This webcast replay features Kofi Gyasi, CEO of NotedSource, and Dr. Anand Rao, Distinguished Professor at Carnegie Mellon University, discussing how Hybrid AI is redefining innovation.
You’ll learn about digital co-workers, streamlining literature review, and data analysis. The speakers share prompts that upskill teams and integrate workflows that balance AI insights with human creativity.
The session also addressed critical risks:
- Accuracy & Measurement
- Speed of Change
- Ethical Compliance.
The webcast included these two poll questions:
The slides used in this webcast are available for download in PDF form below. Here are five insights from the discussion.
1. AI Evolution and Adoption is Occurring at Multiple Speeds — And That’s OK
Rao emphasized that AI’s evolution and adoption occur at four distinct speeds: technology development (fastest), consumer use, enterprise adoption, and public sector regulation (slowest). Each level lags behind the one before it. Rao noted that “you don’t have to feel pressured to adopt everything that is coming out,” advocating instead a deliberate pace for enterprises so they can extract value from current models before chasing the next. He advised organizations to consider a “waiting” strategy in their build vs. buy vs. partner decisions, to avoid wasting resources on tools that may soon become outdated.
2. Use AI to Learn AI — Don’t Be Afraid of the Tools
To address lack of expertise and fear of complexity, Rao recommended a hands-on learning approach: “Use AI to learn about AI.” He encouraged experimenting with tools through methods like prompting models to critique and revise their own output, or cite evidence for their claims. This not only helps users improve their own understanding, but builds confidence in deploying AI in business settings. He added that white-coding and low-code tools are removing technical barriers, making AI more accessible for business users.
3. Trust and Safety Are Prerequisites for Responsible Enterprise Adoption
Rao outlined a “Maslow’s hierarchy” for enterprise AI adoption: first, address safety, security, and privacy; second, build explainability and interpretability to generate trust; third, aim for fairness and inclusivity; fourth, pursue competitive advantage; and finally, achieve sustainable and responsible use. He warned that hallucinations and liability risks remain real: “It doesn’t matter if your chatbot is hallucinating, you still have to pay up.”
4. Evaluate AI Tools by Matching Them to Specific Business Problems
Gyasi recommended that companies avoid falling for overhyped AI solutions by tying tool selection to specific needs: “Try to identify the AI solution that’s tailor-made for that problem.” He contrasted generic tool claims with focused, niche offerings that show direct impact. Rao added that agentic AI — digital co-workers that perceive, reason, and act — is not a new concept, but its capabilities have expanded significantly with LLMs. Still, success lies in evaluating these systems through pragmatic tests, not marketing claims.
5. Rethink How You Measure AI Impact
Rao critiqued traditional AI evaluation metrics like accuracy, calling them “easy to measure, not what should be measured.” He argued that ROI from AI must consider baseline comparisons against human performance, which are rarely captured or consistent. Instead, he recommended evaluating the outcomes of human-AI collaboration and understanding how both AI and humans evolve over time. “We say the AI is 95 percent accurate, but 95 percent with respect to whom?” Rao observed that many companies, academics, and vendors focus on metrics and benchmarks that are easy to quantify,rather than on those that actually reflect real-world performance or business impact.
Host Bios
Dr. Anand Rao
Anand Rao is a Distinguished Services Professor of Applied Data Science and AI in the Heinz College of Information Systems and Public Policy at Carnegie Mellon University. He teaches Operationalizing AI, Responsible AI, Applications of LLM, and Agent-Based Models & Digital Twins. He also serves as a Venture Partner at Golden Sparrow, an early-stage VC fund and is a Strategic Advisor at Innospark Ventures.
Kofi Gyasi
Kofi Gyasi is the co-founder and CEO of NotedSource – the platform that helps innovation and research teams access the information, expertise, and solutions needed to improve existing products and develop new solutions. Prior to founding NotedSource, Kofi was VP of R&D, Innovation and New Product Development at Citi, where he led initiatives to identify emerging technologies and incorporate them into the business. Before corporate innovation roles, Kofi was a research scientist at Vanderbilt University’s Medical Center. Passionate about helping companies address challenges quickly, Kofi received his MBA from the University of Michigan and his BA from Vanderbilt University.
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