IT firms are accelerating the adoption of technologies like digital humans and advanced artificial intelligence that can reason through cause and effect. This perspective aligns with Gartner’s Hype Cycle for Emerging Technologies, which analysts have spotlighted as shaping the next decade for competitive advantage in the United States and Canada.
Experts indicate that embracing these trends can offer a meaningful edge for organizations that strategically implement them within the next 2 to 10 years. The central idea is to harness AI and related tools to drive faster, more reliable outcomes in business processes, customer interactions, and product development.
Digital humans are described as interactive, AI-driven representations that carry elements of a real person, including certain knowledge, personality traits, and the capacity for thought. They function as responsive agents in customer service, training, and experiential marketing, blending visual presence with intelligent behavior to simulate human interaction at scale.
Gartner analysts expect that identifying and leveraging cause–effect relationships will reshape AI prediction systems in the near future. By understanding the causal links between actions and outcomes, AI can forecast results with higher confidence and proceed with greater autonomy, reducing the need for constant human intervention in routine decision-making.
This shift points toward AI systems that can anticipate needs, suggest courses of action, and execute agreed-upon tasks with minimal human oversight. It is a move from reactive AI to proactive, context-aware intelligence that can operate across complex environments with improved reliability and speed.
Within Gartner’s report, other technologies to watch include metadata storage solutions, non-fungible tokens, and the rise of superapplications. Analysts advise IT leaders to explore Web3 as a platform for building decentralized web applications that host a range of services where tokens may serve as a payment mechanism. These elements collectively describe a broader ecosystem that could redefine digital business models and user experiences in the coming years.
In the industry, a notable conversation surrounds claims by a former Google engineer asserting that the LaMDA AI system possesses human-like consciousness and emotions. While such statements generate discussion, the broader consensus in the field emphasizes rigorous testing, clear definitions of machine intelligence, and ongoing evaluation of AI capabilities against measurable benchmarks.