation model to Google’s LaMDA conversation agent, are expected to dominate the landscape in 2023. Billions of files will be used to train big models for longer periods of time, requiring more specialized infrastructure and solutions. Next-generation AI infrastructure will be developed to handle the scale. –Haoyuan Li, Founder and CEO, Alluxio