University of Cincinnati

07/02/2026 | Press release | Distributed by Public on 07/02/2026 16:11

What is neuro-symbolic AI

What is neuro-symbolic AI?

This powerful form of AI mixes awareness of sequences with logic

7 minute read July 2, 2026 Share on Facebook Share on Twitter Share on LinkedIn Share on Reddit Print Story Like

Neuro-symbolic AI combines the pattern recognition capabilities of deep learning neural networks with the logical reasoning of symbolic AI.

The result is a smarter system of artificial intelligence that can draw insights from data while applying rules, facts and reasoning to reach reliable decisions.

Elhelo speaking during the AI+Robotics Summit 2026. Photo/Gregory Glevicky

As organizations search for AI systems that are more transparent, explainable and capable of complex decision-making, neuro-symbolic AI is emerging as one of the field's most promising developments. Its impressive abilities could dramatically influence how businesses, researchers and governments use artificial intelligence in the years ahead.

Ohad Elhelo, co-founder and CEO of AUI, spoke about the current state and future of neuro-symbolic AI during the University of Cincinnati's Future of Commerce: AI+Robotics Summit 2026. The signature event, hosted at the UC 1819 Innovation Hub and Digital Futures complex, brought together national leaders on automation-related topics.

Elhelo, a leading expert on neuro-symbolic AI, explained how this form of AI works, its top use cases and where the emerging technology is headed.

How does neuro-symbolic AI work?

Neuro-symbolic AI works by learning from data and applying logic to it to reach conclusions. The name "neuro-symbolic" refers to the two unique AI approaches the model combines: deep learning neural networks and symbolic AI.

Put simply, "neuro" learns as it goes while "symbolic" deduces from what it knows.

What are neural networks? right arrow down arrow

Deep learning neural networks are AI systems trained on massive amounts of data that identify relationships across it. These systems improve their performance by recognizing trends in large datasets rather than relying on predefined rules.

Large language models (LLMs) such as ChatGPT, Claude and Google Gemini mainly run on pattern recognition through a neural system.

"Neural approaches - deep learning - has driven all the great breakthroughs in AI in the past 10 years," Elhelo says. "It is always sampling from the data; it's always statistical, it doesn't have hard rules or guarantees."

What is symbolic AI? right arrow down arrow

Symbolic AI relies on predefined facts, rules and logic. Rather than learning patterns from massive datasets, it uses structured knowledge to draw conclusions and make decisions.

This is the more established form of AI, with research on it dating back to the 1950s.

"The first rule of symbolic says, 'I'm going to lay out a map in front of the model, and I'm going to show it what every entity means,'" Elhelo notes. "So, the AI will have a representation of what's in front of it."

Neuro-symbolic AI use cases

The unique traits of neuro-symbolic AI make it especially valuable in industries where decisions carry significant consequences. Organizations are increasingly exploring how neuro-symbolic AI can support professionals by providing explainable recommendations and insights.

Expect neuro-symbolic AI to play a supplemental role alongside human partners in the following fields:

  • Healthcare: Deep-learning neural networks could be given medical information to analyze while symbolic AI can then recommend next steps.
  • Law and compliance: As neural networks scan legal documents and records, symbolic AI determines which actions should be taken to fulfill laws and regulations.
  • Robotics and automation: Robots' neural characteristics allow them to perceive what's around them in warehouses and ecommerce settings, and then symbolic pieces come up with reasonable actions in response.
  • Scientific discovery: Neural networks can analyze vast datasets, and symbolic AI then applies scientific and mathematical concepts to formulate new findings.

Humans, according to Elhelo, remain critical in a world where neuro-symbolic AI is performing work. "AI cognition needs to not be opaque; it cannot be a black box," he says. That's because organizations need a clear way to evaluate AI-generated conclusions and understand how decisions are made.

Neuro-symbolic AI and agentic AI

Neuro-symbolic AI is increasingly viewed as a strong foundation for agentic AI because it packages together autonomy, reasoning and decision-making.

Microsoft has an innovation space at the 1819 Innovation Hub. Photo/Gregory Glevicky

Microsoft defined agentic AI as "an autonomous AI system that plans, reasons and acts to complete tasks with minimal human oversight" during an event held at UC's 1819 Innovation Hub. The tech giant, an 1819 partner company, has identified five characteristics of agentic AI:
  1. Autonomy
  2. Reasoning
  3. Adaptable planning
  4. Context understanding
  5. Action enabled

Since neuro-symbolic AI largely works independently using logical reasoning and context clues, there's huge appetite for it in the development of AI agents. After using a neuro-symbolic AI-based judgment model to reach a conclusion, these agents could act on behalf of customers.

An AI powerhouse in Cincinnati

The UC 1819 Innovation Hub and neighboring Digital Futures complex, two pieces of the growing Cincinnati Innovation District, are more than places where tech leaders learn about AI. They are environments where advances in artificial intelligence happen every day.

Companies like Procter & Gamble, Microsoft and Kroger, all 1819 industry partners, use AI and robotics to boost reliability, efficiency and productivity. Add AI-driven startups in the Venture Lab and forward-thinking firms like Sensory Robotics, and automation innovations are occurring at 1819.

UC's AI+Robotics Summit 2026 confirmed what innovators in Ohio already know: the future of artificial intelligence, powered by the rise of neuro-symbolic AI, is bright. Cincinnati is helping guide that future by bringing together national leaders, researchers and companies to shape tomorrow's innovations today.

Frequently asked questions

Does the UC 1819 Innovation Hub support AI startups? right arrow down arrow

Yes, the 1819 Innovation Hub encourages the growth of AI startups through the Venture Lab. This business accelerator connects tech startups with entrepreneurs in residence, helps them launch and scale ventures and gives founders access to the region's largest pool of nondilutive funding.

How can I learn about upcoming AI and technology events at 1819? right arrow down arrow

The 1819 Innovation Hub regularly hosts AI and technology events such as the AI+Robotics Summit, MidwestCon and various hackathons throughout the year. The best way to learn about upcoming tech- and AI-related events is by contacting us at [email protected].

What resources are available to AI firms at 1819? right arrow down arrow

AI companies in the 1819 Innovation Hub benefit from mentorship and training through the Venture Lab, rapid prototyping in the Ground Floor Makerspace, generous room for coworking, quick access to UC student talent and connections to leaders at tech firms like Microsoft, Sensory Robotics and Quest Defense.

Featured image at top: Neuro-symbolic AI has potential to be heavily used in robotics. Photo/Ole_CNX via iStock

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University of Cincinnati published this content on July 02, 2026, and is solely responsible for the information contained herein. Distributed via Public Technologies (PUBT), unedited and unaltered, on July 02, 2026 at 22:11 UTC. If you believe the information included in the content is inaccurate or outdated and requires editing or removal, please contact us at [email protected]